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@@ -11,5 +11,5 @@ runs:
|
||||
git fetch origin $CURRENT_SHA
|
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export COMMIT_MESSAGE=$(git show -s --format=%B "$CURRENT_SHA")
|
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export CURRENT_HEAD=$(git rev-parse HEAD)
|
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cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && IGNORE_OOB=1 PYTHONPATH=. python3 process_replay.py
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cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && CHECK_OOB=0 PYTHONPATH=. python3 process_replay.py
|
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git checkout $CURRENT_HEAD # restore to branch
|
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|
||||
@@ -56,7 +56,15 @@ runs:
|
||||
|
||||
# **** Caching packages ****
|
||||
|
||||
- name: Cache Python packages (PR)
|
||||
if: github.event_name == 'pull_request'
|
||||
id: restore-venv-pr
|
||||
uses: actions/cache/restore@v4
|
||||
with:
|
||||
path: ${{ github.workspace }}/.venv
|
||||
key: venv-${{ runner.os }}-python-${{ steps.setup-python.outputs.python-version }}-${{ inputs.deps }}-${{ inputs.pydeps }}-${{ env.CACHE_VERSION }}
|
||||
- name: Cache Python packages
|
||||
if: github.event_name != 'pull_request'
|
||||
id: restore-venv
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
@@ -65,23 +73,23 @@ runs:
|
||||
|
||||
# **** Caching downloads ****
|
||||
|
||||
- name: Cache downloads (Linux)
|
||||
if: inputs.key != '' && runner.os == 'Linux'
|
||||
uses: actions/cache@v4
|
||||
- name: Cache downloads (PR)
|
||||
if: inputs.key != '' && github.event_name == 'pull_request'
|
||||
uses: actions/cache/restore@v4
|
||||
with:
|
||||
path: ~/.cache/tinygrad/downloads/
|
||||
path: ${{ runner.os == 'Linux' && '~/.cache/tinygrad/downloads/' || '~/Library/Caches/tinygrad/downloads/' }}
|
||||
key: downloads-${{ github.job }}-${{ inputs.key }}-${{ env.CACHE_VERSION }}
|
||||
- name: Cache downloads (macOS)
|
||||
if: inputs.key != '' && runner.os == 'macOS'
|
||||
- name: Cache downloads
|
||||
if: inputs.key != '' && github.event_name != 'pull_request'
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/Library/Caches/tinygrad/downloads/
|
||||
path: ${{ runner.os == 'Linux' && '~/.cache/tinygrad/downloads/' || '~/Library/Caches/tinygrad/downloads/' }}
|
||||
key: downloads-${{ github.job }}-${{ inputs.key }}-${{ env.CACHE_VERSION }}
|
||||
|
||||
# **** Python deps ****
|
||||
|
||||
- name: Install dependencies in venv (with extra)
|
||||
if: inputs.deps != '' && steps.restore-venv.outputs.cache-hit != 'true'
|
||||
if: inputs.deps != '' && steps.restore-venv-pr.outputs.cache-hit != 'true' && steps.restore-venv.outputs.cache-hit != 'true'
|
||||
shell: bash
|
||||
run: |
|
||||
python -m venv .venv
|
||||
@@ -92,7 +100,7 @@ runs:
|
||||
fi
|
||||
python -m pip install -e ".[${{ inputs.deps }}]" ${{ inputs.pydeps }} --extra-index-url https://download.pytorch.org/whl/cpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/Triton-Nightly/pypi/simple/
|
||||
- name: Install dependencies in venv (without extra)
|
||||
if: inputs.deps == '' && steps.restore-venv.outputs.cache-hit != 'true'
|
||||
if: inputs.deps == '' && steps.restore-venv-pr.outputs.cache-hit != 'true' && steps.restore-venv.outputs.cache-hit != 'true'
|
||||
shell: bash
|
||||
run: |
|
||||
python -m venv .venv
|
||||
@@ -182,8 +190,14 @@ runs:
|
||||
echo "pkgs=$pkgs" >> "$GITHUB_OUTPUT"
|
||||
echo "hash=$(echo -n "$pkgs" | sha256sum | cut -d' ' -f1)" >> "$GITHUB_OUTPUT"
|
||||
|
||||
- name: Cache apt (PR)
|
||||
if: runner.os == 'Linux' && (inputs.opencl == 'true' || inputs.amd == 'true' || inputs.cuda == 'true' || inputs.webgpu == 'true' || inputs.llvm == 'true') && github.event_name == 'pull_request'
|
||||
uses: actions/cache/restore@v4
|
||||
with:
|
||||
path: /var/cache/apt/archives/
|
||||
key: ${{ runner.os }}-apt-${{ steps.apt-pkgs.outputs.hash }}-${{ env.CACHE_VERSION }}
|
||||
- name: Cache apt
|
||||
if: runner.os == 'Linux' && (inputs.opencl == 'true' || inputs.amd == 'true' || inputs.cuda == 'true' || inputs.webgpu == 'true' || inputs.llvm == 'true')
|
||||
if: runner.os == 'Linux' && (inputs.opencl == 'true' || inputs.amd == 'true' || inputs.cuda == 'true' || inputs.webgpu == 'true' || inputs.llvm == 'true') && github.event_name != 'pull_request'
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: /var/cache/apt/archives/
|
||||
@@ -239,8 +253,17 @@ runs:
|
||||
ln -s /opt/homebrew/opt/[email protected] /opt/homebrew/opt/boost || true
|
||||
ln -s /opt/homebrew/opt/boost/lib/libboost_atomic-mt.dylib /opt/homebrew/opt/boost/lib/libboost_atomic.dylib || true
|
||||
ln -s /opt/homebrew/opt/boost/lib/libboost_thread-mt.dylib /opt/homebrew/opt/boost/lib/libboost_thread.dylib || true
|
||||
- name: Cache gpuocelot (PR)
|
||||
if: inputs.ocelot == 'true' && github.event_name == 'pull_request'
|
||||
id: cache-build-pr
|
||||
uses: actions/cache/restore@v4
|
||||
env:
|
||||
cache-name: cache-gpuocelot-build-1
|
||||
with:
|
||||
path: ${{ github.workspace }}/gpuocelot/ocelot
|
||||
key: ${{ runner.os }}-gpuocelot-b16039dc940dc6bc4ea0a98380495769ff35ed99-rebuild-${{ env.CACHE_VERSION }}
|
||||
- name: Cache gpuocelot
|
||||
if: inputs.ocelot == 'true'
|
||||
if: inputs.ocelot == 'true' && github.event_name != 'pull_request'
|
||||
id: cache-build
|
||||
uses: actions/cache@v4
|
||||
env:
|
||||
@@ -249,7 +272,7 @@ runs:
|
||||
path: ${{ github.workspace }}/gpuocelot/ocelot
|
||||
key: ${{ runner.os }}-gpuocelot-b16039dc940dc6bc4ea0a98380495769ff35ed99-rebuild-${{ env.CACHE_VERSION }}
|
||||
- name: Clone/compile gpuocelot
|
||||
if: inputs.ocelot == 'true' && steps.cache-build.outputs.cache-hit != 'true'
|
||||
if: inputs.ocelot == 'true' && steps.cache-build-pr.outputs.cache-hit != 'true' && steps.cache-build.outputs.cache-hit != 'true'
|
||||
shell: bash
|
||||
run: |
|
||||
git clone --recurse-submodules https://github.com/gpuocelot/gpuocelot.git ${{ github.workspace }}/gpuocelot
|
||||
|
||||
@@ -40,13 +40,13 @@ jobs:
|
||||
mesa: 'true'
|
||||
pydeps: 'pyyaml mako'
|
||||
- name: Install autogen support packages
|
||||
run: sudo apt-get install -y --no-install-recommends libclang-20-dev llvm-20-dev hip-dev libusb-1.0-0-dev
|
||||
run: sudo apt-get install -y --no-install-recommends libclang-20-dev llvm-20-dev hip-dev libusb-1.0-0-dev libdrm-dev
|
||||
- name: Regenerate autogen files
|
||||
run: |
|
||||
find tinygrad/runtime/autogen -type f -name "*.py" -not -name "__init__.py" -not -name "comgr_3.py" -not -name "metal.py" -not -name "libclang.py" -delete
|
||||
find tinygrad/runtime/autogen -type f -name "*.py" -not -path "*/amd/*" -not -name "__init__.py" -not -name "comgr_3.py" -not -name "metal.py" -not -name "iokit.py" -not -name "corefoundation.py" -not -name "libclang.py" -delete
|
||||
python3 -c "from tinygrad.runtime.autogen import opencl"
|
||||
python3 -c "from tinygrad.runtime.autogen import cuda, nvrtc, nvjitlink, nv_570, nv_580, nv"
|
||||
python3 -c "from tinygrad.runtime.autogen import comgr, hsa, hip, amd_gpu, sqtt, rocprof, amdgpu_kd"
|
||||
python3 -c "from tinygrad.runtime.autogen import comgr, hsa, hip, amd_gpu, sqtt, rocprof, amdgpu_kd, amdgpu_drm"
|
||||
python3 -c "from tinygrad.runtime.autogen.am import am, pm4_soc15, pm4_nv, sdma_4_0_0, sdma_5_0_0, sdma_6_0_0, smu_v13_0_0, smu_v13_0_6, smu_v14_0_2"
|
||||
python3 -c "from tinygrad.runtime.autogen import libc, kfd, io_uring, ib, pci, vfio"
|
||||
python3 -c "from tinygrad.runtime.autogen import llvm"
|
||||
@@ -83,8 +83,8 @@ jobs:
|
||||
llvm: 'true'
|
||||
- name: Regenerate autogen files
|
||||
run: |
|
||||
rm tinygrad/runtime/autogen/metal.py
|
||||
LIBCLANG_PATH=/opt/homebrew/opt/llvm@20/lib/libclang.dylib python3 -c "from tinygrad.runtime.autogen import metal"
|
||||
rm tinygrad/runtime/autogen/metal.py tinygrad/runtime/autogen/iokit.py tinygrad/runtime/autogen/corefoundation.py
|
||||
python3 -c "from tinygrad.runtime.autogen import metal, iokit, corefoundation"
|
||||
- name: Check for differences
|
||||
run: |
|
||||
if ! git diff --quiet; then
|
||||
|
||||
@@ -16,6 +16,48 @@ on:
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
# the goal of this test is to replicate a normal person on a laptop running the test
|
||||
# no process replay, no benchmarks, no CI, just a normal laptop person
|
||||
# the 3 minute timeout should not be raised
|
||||
testmacpytest:
|
||||
name: Mac pytest
|
||||
runs-on: [self-hosted, macOS]
|
||||
timeout-minutes: 3
|
||||
defaults:
|
||||
run:
|
||||
shell: bash -e -o pipefail {0}
|
||||
if: github.repository_owner == 'tinygrad'
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v4
|
||||
# brew install uv
|
||||
- name: setup python environment
|
||||
run: |
|
||||
rm -rf /tmp/tinygrad_pytest_ci
|
||||
uv venv /tmp/tinygrad_pytest_ci
|
||||
source /tmp/tinygrad_pytest_ci/bin/activate
|
||||
uv pip install .[testing]
|
||||
- name: setup staging db
|
||||
run: |
|
||||
echo "CACHEDB=/tmp/pytest-db-ci.db" >> $GITHUB_ENV
|
||||
rm -f /tmp/pytest-db-ci*
|
||||
# TODO: remove this step once all old caches are migrated
|
||||
- name: Migrate old huggingface cache (symlinks break onnxruntime 1.24+)
|
||||
run: |
|
||||
cd ~/Library/Caches/tinygrad/downloads/models 2>/dev/null || exit 0
|
||||
for old_dir in models--*; do
|
||||
[ -d "$old_dir" ] || continue
|
||||
repo_id=$(echo "$old_dir" | sed 's/models--//; s/--/\//g')
|
||||
snapshot=$(ls -1 "$old_dir/snapshots" 2>/dev/null | head -1)
|
||||
[ -n "$snapshot" ] || continue
|
||||
mkdir -p "$repo_id"
|
||||
cp -RLn "$old_dir/snapshots/$snapshot/"* "$repo_id/" 2>/dev/null || true
|
||||
done
|
||||
- name: Run pytest -nauto
|
||||
run: |
|
||||
source /tmp/tinygrad_pytest_ci/bin/activate
|
||||
pytest -nauto --durations=20
|
||||
|
||||
testmacbenchmark:
|
||||
name: Mac Benchmark
|
||||
env:
|
||||
@@ -145,6 +187,10 @@ jobs:
|
||||
run: |
|
||||
echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
|
||||
rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
|
||||
- name: Kill stale pids
|
||||
run: |
|
||||
PYTHONPATH=. ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
PYTHONPATH=. ./extra/hcq/hcq_smi.py nv kill_pids
|
||||
- name: UsbGPU boot time
|
||||
run: sudo -E PYTHONPATH=. DEBUG=2 AM_RESET=1 AMD=1 AMD_IFACE=USB time python3.11 test/test_tiny.py TestTiny.test_plus
|
||||
- name: UsbGPU tiny tests
|
||||
@@ -332,9 +378,9 @@ jobs:
|
||||
- name: Setcap to python
|
||||
run: ./extra/amdpci/setup_python_cap.sh
|
||||
- name: Remove amd modules
|
||||
run: ./extra/hcq/hcq_smi.py amd rmmod
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd rmmod
|
||||
- name: Kill stale pids
|
||||
run: ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
#- name: Insert amdgpu
|
||||
# run: sudo modprobe amdgpu
|
||||
- name: Symlink models and datasets
|
||||
@@ -444,9 +490,9 @@ jobs:
|
||||
- name: Setcap to python
|
||||
run: ./extra/amdpci/setup_python_cap.sh
|
||||
- name: Remove amd modules
|
||||
run: ./extra/hcq/hcq_smi.py amd rmmod
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd rmmod
|
||||
- name: Kill stale pids
|
||||
run: ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
- name: Symlink models and datasets
|
||||
run: |
|
||||
mkdir -p weights
|
||||
@@ -479,6 +525,8 @@ jobs:
|
||||
run: time BENCHMARK_LOG=cifar AMD=1 DEFAULT_FLOAT=HALF STEPS=1000 TARGET_EVAL_ACC_PCT=93.0 python3 examples/hlb_cifar10.py
|
||||
- name: Run full CIFAR training steps w 6 GPUS
|
||||
run: time BENCHMARK_LOG=cifar_6gpu AMD=1 DEFAULT_FLOAT=HALF STEPS=350 BS=1536 GPUS=6 TARGET_EVAL_ACC_PCT=93.0 python3 examples/hlb_cifar10.py
|
||||
- name: Test full tinyfs load
|
||||
run: TINYFS_ENDPOINT=10.0.52.11:6767 PYTHONPATH=. python extra/tinyfs/fetch_file.py --hash d734f5e3be9f1e9d863bfaa4fc6c1ef2 --len 175866113 --dest mapping.json --check
|
||||
- name: Run process replay tests
|
||||
run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
|
||||
|
||||
@@ -496,9 +544,9 @@ jobs:
|
||||
- name: Setcap to python
|
||||
run: ./extra/amdpci/setup_python_cap.sh
|
||||
- name: Remove amd modules
|
||||
run: ./extra/hcq/hcq_smi.py amd rmmod
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd rmmod
|
||||
- name: Kill stale pids
|
||||
run: ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
- name: Symlink models and datasets
|
||||
run: |
|
||||
mkdir -p weights
|
||||
@@ -561,7 +609,7 @@ jobs:
|
||||
- name: openpilot compile3 0.10.1 driving_policy
|
||||
run: BENCHMARK_LOG=openpilot_0_10_1_policy PYTHONPATH="." ASSERT_MIN_STEP_TIME=3 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/driving_policy.onnx
|
||||
- name: openpilot compile3 0.10.1 dmonitoring
|
||||
run: BENCHMARK_LOG=openpilot_0_10_1_dmonitoring PYTHONPATH="." ASSERT_MIN_STEP_TIME=10 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/dmonitoring_model.onnx
|
||||
run: BENCHMARK_LOG=openpilot_0_10_1_dmonitoring PYTHONPATH="." ASSERT_MIN_STEP_TIME=11 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/dmonitoring_model.onnx
|
||||
- name: benchmark MobileNetV2 on DSP
|
||||
run: |
|
||||
# generate quantized weights
|
||||
@@ -587,9 +635,9 @@ jobs:
|
||||
- name: Setcap to python
|
||||
run: ./extra/amdpci/setup_python_cap.sh
|
||||
- name: Remove amd modules
|
||||
run: ./extra/hcq/hcq_smi.py amd rmmod
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd rmmod
|
||||
- name: Kill stale pids
|
||||
run: ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py amd kill_pids
|
||||
- name: Symlink models and datasets
|
||||
run: |
|
||||
mkdir -p weights
|
||||
@@ -651,9 +699,9 @@ jobs:
|
||||
- name: Setcap to python
|
||||
run: ./extra/amdpci/setup_python_cap.sh
|
||||
- name: Remove nv modules
|
||||
run: ./extra/hcq/hcq_smi.py nv rmmod
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py nv rmmod
|
||||
- name: Kill stale pids
|
||||
run: ./extra/hcq/hcq_smi.py nv kill_pids
|
||||
run: PYTHONPATH=. ./extra/hcq/hcq_smi.py nv kill_pids
|
||||
- name: Symlink models and datasets
|
||||
run: |
|
||||
mkdir -p weights
|
||||
|
||||
+134
-112
@@ -1,11 +1,11 @@
|
||||
name: Unit Tests
|
||||
env:
|
||||
# increment this when downloads substantially change to avoid the internet
|
||||
CACHE_VERSION: '15'
|
||||
CACHE_VERSION: '16'
|
||||
CAPTURE_PROCESS_REPLAY: 1
|
||||
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
PYTHONPATH: ${{ github.workspace }}
|
||||
IGNORE_OOB: 0
|
||||
CHECK_OOB: 1
|
||||
|
||||
on:
|
||||
push:
|
||||
@@ -26,19 +26,19 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: llvm-speed
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
llvm: 'true'
|
||||
- name: Speed Test
|
||||
run: CPU=1 CPU_LLVM=1 python3 test/speed/external_test_speed_v_torch.py
|
||||
run: CPU=1 CPU_LLVM=1 THREADS=0 python3 test/speed/external_test_speed_v_torch.py
|
||||
- name: Speed Test (BEAM=2)
|
||||
run: BEAM=2 CPU=1 CPU_LLVM=1 python3 test/speed/external_test_speed_v_torch.py
|
||||
run: BEAM=2 CPU=1 CPU_LLVM=1 THREADS=0 python3 test/speed/external_test_speed_v_torch.py
|
||||
|
||||
docs:
|
||||
name: Docs
|
||||
runs-on: ubuntu-22.04
|
||||
timeout-minutes: 10
|
||||
env:
|
||||
IGNORE_OOB: 1
|
||||
CHECK_OOB: 0
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v4
|
||||
@@ -98,7 +98,7 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: torch-backend-pillow-torchvision-et-pt
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
pydeps: "pillow torchvision expecttest"
|
||||
llvm: 'true'
|
||||
- name: Install ninja
|
||||
@@ -106,7 +106,7 @@ jobs:
|
||||
sudo apt update || true
|
||||
sudo apt install -y --no-install-recommends ninja-build
|
||||
- name: Test one op
|
||||
run: FORWARD_ONLY=1 TINY_BACKEND=1 python3 test/test_ops.py TestOps.test_add
|
||||
run: FORWARD_ONLY=1 TINY_BACKEND=1 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Test ResNet-18
|
||||
run: DEBUG=2 python3 extra/torch_backend/example.py
|
||||
- name: custom tests
|
||||
@@ -114,7 +114,7 @@ jobs:
|
||||
- name: Test one op in torch tests
|
||||
run: DEBUG=2 python3 extra/torch_backend/torch_tests.py TestTinyBackendPRIVATEUSE1.test_unary_log_tiny_float32
|
||||
- name: Test Ops with TINY_BACKEND
|
||||
run: CPU=1 CPU_LLVM=1 LLVMOPT=0 TINY_BACKEND=1 python3 -m pytest -n auto test/test_ops.py --durations=20
|
||||
run: CPU=1 CPU_LLVM=1 LLVMOPT=0 TINY_BACKEND=1 python3 -m pytest -n auto test/backend/test_ops.py --durations=20
|
||||
- name: Test in-place operations on views
|
||||
run: TORCH_DEBUG=1 python3 extra/torch_backend/test_inplace.py
|
||||
- name: Test multi-gpu
|
||||
@@ -134,7 +134,7 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: torch-backend-pillow-torchvision-et-pt
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
llvm: 'true'
|
||||
- name: Install ninja
|
||||
run: |
|
||||
@@ -156,27 +156,27 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: be-minimal
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
- name: Test dtype with Python emulator
|
||||
run: DEBUG=1 PYTHON=1 python3 -m pytest -n=auto test/test_dtype.py test/test_dtype_alu.py
|
||||
run: DEBUG=1 PYTHON=1 python3 -m pytest -n=auto test/backend/test_dtype.py test/backend/test_dtype_alu.py
|
||||
- name: Test ops with Python emulator
|
||||
run: DEBUG=2 SKIP_SLOW_TEST=1 PYTHON=1 python3 -m pytest -n=auto test/test_ops.py --durations=20
|
||||
run: DEBUG=2 SKIP_SLOW_TEST=1 PYTHON=1 python3 -m pytest -n=auto test/backend/test_ops.py --durations=20
|
||||
- name: Test uops with Python emulator
|
||||
run: PYTHON=1 python3 -m pytest test/test_uops.py --durations=20
|
||||
run: PYTHON=1 python3 -m pytest test/backend/test_uops.py --durations=20
|
||||
- name: Test symbolic with Python emulator
|
||||
run: PYTHON=1 python3 test/test_symbolic_ops.py
|
||||
run: PYTHON=1 python3 test/backend/test_symbolic_ops.py
|
||||
- name: test_renderer_failures with Python emulator
|
||||
run: PYTHON=1 python3 -m pytest -rA test/test_renderer_failures.py::TestRendererFailures
|
||||
run: PYTHON=1 python3 -m pytest -rA test/backend/test_renderer_failures.py::TestRendererFailures
|
||||
- name: Test IMAGE=2 support
|
||||
run: |
|
||||
IMAGE=2 PYTHON=1 python3 test/test_ops.py TestOps.test_gemm
|
||||
IMAGE=2 PYTHON=1 python3 test/test_ops.py TestOps.test_simple_conv2d
|
||||
IMAGE=2 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_gemm
|
||||
IMAGE=2 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_simple_conv2d
|
||||
- name: Test emulated METAL tensor cores
|
||||
run: |
|
||||
DEBUG=2 EMULATE=METAL FORWARD_ONLY=1 PYTHON=1 python3 test/test_ops.py TestOps.test_big_gemm
|
||||
DEBUG=2 EMULATE=METAL FORWARD_ONLY=1 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_big_gemm
|
||||
DEBUG=2 EMULATE=METAL FORWARD_ONLY=1 PYTHON=1 python3 test/opt/test_tensor_cores.py
|
||||
- name: Test emulated AMX tensor cores
|
||||
run: DEBUG=2 AMX=1 EMULATE=AMX FORWARD_ONLY=1 PYTHON=1 python3 test/test_ops.py TestOps.test_gemm
|
||||
run: DEBUG=2 AMX=1 EMULATE=AMX FORWARD_ONLY=1 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_gemm
|
||||
- name: Test emulated AMD tensor cores
|
||||
run: |
|
||||
DEBUG=2 EMULATE=AMD FORWARD_ONLY=1 PYTHON=1 N=16 HALF=1 ACC_HALF=0 python3 ./extra/gemm/simple_matmul.py
|
||||
@@ -197,9 +197,9 @@ jobs:
|
||||
DEBUG=2 EMULATE=AMD_RDNA4 FORWARD_ONLY=1 PYTHON=1 python3 test/opt/test_tensor_cores.py
|
||||
- name: Test emulated CUDA tensor cores
|
||||
run: |
|
||||
DEBUG=2 EMULATE=CUDA FORWARD_ONLY=1 PYTHON=1 python3 test/test_ops.py TestOps.test_gemm_fp16
|
||||
DEBUG=2 EMULATE=CUDA ALLOW_TF32=1 FORWARD_ONLY=1 PYTHON=1 python3 test/test_ops.py TestOps.test_gemm
|
||||
DEBUG=2 EMULATE=CUDA_SM75 FORWARD_ONLY=1 PYTHON=1 python3 test/test_ops.py TestOps.test_gemm_fp16
|
||||
DEBUG=2 EMULATE=CUDA FORWARD_ONLY=1 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_gemm_fp16
|
||||
DEBUG=2 EMULATE=CUDA ALLOW_TF32=1 FORWARD_ONLY=1 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_gemm
|
||||
DEBUG=2 EMULATE=CUDA_SM75 FORWARD_ONLY=1 PYTHON=1 python3 test/backend/test_ops.py TestOps.test_gemm_fp16
|
||||
DEBUG=2 EMULATE=CUDA_SM89 ALLOW_TF32=1 FORWARD_ONLY=1 PYTHON=1 python3 test/opt/test_tensor_cores.py
|
||||
- name: Test emulated INTEL OpenCL tensor cores
|
||||
run: DEBUG=2 EMULATE=INTEL FORWARD_ONLY=1 PYTHON=1 HALF=1 N=64 python3 ./extra/gemm/simple_matmul.py
|
||||
@@ -207,11 +207,11 @@ jobs:
|
||||
run: DEBUG=2 AMX=1 EMULATE=AMX FORWARD_ONLY=1 PYTHON=1 python3 test/opt/test_tensor_cores.py
|
||||
- name: Test device flop counts
|
||||
run: |
|
||||
DEBUG=2 EMULATE=METAL PYTHON=1 python3 ./test/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=AMD PYTHON=1 python3 ./test/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=CUDA PYTHON=1 python3 ./test/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=INTEL PYTHON=1 python3 ./test/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 AMX=1 EMULATE=AMX PYTHON=1 python3 ./test/test_uops_stats.py TestUOpsStats.test_simple_matmul
|
||||
DEBUG=2 EMULATE=METAL PYTHON=1 python3 ./test/null/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=AMD PYTHON=1 python3 ./test/null/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=CUDA PYTHON=1 python3 ./test/null/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 EMULATE=INTEL PYTHON=1 python3 ./test/null/test_uops_stats.py TestUOpsStatsMatmulHalf
|
||||
DEBUG=2 AMX=1 EMULATE=AMX PYTHON=1 python3 ./test/null/test_uops_stats.py TestUOpsStats.test_simple_matmul
|
||||
|
||||
linter:
|
||||
name: Linters
|
||||
@@ -229,19 +229,20 @@ jobs:
|
||||
deps: linting
|
||||
- name: Lint bad-indentation and trailing-whitespace with pylint
|
||||
run: python -m pylint --disable=all -e W0311 -e C0303 --jobs=0 --indent-string=' ' --recursive=y .
|
||||
- name: Lint with ruff
|
||||
- name: Run pre-commit linting hooks
|
||||
run: SKIP=tiny,tests,example pre-commit run --all-files
|
||||
- name: Lint additional files with ruff
|
||||
run: |
|
||||
pip3 install --upgrade --force-reinstall ruff==0.14.10
|
||||
pre-commit run ruff --all-files
|
||||
python3 -m ruff check examples/mlperf/ --ignore E501
|
||||
python3 -m ruff check extra/thunder/tiny/ --ignore E501 --ignore F841 --ignore E722
|
||||
python3 -m ruff check extra/torch_backend/backend.py
|
||||
- name: Run mypy
|
||||
- name: Run mypy with lineprecision report
|
||||
run: |
|
||||
python -m mypy --lineprecision-report .
|
||||
grep -v autogen lineprecision.txt | awk 'NR>2 {lines+=$2; precise+=$3; imprecise+=$4; any+=$5; empty+=$6} END {t=lines-empty; printf "TOTAL: %d lines, %d precise (%.1f%%), %d imprecise (%.1f%%), %d any (%.1f%%)\n", t, precise, 100*precise/t, imprecise, 100*imprecise/t, any, 100*any/t}'
|
||||
cat lineprecision.txt
|
||||
- name: Run TYPED=1
|
||||
run: TYPED=1 python -c "import tinygrad"
|
||||
run: CHECK_OOB=0 DEV=CPU TYPED=1 python test/test_tiny.py
|
||||
|
||||
unittest:
|
||||
name: Unit Tests
|
||||
@@ -254,25 +255,30 @@ jobs:
|
||||
- name: Setup Environment
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: unittest-12
|
||||
pydeps: "pillow numpy ftfy regex"
|
||||
key: unittest-13
|
||||
pydeps: "pillow ftfy regex pre-commit"
|
||||
deps: testing_unit
|
||||
llvm: 'true'
|
||||
amd: 'true'
|
||||
- name: Run pre-commit test hooks
|
||||
run: SKIP=ruff,mypy pre-commit run --all-files
|
||||
- name: Check Device.DEFAULT
|
||||
run: python -c "from tinygrad import Device; assert Device.DEFAULT == 'CPU', Device.DEFAULT"
|
||||
- name: Run unit tests
|
||||
run: |
|
||||
CPU=1 python test/unit/test_device.py TestRunAsModule.test_module_runs
|
||||
CPU=1 python -m pytest -n=auto test/unit/ --durations=20 --deselect=test/unit/test_device.py::TestRunAsModule::test_module_runs
|
||||
CPU=1 python test/null/test_device.py TestRunAsModule.test_module_runs
|
||||
CPU=1 python -m pytest -n=auto test/unit/ --durations=20
|
||||
- name: Run NULL backend tests
|
||||
run: NULL=1 python -m pytest -n=auto test/null/ --durations=20
|
||||
- name: Run targetted tests on NULL backend
|
||||
run: NULL=1 python3 -m unittest test.test_multitensor.TestMultiTensor.test_data_parallel_resnet_train_step test/device/test_null.py
|
||||
run: NULL=1 python3 -m unittest test.backend.test_multitensor.TestMultiTensor.test_data_parallel_resnet_train_step
|
||||
# TODO: too slow
|
||||
# - name: Run SDXL on NULL backend
|
||||
# run: NULL=1 DEBUG=1 python3 examples/sdxl.py --seed 0 --noshow --timing --fakeweights
|
||||
- name: Run Clip tests for SD MLPerf on NULL backend
|
||||
run: NULL=1 python -m pytest -n=auto test/external/mlperf_stable_diffusion/external_test_models.py::TestOpenClip --durations=20
|
||||
- name: Run AMD emulated BERT training on NULL backend
|
||||
run: EMULATE=AMD_RDNA4 NULL=1 CAPTURE_PROCESS_REPLAY=0 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=66 GPUS=1 BERT_LAYERS=2 MODEL=bert python3 examples/mlperf/model_train.py
|
||||
run: EMULATE=AMD_RDNA4 NULL=1 NULL_ALLOW_COPYOUT=1 CAPTURE_PROCESS_REPLAY=0 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=66 GPUS=1 BERT_LAYERS=2 MODEL=bert python3 examples/mlperf/model_train.py
|
||||
# TODO: support fake weights
|
||||
#- name: Run LLaMA 7B on 4 fake devices
|
||||
# run: NULL=1 python3 examples/llama.py --gen 1 --size 7B --shard 4 --prompt "Hello." --count 3 --temperature 0 --timing
|
||||
@@ -289,8 +295,8 @@ jobs:
|
||||
python extra/optimization/extract_dataset.py
|
||||
gzip -c /tmp/sops > extra/datasets/sops.gz
|
||||
#DEBUG=1 MIN_ASTS=1 python extra/optimization/get_action_space.py
|
||||
- name: Repo line count < 20000 lines
|
||||
run: MAX_LINE_COUNT=20000 python sz.py
|
||||
- name: Repo line count < 24000 lines
|
||||
run: MAX_LINE_COUNT=24000 python sz.py
|
||||
|
||||
spec:
|
||||
strategy:
|
||||
@@ -310,7 +316,7 @@ jobs:
|
||||
deps: testing_unit
|
||||
python-version: '3.14'
|
||||
- name: Test SPEC=2
|
||||
run: SPEC=2 pytest --maxfail=10 -n auto --durations=30 --ignore=test/models --ignore test/test_custom_kernel.py --ignore test/unit/test_hashing.py --ignore test/unit/test_autogen.py --timeout 60 -k "not test_setitem_big" --splits 2 --group ${{ matrix.group }}
|
||||
run: SPEC=2 pytest --maxfail=10 -n auto --durations=30 test/unit test/backend test/opt --ignore test/backend/test_custom_kernel.py --ignore test/unit/test_hashing.py --timeout 60 -k "not test_setitem_big" --splits 2 --group ${{ matrix.group }}
|
||||
|
||||
fuzzing:
|
||||
name: Fuzzing
|
||||
@@ -344,11 +350,11 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: gpu-image
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
opencl: 'true'
|
||||
- name: Test CL IMAGE=2 ops
|
||||
run: |
|
||||
CL=1 IMAGE=2 python -m pytest -n=auto test/test_ops.py --durations=20
|
||||
CL=1 IMAGE=2 python -m pytest -n=auto test/backend/test_ops.py --durations=20
|
||||
# TODO: training is broken
|
||||
# CL=1 IMAGE=2 python test/models/test_end2end.py TestEnd2End.test_linear_mnist
|
||||
- name: Run process replay tests
|
||||
@@ -365,14 +371,14 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: gen-dataset
|
||||
deps: testing_minimal
|
||||
deps: testing
|
||||
opencl: 'true'
|
||||
- name: Generate Dataset
|
||||
run: CL=1 extra/optimization/generate_dataset.sh
|
||||
- name: Run Kernel Count Test
|
||||
run: CL=1 python -m pytest -n=auto test/external/external_test_opt.py
|
||||
- name: Run fused optimizer tests
|
||||
run: CL=1 FUSE_OPTIM=1 python -m pytest -n=auto test/models/test_mnist.py test/test_optim.py -k "not muon"
|
||||
run: CL=1 FUSE_OPTIM=1 python -m pytest -n=auto test/models/test_mnist.py test/backend/test_optim.py -k "not muon"
|
||||
- name: Upload artifact
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
@@ -420,7 +426,7 @@ jobs:
|
||||
with:
|
||||
key: onnxoptc
|
||||
deps: testing
|
||||
python-version: '3.11'
|
||||
python-version: '3.12'
|
||||
llvm: 'true'
|
||||
- name: Test ONNX (CPU)
|
||||
run: CPU=1 CPU_LLVM=0 python -m pytest -n=auto test/external/external_test_onnx_backend.py --durations=20
|
||||
@@ -431,7 +437,7 @@ jobs:
|
||||
- name: Test Additional ONNX Ops (CPU)
|
||||
run: CPU=1 CPU_LLVM=0 python3 test/external/external_test_onnx_ops.py
|
||||
- name: Test Quantize ONNX
|
||||
run: CPU=1 CPU_LLVM=0 python3 test/test_quantize_onnx.py
|
||||
run: CPU=1 CPU_LLVM=0 python3 test/backend/test_quantize_onnx.py
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
@@ -448,7 +454,7 @@ jobs:
|
||||
key: onnxoptl
|
||||
deps: testing
|
||||
pydeps: "tensorflow==2.19"
|
||||
python-version: '3.11'
|
||||
python-version: '3.12'
|
||||
opencl: 'true'
|
||||
- name: Test ONNX (CL)
|
||||
run: CL=1 python -m pytest -n=auto test/external/external_test_onnx_backend.py --durations=20
|
||||
@@ -461,11 +467,11 @@ jobs:
|
||||
- name: Test MLPerf stuff
|
||||
run: CL=1 python -m pytest -n=auto test/external/external_test_optim.py test/external/external_test_losses.py test/external/external_test_metrics.py test/external/external_test_datasets.py --durations=20
|
||||
- name: NULL=1 beautiful_mnist_multigpu
|
||||
run: NULL=1 python examples/beautiful_mnist_multigpu.py
|
||||
run: NULL=1 NULL_ALLOW_COPYOUT=1 python examples/beautiful_mnist_multigpu.py
|
||||
- name: Test Bert training
|
||||
run: NULL=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=24 GPUS=4 BERT_LAYERS=2 MODEL=bert python3 examples/mlperf/model_train.py
|
||||
run: NULL=1 NULL_ALLOW_COPYOUT=1 DEFAULT_FLOAT=HALF BENCHMARK=10 BS=24 GPUS=4 BERT_LAYERS=2 MODEL=bert python3 examples/mlperf/model_train.py
|
||||
- name: Test llama 3 training
|
||||
run: NULL=1 SAMPLES=300 BS=8 SEQLEN=512 GRADIENT_ACC_STEPS=1 FAKEDATA=1 DEFAULT_FLOAT=bfloat16 OPTIM_DTYPE=bfloat16 LLAMA3_SIZE=1B MODEL=llama3 python3 examples/mlperf/model_train.py
|
||||
run: NULL=1 NULL_ALLOW_COPYOUT=1 SAMPLES=300 BS=8 SEQLEN=512 GRADIENT_ACC_STEPS=1 FAKEDATA=1 DEFAULT_FLOAT=bfloat16 OPTIM_DTYPE=bfloat16 LLAMA3_SIZE=1B MODEL=llama3 python3 examples/mlperf/model_train.py
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
@@ -474,7 +480,7 @@ jobs:
|
||||
runs-on: ubuntu-24.04
|
||||
timeout-minutes: 15
|
||||
env:
|
||||
IGNORE_OOB: 1
|
||||
CHECK_OOB: 0
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v4
|
||||
@@ -522,7 +528,7 @@ jobs:
|
||||
with:
|
||||
key: metal
|
||||
deps: testing
|
||||
python-version: '3.11'
|
||||
python-version: '3.12'
|
||||
- name: Test models (Metal)
|
||||
run: METAL=1 python -m pytest -n=auto test/models --durations=20
|
||||
- name: Test LLaMA compile speed
|
||||
@@ -541,15 +547,15 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: devectorize-minimal
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
pydeps: "pillow"
|
||||
llvm: "true"
|
||||
- name: Test LLVM=1 DEVECTORIZE=0
|
||||
run: CPU=1 CPU_LLVM=1 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/test_ops.py
|
||||
run: CPU=1 CPU_LLVM=1 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/backend/test_ops.py
|
||||
- name: Test LLVM=1 DEVECTORIZE=0 for model
|
||||
run: CPU=1 CPU_LLVM=1 DEVECTORIZE=0 python3 test/models/test_efficientnet.py
|
||||
- name: Test CPU=1 DEVECTORIZE=0
|
||||
run: CPU=1 CPU_LLVM=0 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/test_ops.py
|
||||
run: CPU=1 CPU_LLVM=0 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/backend/test_ops.py
|
||||
|
||||
testdsp:
|
||||
name: Linux (DSP)
|
||||
@@ -562,8 +568,8 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: dsp-minimal
|
||||
deps: testing_minimal
|
||||
pydeps: "onnx==1.18.0 onnxruntime pillow"
|
||||
deps: testing_unit
|
||||
pydeps: "onnx==1.18.0 onnxruntime ml_dtypes"
|
||||
llvm: "true"
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
@@ -575,15 +581,15 @@ jobs:
|
||||
load: true
|
||||
tags: qemu-hexagon:latest
|
||||
cache-from: type=gha
|
||||
cache-to: type=gha,mode=min
|
||||
cache-to: ${{ github.event_name != 'pull_request' && 'type=gha,mode=min' || '' }}
|
||||
- name: Set MOCKDSP env
|
||||
run: printf "MOCKDSP=1" >> $GITHUB_ENV
|
||||
- name: Run test_tiny on DSP
|
||||
run: DEBUG=2 DSP=1 python test/test_tiny.py
|
||||
- name: Test transcendentals
|
||||
run: CC=clang-20 DEBUG=2 DSP=1 python test/test_transcendental.py TestTranscendentalVectorized
|
||||
run: CC=clang-20 DEBUG=2 DSP=1 python test/backend/test_transcendental.py TestTranscendentalVectorized
|
||||
- name: Test quantize onnx
|
||||
run: DEBUG=2 DSP=1 python3 test/test_quantize_onnx.py
|
||||
run: DEBUG=2 DSP=1 python3 test/backend/test_quantize_onnx.py
|
||||
|
||||
testwebgpu:
|
||||
name: Linux (WebGPU)
|
||||
@@ -596,16 +602,16 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: webgpu-minimal
|
||||
deps: testing_minimal
|
||||
python-version: '3.11'
|
||||
deps: testing_unit
|
||||
python-version: '3.12'
|
||||
webgpu: 'true'
|
||||
- name: Check Device.DEFAULT (WEBGPU) and print some source
|
||||
run: |
|
||||
WEBGPU=1 python -c "from tinygrad import Device; assert Device.DEFAULT == 'WEBGPU', Device.DEFAULT"
|
||||
WEBGPU=1 DEBUG=4 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
|
||||
WEBGPU=1 DEBUG=4 FORWARD_ONLY=1 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Run selected webgpu tests
|
||||
run: |
|
||||
WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Vulkan" python3 -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --durations=20
|
||||
WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Vulkan" python3 -m pytest -n=auto test/backend --durations=20
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
@@ -630,34 +636,41 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: ${{ matrix.backend }}-minimal
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
amd: 'true'
|
||||
llvm: ${{ matrix.backend == 'amdllvm' && 'true' }}
|
||||
- name: Check Device.DEFAULT and print some source
|
||||
run: |
|
||||
python3 -c "from tinygrad import Device; assert Device.DEFAULT in ['AMD'], Device.DEFAULT"
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Run LLVM test
|
||||
if: matrix.backend=='amdllvm'
|
||||
run: python test/device/test_amd_llvm.py
|
||||
- name: Run pytest (amd)
|
||||
run: python -m pytest -n=auto test/test_ops.py test/test_dtype.py test/test_dtype_alu.py test/test_linearizer.py test/test_randomness.py test/test_jit.py test/test_graph.py test/test_multitensor.py test/device/test_hcq.py test/testextra/test_cfg_viz.py --durations=20
|
||||
run: python -m pytest -n=auto test/backend/test_ops.py test/backend/test_dtype.py test/backend/test_dtype_alu.py test/backend/test_linearizer.py test/backend/test_randomness.py test/backend/test_jit.py test/backend/test_graph.py test/backend/test_multitensor.py test/device/test_hcq.py test/testextra/test_cfg_viz.py --durations=20
|
||||
- name: Run pytest (amd)
|
||||
run: python -m pytest test/external/external_test_am.py --durations=20
|
||||
- name: Run TRANSCENDENTAL math
|
||||
run: TRANSCENDENTAL=2 python -m pytest -n=auto test/test_ops.py::TestOps::test_sin test/test_ops.py::TestOps::test_cos test/test_ops.py::TestOps::test_tan test/test_ops.py::TestOps::test_exp test/test_ops.py::TestOps::test_log --durations=20
|
||||
run: TRANSCENDENTAL=2 python -m pytest -n=auto test/backend/test_ops.py::TestOps::test_sin test/backend/test_ops.py::TestOps::test_cos test/backend/test_ops.py::TestOps::test_tan test/backend/test_ops.py::TestOps::test_exp test/backend/test_ops.py::TestOps::test_log --durations=20
|
||||
- name: Run TestOps.test_add with SQTT
|
||||
run: |
|
||||
VIZ=1 PMC=1 DEBUG=5 python3 test/test_ops.py TestOps.test_add
|
||||
VIZ=1 SQTT=1 DEBUG=5 python3 test/test_ops.py TestOps.test_add
|
||||
VIZ=-2 DEBUG=5 python3 test/backend/test_ops.py TestOps.test_add
|
||||
extra/sqtt/rgptool.py create "/tmp/profile.pkl.$USER" -o /tmp/gpu0.rgp
|
||||
- name: Run AMD emulated mmapeak on NULL backend
|
||||
env:
|
||||
AMD: 0
|
||||
run: PYTHONPATH=. NULL=1 EMULATE=AMD python extra/mmapeak/mmapeak.py
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
testamdasm:
|
||||
name: AMD ASM IDE
|
||||
runs-on: ubuntu-24.04
|
||||
timeout-minutes: 10
|
||||
timeout-minutes: 20
|
||||
env:
|
||||
AMD: 1
|
||||
PYTHON_REMU: 1
|
||||
MOCKGPU: 1
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v4
|
||||
@@ -665,13 +678,13 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: rdna3-emu
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
amd: 'true'
|
||||
python-version: '3.13'
|
||||
python-version: '3.14'
|
||||
- name: Verify AMD autogen is up to date
|
||||
run: |
|
||||
python -m extra.assembly.amd.amdxml
|
||||
git diff --exit-code extra/assembly/amd/autogen/
|
||||
python -m tinygrad.renderer.amd.generate
|
||||
git diff --exit-code tinygrad/runtime/autogen/amd/
|
||||
- name: Install LLVM 21
|
||||
run: |
|
||||
wget -qO- https://apt.llvm.org/llvm-snapshot.gpg.key | sudo tee /etc/apt/trusted.gpg.d/apt.llvm.org.asc
|
||||
@@ -679,20 +692,24 @@ jobs:
|
||||
sudo apt-get update
|
||||
sudo apt-get install llvm-21 llvm-21-tools cloc
|
||||
- name: RDNA3 Line Count
|
||||
run: cloc --by-file extra/assembly/amd/*.py
|
||||
run: cloc --by-file tinygrad/renderer/amd/*.py
|
||||
- name: Install rocprof-trace-decoder
|
||||
run: sudo PYTHONPATH="." ./extra/sqtt/install_sqtt_decoder.py
|
||||
- name: Run RDNA3 emulator tests
|
||||
run: python -m pytest -n=auto extra/assembly/amd/ --durations 20
|
||||
run: AMD_LLVM=0 python -m pytest -n=auto test/amd/ --durations 20
|
||||
- name: Run RDNA3 emulator tests (AMD_LLVM=1)
|
||||
run: AMD_LLVM=1 python -m pytest -n=auto extra/assembly/amd/ --durations 20
|
||||
run: AMD_LLVM=1 python -m pytest -n=auto test/amd/ --durations 20
|
||||
- name: Run RDNA3 dtype tests
|
||||
run: AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=auto test/test_dtype_alu.py test/test_dtype.py
|
||||
run: AMD_LLVM=0 pytest -n=auto test/backend/test_dtype_alu.py test/backend/test_dtype.py --durations 20
|
||||
- name: Run RDNA3 dtype tests (AMD_LLVM=1)
|
||||
run: AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=1 pytest -n=auto test/test_dtype_alu.py test/test_dtype.py
|
||||
run: AMD_LLVM=1 pytest -n=auto test/backend/test_dtype_alu.py test/backend/test_dtype.py --durations 20
|
||||
# TODO: run all once emulator is faster
|
||||
- name: Run RDNA3 ops tests
|
||||
run: SKIP_SLOW_TEST=1 AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=auto test/test_ops.py -k "test_sparse_categorical_crossentropy or test_tril"
|
||||
run: SKIP_SLOW_TEST=1 AMD_LLVM=0 pytest -n=auto test/backend/test_ops.py -k "test_sparse_categorical_crossentropy or test_tril or test_nonzero or test_softmax_argmax" --durations 20
|
||||
- name: Run RDNA4 emulator tests
|
||||
run: MOCKGPU_ARCH=rdna4 python -m pytest test/test_tiny.py -v --durations 20
|
||||
- name: Run CDNA4 emulator tests
|
||||
run: AMD_LLVM=1 MOCKGPU_ARCH=cdna4 python -m pytest test/test_tiny.py -v --durations 20
|
||||
|
||||
testnvidia:
|
||||
strategy:
|
||||
@@ -713,7 +730,7 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: ${{ matrix.backend }}-minimal
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
cuda: 'true'
|
||||
ocelot: 'true'
|
||||
- name: Set env
|
||||
@@ -721,10 +738,12 @@ jobs:
|
||||
- name: Check Device.DEFAULT and print some source
|
||||
run: |
|
||||
python3 -c "from tinygrad import Device; assert Device.DEFAULT in ['CUDA','NV'], Device.DEFAULT"
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Run pytest (cuda)
|
||||
# skip multitensor because it's slow
|
||||
run: python -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --ignore test/test_gc.py --ignore test/test_multitensor.py --durations=20
|
||||
run: python -m pytest -n=auto test/backend --ignore test/backend/test_multitensor.py --durations=20
|
||||
- name: Run TestOps.test_add with PMA
|
||||
run: VIZ=-1 PMA=1 DEBUG=5 python3 test/backend/test_ops.py TestOps.test_add
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
@@ -744,7 +763,7 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: ${{ matrix.backend }}-minimal
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
opencl: ${{ matrix.backend == 'opencl' && 'true' }}
|
||||
llvm: ${{ matrix.backend == 'llvm' || matrix.backend == 'lvp' }}
|
||||
mesa: ${{ matrix.backend == 'lvp' && 'true' }}
|
||||
@@ -753,11 +772,11 @@ jobs:
|
||||
- name: Check Device.DEFAULT and print some source
|
||||
run: |
|
||||
python3 -c "from tinygrad import Device; assert Device.DEFAULT in ['CPU','CL'], Device.DEFAULT"
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
|
||||
DEBUG=5 FORWARD_ONLY=1 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Run pytest (${{ matrix.backend }})
|
||||
run: python -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --durations=20
|
||||
run: python -m pytest -n=auto test/backend --durations=20
|
||||
- name: Run TRANSCENDENTAL math
|
||||
run: TRANSCENDENTAL=2 python -m pytest -n=auto test/test_ops.py::TestOps::test_sin test/test_ops.py::TestOps::test_cos test/test_ops.py::TestOps::test_tan test/test_ops.py::TestOps::test_exp test/test_ops.py::TestOps::test_log --durations=20
|
||||
run: TRANSCENDENTAL=2 python -m pytest -n=auto test/backend/test_ops.py::TestOps::test_sin test/backend/test_ops.py::TestOps::test_cos test/backend/test_ops.py::TestOps::test_tan test/backend/test_ops.py::TestOps::test_exp test/backend/test_ops.py::TestOps::test_log --durations=20
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
|
||||
@@ -775,27 +794,27 @@ jobs:
|
||||
with:
|
||||
key: metal
|
||||
deps: testing
|
||||
python-version: '3.11'
|
||||
python-version: '3.12'
|
||||
amd: 'true'
|
||||
cuda: 'true'
|
||||
ocelot: 'true'
|
||||
llvm: 'true'
|
||||
- name: Run unit tests
|
||||
env:
|
||||
LIBCLANG_PATH: '/opt/homebrew/opt/llvm@20/lib/libclang.dylib'
|
||||
run: METAL=1 python -m pytest -n=auto test/unit/ --durations=20
|
||||
- name: Run NULL backend tests
|
||||
run: NULL=1 python -m pytest -n=auto test/null/ --durations=20
|
||||
- name: Run ONNX
|
||||
run: METAL=1 python -m pytest -n=auto test/external/external_test_onnx_backend.py --durations=20
|
||||
- name: Test tensor core ops (fake)
|
||||
run: METAL=1 DEBUG=3 TC=2 python test/test_ops.py TestOps.test_gemm
|
||||
run: METAL=1 DEBUG=3 TC=2 python test/backend/test_ops.py TestOps.test_gemm
|
||||
- name: Test tensor core ops (real)
|
||||
run: METAL=1 DEBUG=3 python test/test_ops.py TestOps.test_big_gemm
|
||||
run: METAL=1 DEBUG=3 python test/backend/test_ops.py TestOps.test_big_gemm
|
||||
- name: Test Beam Search
|
||||
run: METAL=1 IGNORE_BEAM_CACHE=1 python3 -m pytest extra/optimization/test_beam_search.py
|
||||
#- name: Fuzz Test linearizer
|
||||
# run: METAL=1 DEPTH=4 FUZZ_N=50 FUZZ_MAX_SIZE=1000000 python test/external/fuzz_linearizer.py
|
||||
- name: Run TRANSCENDENTAL math
|
||||
run: METAL=1 TRANSCENDENTAL=2 python -m pytest -n=auto test/test_ops.py::TestOps::test_sin test/test_ops.py::TestOps::test_cos test/test_ops.py::TestOps::test_tan test/test_ops.py::TestOps::test_exp test/test_ops.py::TestOps::test_log --durations=20
|
||||
run: METAL=1 TRANSCENDENTAL=2 python -m pytest -n=auto test/backend/test_ops.py::TestOps::test_sin test/backend/test_ops.py::TestOps::test_cos test/backend/test_ops.py::TestOps::test_tan test/backend/test_ops.py::TestOps::test_exp test/backend/test_ops.py::TestOps::test_log --durations=20
|
||||
- name: Run pytest (amd)
|
||||
env:
|
||||
MOCKGPU: 1
|
||||
@@ -836,14 +855,14 @@ jobs:
|
||||
key: osx-webgpu
|
||||
deps: testing
|
||||
webgpu: 'true'
|
||||
- name: Test infinity math in WGSL
|
||||
run: WEBGPU=1 python -m pytest -n=auto test/test_renderer_failures.py::TestWGSLFailures::test_multiply_infinity --durations=20
|
||||
- name: Build WEBGPU Efficientnet
|
||||
run: WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Metal" python3 -m examples.compile_efficientnet
|
||||
- name: Clean npm cache
|
||||
run: npm cache clean --force
|
||||
- name: Install Puppeteer
|
||||
run: npm install puppeteer
|
||||
- name: Run selected webgpu tests
|
||||
run: WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Metal" python3 -m pytest -n=auto test/backend --durations=20
|
||||
#- name: Clean npm cache
|
||||
# run: npm cache clean --force
|
||||
#- name: Install Puppeteer
|
||||
# run: npm install puppeteer
|
||||
# this is also flaky
|
||||
#- name: Run WEBGPU Efficientnet
|
||||
# run: node test/web/test_webgpu.js
|
||||
@@ -875,8 +894,7 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: macos-${{ matrix.backend }}-minimal
|
||||
deps: testing_minimal
|
||||
pydeps: "capstone"
|
||||
deps: testing_unit
|
||||
llvm: ${{ matrix.backend == 'llvm' || matrix.backend == 'lvp' }}
|
||||
mesa: ${{ matrix.backend == 'lvp' && 'true' }}
|
||||
- name: Set env
|
||||
@@ -886,7 +904,7 @@ jobs:
|
||||
python -c "from tinygrad import Device; assert Device.DEFAULT == {'LLVM':'CPU','LVP':'CPU'}.get(x:='${{ matrix.backend }}'.upper(), x), Device.DEFAULT"
|
||||
DEBUG=4 python3 test/test_tiny.py TestTiny.test_plus
|
||||
- name: Run pytest (${{ matrix.backend }})
|
||||
run: python3 -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --durations=20
|
||||
run: python3 -m pytest -n=auto test/backend --durations=20
|
||||
- name: Run process replay tests
|
||||
uses: ./.github/actions/process-replay
|
||||
- name: Run macOS-specific unit test
|
||||
@@ -919,12 +937,16 @@ jobs:
|
||||
- name: Run unit tests
|
||||
if: matrix.backend=='llvm'
|
||||
# test_newton_schulz hits RecursionError
|
||||
run: python -m pytest -n=auto test/unit/ --ignore=test/unit/test_disk_tensor.py --ignore=test/unit/test_elf.py --ignore=test/unit/test_tar.py --ignore=test/unit/test_linalg.py --durations=20
|
||||
run: python -m pytest -n=auto test/unit/ --ignore=test/unit/test_disk_tensor.py --ignore=test/unit/test_tar.py --ignore=test/unit/test_linalg.py --durations=20
|
||||
- name: Run NULL backend tests
|
||||
if: matrix.backend=='llvm'
|
||||
shell: bash
|
||||
run: CPU=0 CPU_LLVM=0 NULL=1 python -m pytest -n=auto test/null/ --ignore=test/null/test_elf.py --durations=20
|
||||
- name: Run pytest (${{ matrix.backend }})
|
||||
shell: bash
|
||||
run: |
|
||||
python -c "from tinygrad import Device; assert Device.DEFAULT == {'LLVM':'CPU'}.get(x:='${{ matrix.backend }}'.upper(), x), Device.DEFAULT"
|
||||
python -m pytest -n=auto test/test_tiny.py test/test_ops.py --durations=20
|
||||
python -m pytest -n=auto test/test_tiny.py test/backend/test_ops.py --durations=20
|
||||
|
||||
# ****** Compile-only Tests ******
|
||||
|
||||
@@ -943,15 +965,15 @@ jobs:
|
||||
uses: ./.github/actions/setup-tinygrad
|
||||
with:
|
||||
key: compile-${{ matrix.backend }}
|
||||
deps: testing_minimal
|
||||
deps: testing_unit
|
||||
mesa: ${{ (matrix.backend == 'ir3' || matrix.backend == 'nak') && 'true' }}
|
||||
python-version: '3.14'
|
||||
python-version: '3.12'
|
||||
- name: Set env
|
||||
shell: bash
|
||||
run: printf "NULL=1\n${{ matrix.backend == 'ir3' && 'NULL_IR3=1' || matrix.backend == 'nak' && 'NULL_NAK=1' }}" >> $GITHUB_ENV
|
||||
run: printf "NULL=1\nNULL_ALLOW_COPYOUT=1\n${{ matrix.backend == 'ir3' && 'NULL_IR3=1' || matrix.backend == 'nak' && 'NULL_NAK=1' }}" >> $GITHUB_ENV
|
||||
- name: Run test_ops
|
||||
shell: bash
|
||||
run: |
|
||||
python -c "from tinygrad import Device; assert Device.DEFAULT == 'NULL'"
|
||||
DEBUG=4 python3 test/test_ops.py TestOps.test_add
|
||||
python -m pytest -n=auto test/test_ops.py --durations=20
|
||||
DEBUG=4 python3 test/backend/test_ops.py TestOps.test_add
|
||||
python -m pytest -n=auto test/backend/test_ops.py --durations=20
|
||||
|
||||
+2
-1
@@ -58,10 +58,11 @@ weights
|
||||
*.lprof
|
||||
comgr_*
|
||||
*.pkl
|
||||
!extra/sqtt/examples/**/*.pkl
|
||||
site/
|
||||
profile_stats
|
||||
*.log
|
||||
target
|
||||
.mypy_cache
|
||||
mutants
|
||||
.mutmut-cache
|
||||
.mutmut-cache
|
||||
|
||||
@@ -28,7 +28,7 @@ repos:
|
||||
pass_filenames: false
|
||||
- id: tests
|
||||
name: comprehensive test suite
|
||||
entry: env OMP_NUM_THREADS=1 SKIP_SLOW_TEST=1 PYTHONPATH="." python3 -m pytest -n=6 test/test_ops.py test/test_schedule.py test/test_assign.py test/test_tensor.py test/test_jit.py test/unit/test_schedule_cache.py test/unit/test_pattern_matcher.py test/unit/test_uop_symbolic.py test/unit/test_helpers.py
|
||||
entry: env OMP_NUM_THREADS=1 SKIP_SLOW_TEST=1 PYTHONPATH="." python3 -m pytest -n=6 test/backend/test_ops.py test/backend/test_schedule.py test/unit/test_assign.py test/backend/test_tensor.py test/backend/test_jit.py test/unit/test_schedule_cache.py test/null/test_pattern_matcher.py test/null/test_uop_symbolic.py test/unit/test_helpers.py
|
||||
language: system
|
||||
always_run: true
|
||||
pass_filenames: false
|
||||
|
||||
@@ -1,17 +0,0 @@
|
||||
# tinygrad agents
|
||||
|
||||
Hello agent. You are one of the most talented programmers of your generation.
|
||||
|
||||
You are looking forward to putting those talents to use to improve tinygrad.
|
||||
|
||||
## philosophy
|
||||
|
||||
tinygrad is a **tensor** library focused on beauty and minimalism, while still matching the functionality of PyTorch and JAX.
|
||||
|
||||
Every line must earn its keep. Prefer readability over cleverness. We believe that if carefully designed, 10 lines can have the impact of 1000.
|
||||
|
||||
Never mix functionality changes with whitespace changes. All functionality changes must be tested.
|
||||
|
||||
## style
|
||||
|
||||
Use **2-space indentation**, and keep lines to a maximum of **150 characters**. Match the existing style.
|
||||
@@ -1,227 +0,0 @@
|
||||
# Claude Code Guide for tinygrad
|
||||
|
||||
## Architecture Overview
|
||||
|
||||
tinygrad compiles tensor operations into optimized kernels. The pipeline:
|
||||
|
||||
1. **Tensor** (`tensor.py`) - User-facing API, creates UOp graph
|
||||
2. **UOp** (`uop/ops.py`) - Unified IR for all operations (both tensor and kernel level)
|
||||
3. **Schedule** (`engine/schedule.py`, `schedule/`) - Converts tensor UOps to kernel UOps
|
||||
4. **Codegen** (`codegen/`) - Converts kernel UOps to device code
|
||||
5. **Runtime** (`runtime/`) - Device-specific execution
|
||||
|
||||
## Key Concepts
|
||||
|
||||
### UOp (Universal Operation)
|
||||
Everything is a UOp - tensors, operations, buffers, kernels. Key properties:
|
||||
- `op`: The operation type (Ops enum)
|
||||
- `dtype`: Data type
|
||||
- `src`: Tuple of source UOps
|
||||
- `arg`: Operation-specific argument
|
||||
- `tag`: Optional tag for graph transformations
|
||||
|
||||
UOps are **immutable and cached** - creating the same UOp twice returns the same object (ucache).
|
||||
|
||||
### PatternMatcher
|
||||
Used extensively for graph transformations:
|
||||
```python
|
||||
pm = PatternMatcher([
|
||||
(UPat(Ops.ADD, src=(UPat.cvar("x"), UPat.cvar("x"))), lambda x: x * 2),
|
||||
])
|
||||
result = graph_rewrite(uop, pm)
|
||||
```
|
||||
|
||||
### Schedule Cache
|
||||
Schedules are cached by graph structure. BIND nodes (variables with bound values) are unbound before cache key computation so different values hit the same cache.
|
||||
|
||||
## Testing
|
||||
|
||||
```bash
|
||||
# Run specific test
|
||||
python -m pytest test/unit/test_schedule_cache.py -xvs
|
||||
|
||||
# Run with timeout
|
||||
python -m pytest test/test_symbolic_ops.py -x --timeout=60
|
||||
|
||||
# Debug with print
|
||||
DEBUG=2 python -m pytest test/test_schedule.py::test_name -xvs
|
||||
|
||||
# Visualize UOp graphs
|
||||
VIZ=1 python -c "from tinygrad import Tensor; Tensor.ones(10).sum().realize()"
|
||||
```
|
||||
|
||||
## Common Environment Variables
|
||||
|
||||
- `DEBUG=1-7` - Increasing verbosity (7 shows assembly output)
|
||||
- `VIZ=1` - Enable graph visualization
|
||||
- `SPEC=1` - Enable UOp spec verification
|
||||
- `NOOPT=1` - Disable optimizations
|
||||
- `DEVICE=CPU/CUDA/AMD/METAL` - Set default device
|
||||
|
||||
## Debugging Tips
|
||||
|
||||
1. **Print UOp graphs**: `print(tensor.uop)` or `print(tensor.uop.sink())`
|
||||
2. **Check schedule**: `tensor.schedule()` returns list of ExecItems
|
||||
3. **Trace graph rewrites**: Use `VIZ=1` or add print in PatternMatcher callbacks
|
||||
4. **Find UOps by type**: `[u for u in uop.toposort() if u.op is Ops.SOMETHING]`
|
||||
|
||||
## Workflow Rules
|
||||
|
||||
- **NEVER commit without explicit user approval** - always show the diff and wait for approval
|
||||
- **NEVER amend commits** - always create a new commit instead
|
||||
- Run `pre-commit run --all-files` before committing to catch linting/type errors
|
||||
- Run tests before proposing commits
|
||||
- Test with `SPEC=2` when modifying UOp-related code
|
||||
|
||||
## Auto-generated Files (DO NOT EDIT)
|
||||
|
||||
The following files are auto-generated and should never be edited manually:
|
||||
- `extra/assembly/amd/autogen/{arch}/__init__.py` - Generated by `python -m extra.assembly.amd.dsl --arch {arch}`
|
||||
- `extra/assembly/amd/autogen/{arch}/gen_pcode.py` - Generated by `python -m extra.assembly.amd.pcode --arch {arch}`
|
||||
|
||||
Where `{arch}` is one of: `rdna3`, `rdna4`, `cdna`
|
||||
|
||||
To add missing instruction implementations, add them to `extra/assembly/amd/emu.py` instead.
|
||||
|
||||
## Style Notes
|
||||
|
||||
- 2-space indentation, 150 char line limit
|
||||
- PatternMatchers should be defined at module level (slow to construct)
|
||||
- Prefer `graph_rewrite` over manual graph traversal
|
||||
- UOp methods like `.replace()` preserve tags unless explicitly changed
|
||||
- Use `.rtag(value)` to add tags to UOps
|
||||
|
||||
## Lessons Learned
|
||||
|
||||
### UOp ucache Behavior
|
||||
UOps are cached by their contents - creating a UOp with identical (op, dtype, src, arg) returns the **same object**. This means:
|
||||
- `uop.replace(tag=None)` on a tagged UOp returns the original untagged UOp if it exists in cache
|
||||
- Two UOps with same structure are identical (`is` comparison works)
|
||||
|
||||
### Spec Validation
|
||||
When adding new UOp patterns, update `tinygrad/uop/spec.py`. Test with:
|
||||
```bash
|
||||
SPEC=2 python3 test/unit/test_something.py
|
||||
```
|
||||
Spec issues appear as `RuntimeError: SPEC ISSUE None: UOp(...)`.
|
||||
|
||||
### Schedule Cache Key Normalization
|
||||
The schedule cache strips values from BIND nodes so different bound values (e.g., KV cache positions) hit the same cache entry:
|
||||
- `pm_pre_sched_cache`: BIND(DEFINE_VAR, CONST) → BIND(DEFINE_VAR) for cache key
|
||||
- `pm_post_sched_cache`: restores original BIND from context
|
||||
- When accessing `bind.src[1]`, check `len(bind.src) > 1` first (might be stripped)
|
||||
- Extract var_vals from `input_buffers` dict after graph_rewrite (avoids extra toposort)
|
||||
|
||||
### Avoiding Extra Work
|
||||
- Use ctx dict from graph_rewrite to collect info during traversal instead of separate toposort
|
||||
- Only extract var_vals when schedule is non-empty (no kernels = no vars needed)
|
||||
- PatternMatchers are slow to construct - define at module level, not in functions
|
||||
|
||||
### Readability Over Speed
|
||||
Don't add complexity for marginal performance gains. Simpler code that's slightly slower is often better:
|
||||
```python
|
||||
# BAD: "optimized" with extra complexity
|
||||
if has_afters: # skip toposort if no AFTERs
|
||||
after_map = [(u, u.buf_uop) for u in big_sink.toposort() if u.op is Ops.AFTER]
|
||||
|
||||
# GOOD: simple, always works
|
||||
after_map = [(u, u.buf_uop) for u in big_sink.toposort() if u.op is Ops.AFTER]
|
||||
```
|
||||
The conditional check adds complexity, potential bugs, and often negligible speedup. Only optimize when profiling shows a real bottleneck.
|
||||
|
||||
### Testing LLM Changes
|
||||
```bash
|
||||
# Quick smoke test
|
||||
echo "Hello" | DEBUG=1 python tinygrad/apps/llm.py --model "llama3.2:1b"
|
||||
|
||||
# Check cache hits (should see "cache hit" after warmup)
|
||||
echo "Hello world" | DEBUG=1 python tinygrad/apps/llm.py --model "llama3.2:1b" 2>&1 | grep cache
|
||||
|
||||
# Test with beam search
|
||||
echo "Hello" | BEAM=2 python tinygrad/apps/llm.py --model "llama3.2:1b"
|
||||
```
|
||||
|
||||
## Common Patterns
|
||||
|
||||
### Graph Transformation
|
||||
```python
|
||||
def my_transform(ctx, x):
|
||||
# Return new UOp or None to skip
|
||||
return x.replace(arg=new_arg)
|
||||
|
||||
pm = PatternMatcher([
|
||||
(UPat(Ops.SOMETHING, name="x"), my_transform),
|
||||
])
|
||||
result = graph_rewrite(input_uop, pm, ctx={})
|
||||
```
|
||||
|
||||
### Finding Variables
|
||||
```python
|
||||
# Get all variables in a UOp graph
|
||||
variables = uop.variables()
|
||||
|
||||
# Get bound variable values
|
||||
var, val = bind_uop.unbind()
|
||||
```
|
||||
|
||||
### Shape Handling
|
||||
```python
|
||||
# Shapes can be symbolic (contain UOps)
|
||||
shape = tensor.shape # tuple[sint, ...] where sint = int | UOp
|
||||
```
|
||||
|
||||
## Performance Optimization
|
||||
|
||||
When optimizing tinygrad internals:
|
||||
|
||||
1. **Measure wall time, not just call counts** - Reducing `graph_rewrite` calls doesn't always improve wall time. The overhead of conditional checks can exceed the cost of the operation being skipped.
|
||||
|
||||
2. **Profile each optimization individually** - Run benchmarks with and without each change to measure actual impact. Use `test/external/external_benchmark_schedule.py` for schedule/rewrite timing.
|
||||
|
||||
3. **Early exits in hot paths are effective** - Simple checks like `if self.op is Ops.CONST: return self` in `simplify()` can eliminate many unnecessary `graph_rewrite` calls.
|
||||
|
||||
4. **`graph_rewrite` is expensive** - Each call has overhead even for small graphs. Avoid calling it when the result is trivially known (e.g., simplifying a CONST returns itself).
|
||||
|
||||
5. **Beware iterator overhead** - Checks like `all(x.op is Ops.CONST for x in self.src)` can be slower than just running the operation, especially for small sequences.
|
||||
|
||||
6. **Verify cache hit rates before adding/keeping caches** - Measure actual hit rates with real workloads. A cache with 0% hit rate is pure overhead (e.g., `pm_cache` was removed because the algorithm guarantees each UOp is only passed to `pm_rewrite` once).
|
||||
|
||||
7. **Use `TRACK_MATCH_STATS=2` to profile pattern matching** - This shows match rates and time per pattern. Look for patterns with 0% match rate that still cost significant time - these are pure overhead for that workload.
|
||||
|
||||
8. **Cached properties beat manual traversal** - `backward_slice` uses `@functools.cached_property`. A DFS with early-exit sounds faster but is actually slower because it doesn't benefit from caching. The cache hit benefit often outweighs algorithmic improvements.
|
||||
|
||||
9. **Avoid creating intermediate objects in hot paths** - For example, `any(x.op in ops for x in self.backward_slice)` is faster than `any(x.op in ops for x in {self:None, **self.backward_slice})` because it avoids dict creation.
|
||||
|
||||
## Pattern Matching Analysis
|
||||
|
||||
**Use the right tool:**
|
||||
|
||||
- `TRACK_MATCH_STATS=2` - **Profiling**: identify expensive patterns
|
||||
- `VIZ=-1` - **Inspection**: see all transformations, what every match pattern does, the before/after diffs
|
||||
|
||||
```bash
|
||||
TRACK_MATCH_STATS=2 PYTHONPATH="." python3 test/external/external_benchmark_schedule.py
|
||||
```
|
||||
|
||||
Output format: `matches / attempts -- match_time / total_time ms -- location`
|
||||
|
||||
Key patterns to watch (from ResNet50 benchmark):
|
||||
- `split_load_store`: ~146ms, 31% match rate - does real work
|
||||
- `simplify_valid`: ~75ms, 0% match rate in this workload - checks AND ops for INDEX in backward slice
|
||||
- `vmin==vmax folding`: ~55ms, 0.33% match rate - checks 52K ops but rarely matches
|
||||
|
||||
Patterns with 0% match rate are workload-specific overhead. They may be useful in other workloads, so don't remove them without understanding their purpose.
|
||||
|
||||
```bash
|
||||
# Save the trace
|
||||
VIZ=-1 python test/test_tiny.py TestTiny.test_gemm
|
||||
|
||||
# Explore it
|
||||
./extra/viz/cli.py --help
|
||||
```
|
||||
|
||||
## AMD Performance Counter Profiling
|
||||
|
||||
Set VIZ to `-2` to save performance counters traces for the AMD backend.
|
||||
|
||||
Use the CLI in `./extra/sqtt/roc.py` to explore the trace.
|
||||
@@ -192,7 +192,7 @@ For more examples on how to run the full test suite please refer to the [CI work
|
||||
Some examples of running tests locally:
|
||||
```sh
|
||||
python3 -m pip install -e '.[testing]' # install extra deps for testing
|
||||
python3 test/test_ops.py # just the ops tests
|
||||
python3 test/backend/test_ops.py # just the ops tests
|
||||
python3 -m pytest test/ # whole test suite
|
||||
```
|
||||
|
||||
|
||||
@@ -0,0 +1,196 @@
|
||||
from tinygrad import Tensor, dtypes, Context, getenv, UOp, fetch
|
||||
from tinygrad.uop.ops import Ops, PatternMatcher, UPat
|
||||
from tinygrad.uop.symbolic import symbolic
|
||||
from tinygrad.codegen import Renderer
|
||||
from tinygrad.codegen.opt import Opt, OptOps
|
||||
|
||||
# ************************* implementation of the problem ************************
|
||||
|
||||
def myhash(a: Tensor) -> Tensor:
|
||||
a = (a + 0x7ED55D16) + (a << 12)
|
||||
a = (a ^ 0xC761C23C) ^ (a >> 19)
|
||||
a = (a + 0x165667B1) + (a << 5)
|
||||
a = (a + 0xD3A2646C) ^ (a << 9)
|
||||
a = (a + 0xFD7046C5) + (a << 3)
|
||||
a = (a ^ 0xB55A4F09) ^ (a >> 16)
|
||||
return a
|
||||
|
||||
def select_with_where_tree(values: Tensor, relative_idx: Tensor) -> Tensor:
|
||||
n = values.shape[0]
|
||||
if n == 1: return values[0].expand(relative_idx.shape)
|
||||
|
||||
mid = n // 2
|
||||
left = select_with_where_tree(values[:mid], relative_idx)
|
||||
right = select_with_where_tree(values[mid:], relative_idx - mid)
|
||||
|
||||
go_left = relative_idx < mid
|
||||
return go_left.where(left, right)
|
||||
|
||||
def tree_traversal(forest: Tensor, val: Tensor, height: int, rounds: int, where_tree_threshold=3) -> Tensor:
|
||||
# All walkers start at idx=0
|
||||
idx = Tensor.zeros(val.shape, device=val.device, dtype=dtypes.uint32)
|
||||
|
||||
for r in range(rounds):
|
||||
level = r % (height + 1)
|
||||
level_start = (1 << level) - 1
|
||||
level_size = 1 << level
|
||||
|
||||
if level == 0:
|
||||
# At root (level 0), all walkers are at idx=0
|
||||
# No gather needed, just broadcast the root value
|
||||
node_val = forest[0].expand(val.shape)
|
||||
idx = idx * 0 # Reset to 0
|
||||
elif level <= where_tree_threshold:
|
||||
# Small level: use where-tree
|
||||
level_values = forest[level_start : level_start + level_size]
|
||||
relative_idx = (idx - level_start)
|
||||
node_val = select_with_where_tree(level_values, relative_idx)
|
||||
else:
|
||||
# Large level: use gather
|
||||
node_val = forest.gather(0, idx)
|
||||
|
||||
val = myhash(val ^ node_val)
|
||||
idx = (idx << 1) + (1 + (val & 1))
|
||||
|
||||
# No wrap check needed! At round 10 (level becomes 0), we reset idx above.
|
||||
|
||||
return val.contiguous(arg=(Opt(OptOps.UPCAST, 0, 8),))
|
||||
|
||||
# ************************* renderer for VLIW machine *************************
|
||||
|
||||
def loop_unrolling(sink:UOp):
|
||||
rng = [x for x in sink.toposort() if x.op is Ops.RANGE]
|
||||
if len(rng) == 0: return None
|
||||
print(f"unrolling loop with size {rng[0].vmax+1}")
|
||||
unrolled_sinks = [sink.substitute({rng[0]:rng[0].const_like(i)}).src[0] for i in range(rng[0].vmax+1)]
|
||||
return UOp.sink(*unrolled_sinks, arg=sink.arg)
|
||||
|
||||
global_addrs = []
|
||||
vliw_prepare = PatternMatcher([
|
||||
# loop unrolling (should be a part of tinygrad)
|
||||
(UPat(Ops.SINK, name="sink"), loop_unrolling),
|
||||
# cast is fake
|
||||
(UPat(Ops.CAST, name="c"), lambda c: c.src[0]),
|
||||
# rewrites to hardcode the addresses in memory
|
||||
(UPat(Ops.PARAM, name="dg"), lambda dg: UOp.const(dtypes.uint, global_addrs[dg.arg])),
|
||||
# INDEX is just plus
|
||||
(UPat(Ops.INDEX, name="i"), lambda i: i.src[0]+i.src[1]),
|
||||
])+symbolic
|
||||
|
||||
class VLIWRenderer(Renderer):
|
||||
has_local = False # TODO: this should be the default / cleaned up
|
||||
# this says this backend supports MULACC + more. decompositions uses this
|
||||
code_for_op: dict = {Ops.MULACC: None, Ops.ADD: "+", Ops.MUL: "*",
|
||||
Ops.XOR: "^", Ops.AND: "&", Ops.OR: "|",
|
||||
Ops.SHL: "<<", Ops.SHR: ">>", Ops.CMPLT: "<"}
|
||||
# this matcher runs while still in graph form
|
||||
pre_matcher = vliw_prepare
|
||||
|
||||
def render(self, uops:list[UOp]):
|
||||
|
||||
# TODO: this is a minimal renderer. for low cycle count, make it good
|
||||
# to get speed, you need to add VLIW packing
|
||||
# to get under 1536 regs, you need to add a register allocator
|
||||
# we left the fun parts to you
|
||||
|
||||
print(f"rendering with {len(uops)} uops")
|
||||
reg, inst = 0, []
|
||||
r: dict[UOp, int] = {}
|
||||
for u in uops:
|
||||
assert u.dtype.count in (1,8), "dtype count must be 1 or 8"
|
||||
|
||||
# dumb register allocator
|
||||
if u.op not in {Ops.STORE, Ops.SINK, Ops.GEP}:
|
||||
r[u] = reg
|
||||
reg += u.dtype.count
|
||||
|
||||
# render UOps to instructions
|
||||
match u.op:
|
||||
case Ops.SINK:
|
||||
inst.append({"flow": [("halt",)]})
|
||||
case Ops.CONST:
|
||||
inst.append({"load": [("const", r[u], u.arg)]})
|
||||
case Ops.GEP:
|
||||
# a GEP is just an alias to a special register in the vector
|
||||
r[u] = r[u.src[0]] + u.arg[0]
|
||||
case Ops.VECTORIZE:
|
||||
if all(s == u.src[0] for s in u.src):
|
||||
# if all sources are the same, we can broadcast
|
||||
inst.append({"valu": [("vbroadcast", r[u], r[u.src[0]])]})
|
||||
else:
|
||||
# this is a copy into a contiguous chunk of registers
|
||||
inst.extend({"flow": [("add_imm", r[u]+i, r[s], 0)]} for i,s in enumerate(u.src) if r[s] != r[u]+i)
|
||||
case Ops.LOAD:
|
||||
op = "vload" if u.dtype.count > 1 else "load"
|
||||
inst.append({"load": [(op, r[u], r[u.src[0]])]})
|
||||
case Ops.STORE:
|
||||
op = "vstore" if u.src[1].dtype.count > 1 else "store"
|
||||
inst.append({"store": [(op, r[u.src[0]], r[u.src[1]])]})
|
||||
case Ops.MULACC:
|
||||
assert u.dtype.count == 8
|
||||
inst.append({"valu": [("multiply_add", r[u], r[u.src[0]], r[u.src[1]], r[u.src[2]])]})
|
||||
case Ops.WHERE:
|
||||
assert u.dtype.count == 8
|
||||
inst.append({"flow": [("vselect", r[u], r[u.src[0]], r[u.src[1]], r[u.src[2]])]})
|
||||
case _ if u.op in self.code_for_op:
|
||||
cat = "valu" if u.dtype.count > 1 else "alu"
|
||||
inst.append({cat: [(self.code_for_op[u.op], r[u], r[u.src[0]], r[u.src[1]])]})
|
||||
case _:
|
||||
raise NotImplementedError(f"unhandled op {u.op}")
|
||||
return repr(inst)
|
||||
|
||||
# ************************* test and render *************************
|
||||
|
||||
import sys, types
|
||||
PROBLEM_URL = "https://raw.githubusercontent.com/anthropics/original_performance_takehome/refs/heads/main/tests/frozen_problem.py"
|
||||
sys.modules["problem"] = problem = types.ModuleType("problem")
|
||||
exec(fetch(PROBLEM_URL).read_text(), problem.__dict__)
|
||||
|
||||
if __name__ == "__main__":
|
||||
batch_size = getenv("BS", 256)
|
||||
height = 10
|
||||
rounds = getenv("ROUNDS", 16)
|
||||
|
||||
# build problem
|
||||
tree = problem.Tree.generate(height)
|
||||
inp = problem.Input.generate(tree, batch_size, rounds)
|
||||
mem = problem.build_mem_image(tree, inp)
|
||||
global_addrs.extend([mem[6], mem[6], mem[4]]) # output, input, forest
|
||||
|
||||
# *** verify the kernel in tinygrad compared to reference ***
|
||||
|
||||
forest_t = Tensor(tree.values, dtype=dtypes.uint32)
|
||||
val_t = Tensor(inp.values, dtype=dtypes.uint32)
|
||||
|
||||
if getenv("VERIFY", 1):
|
||||
# verify on normal tinygrad device
|
||||
with Context(PCONTIG=2):
|
||||
out = tree_traversal(forest_t, val_t, height, rounds)
|
||||
val_out = out.tolist()
|
||||
problem.reference_kernel(tree, inp)
|
||||
assert val_out == inp.values
|
||||
print("verification passed")
|
||||
|
||||
# *** render to device ***
|
||||
|
||||
from tinygrad.codegen import get_program
|
||||
with Context(PCONTIG=2, DEVECTORIZE=2, SPEC=0):
|
||||
out = tree_traversal(forest_t, val_t, height, rounds)
|
||||
sink = out.schedule()[-1].ast
|
||||
prg = get_program(sink, VLIWRenderer())
|
||||
|
||||
# *** run on Machine and compare ***
|
||||
|
||||
# NOTE: the scratch size needs to be reduced to 1536 when you have a register allocator
|
||||
src = eval(prg.src)
|
||||
max_regs = max(t[1] for instr in src for v in instr.values() for t in v if len(t) > 1) + 8
|
||||
print(f"{max_regs:5d} regs used" + ("" if max_regs <= 1536 else " <-- WARNING: TOO MANY REGISTERS, MUST BE <= 1536"))
|
||||
machine = problem.Machine(mem, src, problem.DebugInfo(scratch_map={}), n_cores=1, trace=False, scratch_size=max_regs)
|
||||
machine.run()
|
||||
print(f"ran for {machine.cycle:5d} cycles" + ("" if machine.cycle <= 1363 else " <-- EVEN CLAUDE GOT 1363"))
|
||||
|
||||
# compare to reference
|
||||
ref_mem = mem.copy()
|
||||
for _ in problem.reference_kernel2(ref_mem, {}): pass
|
||||
assert machine.mem[mem[6]:mem[6]+mem[2]] == ref_mem[mem[6]:mem[6]+mem[2]]
|
||||
print("compare passed!")
|
||||
@@ -0,0 +1,79 @@
|
||||
from typing import Optional
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.dtype import DTypeLike, dtypes
|
||||
import math
|
||||
|
||||
# rewritten from numpy
|
||||
def rfftfreq(n: int, d: float = 1.0, device=None) -> Tensor:
|
||||
val = 1.0 / (n * d)
|
||||
N = n // 2 + 1
|
||||
results = Tensor.arange(N, device=device)
|
||||
return results * val
|
||||
|
||||
# just like in librosa
|
||||
def fft_frequencies(sr: float, n_fft: int) -> Tensor:
|
||||
return rfftfreq(n=n_fft, d=1.0 / sr)
|
||||
|
||||
def hz_to_mel(freq: Tensor) -> Tensor:
|
||||
# linear part
|
||||
f_min = 0.0
|
||||
f_sp = 200.0 / 3
|
||||
mels = (freq - f_min) / f_sp
|
||||
|
||||
# log-scale part
|
||||
min_log_hz = 1000.0 # beginning of log region (Hz)
|
||||
mask = freq >= min_log_hz
|
||||
return mask.where(((min_log_hz - f_min) / f_sp) + (freq / min_log_hz).log() / (math.log(6.4) / 27.0), mels)
|
||||
|
||||
def mel_to_hz(mels: Tensor) -> Tensor:
|
||||
# linear scale
|
||||
f_min = 0.0
|
||||
f_sp = 200.0 / 3
|
||||
freqs = f_min + f_sp * mels
|
||||
|
||||
# nonlinear scale
|
||||
min_log_hz = 1000.0 # beginning of log region (Hz)
|
||||
min_log_mel = (min_log_hz - f_min) / f_sp # same (Mels)
|
||||
logstep = math.log(6.4) / 27.0 # step size for log region
|
||||
|
||||
log_t = mels >= min_log_mel
|
||||
freqs = log_t.where(min_log_hz * ((logstep * (mels - min_log_mel)).exp()), freqs)
|
||||
return freqs
|
||||
|
||||
def mel_frequencies(n_mels: int = 128, *, fmin: float = 0.0, fmax: float = 11025.0) -> Tensor:
|
||||
# center freqs of mel bands - uniformly spaced between limits
|
||||
min_max_mel = hz_to_mel(Tensor([fmin, fmax]))
|
||||
|
||||
mels = Tensor.linspace(min_max_mel[0], min_max_mel[1], n_mels)
|
||||
hz = mel_to_hz(mels)
|
||||
return hz
|
||||
|
||||
def mel(
|
||||
*,
|
||||
sr: float,
|
||||
n_fft: int,
|
||||
n_mels: int = 128,
|
||||
fmin: float = 0.0,
|
||||
fmax: Optional[float] = None,
|
||||
dtype: DTypeLike = dtypes.default_float,
|
||||
) -> Tensor:
|
||||
if fmax is None:
|
||||
fmax = float(sr) / 2
|
||||
|
||||
n_mels = int(n_mels)
|
||||
|
||||
fftfreqs = fft_frequencies(sr=sr, n_fft=n_fft) # center freqs of each FFT bin
|
||||
mel_f = mel_frequencies(n_mels + 2, fmin=fmin, fmax=fmax) # center freqs of mel bands
|
||||
|
||||
fdiff = mel_f[1:] - mel_f[:-1]
|
||||
ramps = mel_f[None].T.expand(-1, fftfreqs.shape[-1]) - fftfreqs
|
||||
|
||||
lower = -ramps[:n_mels] / fdiff[:n_mels][None].T
|
||||
upper = ramps[2 : n_mels + 2] / fdiff[1 : n_mels + 1][None].T
|
||||
weights = lower.minimum(upper).maximum(0)
|
||||
|
||||
# Slaney-style mel is scaled to be approx constant energy per channel
|
||||
enorm = 2.0 / (mel_f[2 : n_mels + 2] - mel_f[:n_mels])
|
||||
weights *= enorm[:, None]
|
||||
|
||||
return weights
|
||||
@@ -72,7 +72,7 @@ def loader_process(q_in, q_out, X:Tensor, seed):
|
||||
#storage_tensor._copyin(img_tensor.numpy())
|
||||
|
||||
# faster
|
||||
X[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = img.tobytes()
|
||||
X[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = img.tobytes()
|
||||
|
||||
# ideal
|
||||
#X[idx].assign(img.tobytes()) # NOTE: this is slow!
|
||||
@@ -264,8 +264,8 @@ def load_unet3d_data(preprocessed_dataset_dir, seed, queue_in, queue_out, X:Tens
|
||||
x = random_brightness_augmentation(x)
|
||||
x = gaussian_noise(x)
|
||||
|
||||
X[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = x.tobytes()
|
||||
Y[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = y.tobytes()
|
||||
X[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = x.tobytes()
|
||||
Y[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = y.tobytes()
|
||||
|
||||
queue_out.put(idx)
|
||||
queue_out.put(None)
|
||||
@@ -379,12 +379,12 @@ def load_retinanet_data(base_dir:Path, val:bool, queue_in:Queue, queue_out:Queue
|
||||
clipped_match_idxs = np.clip(match_idxs, 0, None)
|
||||
clipped_boxes, clipped_labels = tgt["boxes"][clipped_match_idxs], tgt["labels"][clipped_match_idxs]
|
||||
|
||||
boxes[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = clipped_boxes.tobytes()
|
||||
labels[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = clipped_labels.tobytes()
|
||||
matches[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = match_idxs.tobytes()
|
||||
anchors[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = anchor.tobytes()
|
||||
boxes[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = clipped_boxes.tobytes()
|
||||
labels[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = clipped_labels.tobytes()
|
||||
matches[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = match_idxs.tobytes()
|
||||
anchors[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = anchor.tobytes()
|
||||
|
||||
imgs[idx].contiguous().realize().uop.base.realized.as_buffer(force_zero_copy=True)[:] = img.tobytes()
|
||||
imgs[idx].contiguous().realize().uop.base.realized.as_memoryview(force_zero_copy=True)[:] = img.tobytes()
|
||||
|
||||
queue_out.put(idx)
|
||||
queue_out.put(None)
|
||||
@@ -552,7 +552,7 @@ class BinIdxDataset:
|
||||
version, = struct.unpack("<Q", self.idx.read(8))
|
||||
assert version == 1, "unsupported index version"
|
||||
dtype_code, = struct.unpack("<B", self.idx.read(1))
|
||||
self.dtype = {1:dtypes.uint8, 2:dtypes.int8, 3:dtypes.int16, 4:dtypes.int32, 5:dtypes.int64, 6:dtypes.float64, 7:dtypes.double, 8:dtypes.uint16}[dtype_code]
|
||||
self.dtype = {1:np.dtype(np.uint8), 2:np.dtype(np.int8), 3:np.dtype(np.int16), 4:np.dtype(np.int32), 5:np.dtype(np.int64), 6:np.dtype(np.float64), 7:np.dtype(np.double), 8:np.dtype(np.uint16)}[dtype_code]
|
||||
self.count, = struct.unpack("<Q", self.idx.read(8))
|
||||
doc_count, = struct.unpack("<Q", self.idx.read(8))
|
||||
|
||||
@@ -569,7 +569,7 @@ class BinIdxDataset:
|
||||
self.doc_idx = self.idx_t[start:end].bitcast(dtypes.int64).numpy()
|
||||
|
||||
# bin file
|
||||
self.bin_t = Tensor(base_path.with_name(f"{base_path.name}.bin"))
|
||||
self.bin_t = Tensor(base_path.with_name(f"{base_path.name}.bin")).numpy()
|
||||
|
||||
def _index(self, idx) -> tuple[int, int]:
|
||||
return int(self.pointers[idx]), int(self.sizes[idx])
|
||||
@@ -578,7 +578,7 @@ class BinIdxDataset:
|
||||
ptr, size = self._index(idx)
|
||||
if length is None: length = size - offset
|
||||
ptr += offset * self.dtype.itemsize
|
||||
return self.bin_t[ptr:ptr+length*self.dtype.itemsize].bitcast(self.dtype).to(None)
|
||||
return self.bin_t[ptr:ptr+length*self.dtype.itemsize].view(self.dtype)
|
||||
|
||||
# https://docs.nvidia.com/megatron-core/developer-guide/latest/api-guide/datasets.html
|
||||
class GPTDataset:
|
||||
@@ -637,7 +637,7 @@ class GPTDataset:
|
||||
sample_parts.append(self.indexed_dataset.get(int(self.doc_idx[i]), offset=int(offset), length=length))
|
||||
|
||||
# concat all parts
|
||||
text = Tensor.cat(*sample_parts)
|
||||
text = np.concatenate(sample_parts, axis=0)
|
||||
|
||||
return text
|
||||
|
||||
@@ -780,7 +780,8 @@ def get_llama3_dataset(samples:int, seqlen:int, base_dir:Path, seed:int=0, val:b
|
||||
def iterate_llama3_dataset(dataset:BlendedGPTDataset, bs:int):
|
||||
for b in range(math.ceil(dataset.samples / bs)):
|
||||
batch = [dataset.get(b * bs + i) for i in range(bs)]
|
||||
yield Tensor.stack(batch, dim=0)
|
||||
stacked = np.stack(batch, axis=0)
|
||||
yield Tensor(stacked, device="NPY")
|
||||
|
||||
def batch_load_llama3(bs:int, samples:int, seqlen:int, base_dir:Path, seed:int=0, val:bool=True, small:bool=False):
|
||||
return iterate_llama3_dataset(get_llama3_dataset(samples, seqlen, base_dir, seed, val, small), bs)
|
||||
|
||||
+116
-39
@@ -3,7 +3,7 @@ from pathlib import Path
|
||||
import multiprocessing
|
||||
|
||||
from tinygrad import Device, GlobalCounters, Tensor, TinyJit, dtypes
|
||||
from tinygrad.helpers import getenv, BEAM, WINO, round_up, diskcache_clear, Profiling
|
||||
from tinygrad.helpers import getenv, BEAM, WINO, round_up, diskcache_clear, Profiling, profile_marker
|
||||
from tinygrad.nn.state import get_parameters, get_state_dict, load_state_dict, safe_load, safe_save
|
||||
from tinygrad.nn.optim import LAMB, LARS, SGD, OptimizerGroup, Adam, AdamW
|
||||
|
||||
@@ -1286,17 +1286,24 @@ def train_llama3():
|
||||
from examples.llama3 import MODEL_PARAMS
|
||||
from examples.mlperf.lr_schedulers import CosineAnnealingLRWithWarmup
|
||||
|
||||
BENCHMARK = getenv("BENCHMARK")
|
||||
|
||||
config = {}
|
||||
BASEDIR = config["BASEDIR"] = Path(getenv("BASEDIR", "/raid/datasets/c4/"))
|
||||
BS = config["BS"] = getenv("BS", 16)
|
||||
grad_acc = config["GRADIENT_ACC_STEPS"] = getenv("GRADIENT_ACC_STEPS", 1)
|
||||
assert grad_acc == 1, f"{grad_acc=} is not supported"
|
||||
GBS = config["GLOBAL_BATCH_SIZE"] = BS * grad_acc
|
||||
SEED = config["SEED"] = getenv("SEED", 5760)
|
||||
DATA_SEED = config["DATA_SEED"] = getenv("DATA_SEED", SEED)
|
||||
SEQLEN = config["SEQLEN"] = getenv("SEQLEN", 8192)
|
||||
TRAIN_ON_VAL = config["TRAIN_ON_VAL"] = getenv("TRAIN_ON_VAL", 0)
|
||||
SMALL = config["SMALL"] = getenv("SMALL", 0)
|
||||
SAMPLES = config["SAMPLES"] = getenv("SAMPLES", 5_760 if TRAIN_ON_VAL else 1_200_000 * 1152)
|
||||
EVAL_SAMPLES = config["EVAL_SAMPLES"] = getenv("EVAL_SAMPLES", 5760 if not SMALL else 1024)
|
||||
MAX_STEPS = config["MAX_STEPS"] = getenv("MAX_STEPS", math.ceil(1_200_000 * 1152 / GBS))
|
||||
WARMUP_STEPS = config["WARMUP_STEPS"] = getenv("WARMUP_STEPS", math.ceil(8000 * 1152 / GBS))
|
||||
LR = config["LR"] = getenv("LR", 8e-5 * GBS / 1152)
|
||||
END_LR = config["END_LR"] = getenv("END_LR", 8e-7)
|
||||
EVAL_FREQ = config["EVAL_FREQ"] = getenv("EVAL_FREQ", 46080)
|
||||
EVAL_BS = config["EVAL_BS"] = getenv("EVAL_BS", 16)
|
||||
EVAL_TARGET = config["EVAL_TARGET"] = getenv("EVAL_TARGET", 5.6)
|
||||
@@ -1310,10 +1317,12 @@ def train_llama3():
|
||||
opt_adamw_weight_decay = 0.1
|
||||
|
||||
opt_gradient_clip_norm = 1.0
|
||||
opt_learning_rate_warmup_steps = getenv("WARMUP_STEPS", math.ceil(8000 * 1152 / GBS))
|
||||
opt_learning_rate_decay_steps = getenv("MAX_STEPS", math.ceil(1_200_000 * 1152 / GBS)) - opt_learning_rate_warmup_steps
|
||||
opt_base_learning_rate = getenv("LR", 8e-5 * GBS / 1152) # NOTE: cannot change for benchmark
|
||||
opt_end_learning_rate = getenv("END_LR", 8e-7)
|
||||
opt_learning_rate_warmup_steps = WARMUP_STEPS
|
||||
opt_learning_rate_decay_steps = MAX_STEPS - opt_learning_rate_warmup_steps
|
||||
opt_base_learning_rate = LR
|
||||
opt_end_learning_rate = END_LR
|
||||
|
||||
Tensor.manual_seed(SEED) # seed for weight initialization
|
||||
|
||||
# ** init wandb **
|
||||
WANDB = getenv("WANDB")
|
||||
@@ -1326,6 +1335,8 @@ def train_llama3():
|
||||
# vocab_size from the mixtral tokenizer
|
||||
if not SMALL: model_params |= {"vocab_size": 32000}
|
||||
if (llama_layers:=getenv("LLAMA_LAYERS")) != 0: model_params['n_layers'] = llama_layers
|
||||
print(f"model parameters: {model_params}")
|
||||
|
||||
model = Transformer(**model_params, max_context=SEQLEN, jit=False, disable_kv_cache=True)
|
||||
params = get_parameters(model)
|
||||
# weights are all bfloat16 for now
|
||||
@@ -1361,6 +1372,12 @@ def train_llama3():
|
||||
|
||||
optim = AdamW(get_parameters(model), lr=0.0,
|
||||
b1=opt_adamw_beta_1, b2=opt_adamw_beta_2, eps=opt_adamw_epsilon, weight_decay=opt_adamw_weight_decay)
|
||||
|
||||
# init grads
|
||||
for p in optim.params:
|
||||
p.grad = p.zeros_like().contiguous().realize()
|
||||
grads = [p.grad for p in optim.params]
|
||||
|
||||
scheduler = CosineAnnealingLRWithWarmup(optim, opt_base_learning_rate, opt_end_learning_rate, opt_learning_rate_warmup_steps, opt_learning_rate_decay_steps)
|
||||
|
||||
if resume_ckpt := getenv("RESUME_CKPT"):
|
||||
@@ -1373,9 +1390,8 @@ def train_llama3():
|
||||
load_state_dict(scheduler, safe_load(fn), realize=False)
|
||||
|
||||
@TinyJit
|
||||
@Tensor.train()
|
||||
def train_step(model, tokens:Tensor):
|
||||
optim.zero_grad()
|
||||
def minibatch(tokens:Tensor):
|
||||
tokens = tokens.to(None)
|
||||
if (DP := getenv("DP", 1)) > 1:
|
||||
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(DP))
|
||||
tokens = tokens.shard(device, 0)
|
||||
@@ -1385,27 +1401,41 @@ def train_llama3():
|
||||
logits:Tensor = model(tokens[:, :-1], start_pos=0, temperature=math.nan)
|
||||
loss = logits.sparse_categorical_crossentropy(tokens[:, 1:])
|
||||
loss.backward()
|
||||
assert all(p.grad is g for p,g in zip(optim.params, grads))
|
||||
Tensor.realize(loss, *grads)
|
||||
return loss.flatten().float().to("CPU")
|
||||
|
||||
@TinyJit
|
||||
def optim_step():
|
||||
for p in optim.params:
|
||||
p.grad.assign(p.grad / grad_acc)
|
||||
|
||||
# L2 norm grad clip
|
||||
# https://github.com/NVIDIA/NeMo/blob/3368c3fc0b4a186ab33a1d68a504315100c0b2a6/nemo/collections/nlp/modules/common/megatron/clip_grads.py#L57
|
||||
# https://docs.pytorch.org/docs/stable/generated/torch.nn.utils.clip_grad_norm_.html
|
||||
if not getenv("DISABLE_GRAD_CLIP_NORM"):
|
||||
total_norm = Tensor(0.0, dtype=dtypes.float32, device=optim.params[0].device)
|
||||
for p in optim.params:
|
||||
total_norm += p.grad.float().square().sum()
|
||||
total_norm = total_norm.sqrt().contiguous()
|
||||
for p in optim.params:
|
||||
p.grad = p.grad * (opt_gradient_clip_norm / (total_norm + 1e-6)).clamp(max_=1.0)
|
||||
for g in grads:
|
||||
total_norm += g.float().square().sum()
|
||||
total_norm = total_norm.sqrt().contiguous().realize()
|
||||
for g in grads:
|
||||
g.assign((g * (opt_gradient_clip_norm / (total_norm + 1e-6)).clamp(max_=1.0)).cast(g.dtype)).realize()
|
||||
|
||||
optim.step()
|
||||
scheduler.step()
|
||||
|
||||
for g in grads:
|
||||
g.assign(g.zeros_like().contiguous()).realize()
|
||||
|
||||
lr = optim.lr
|
||||
loss.realize(lr)
|
||||
return loss, lr
|
||||
Tensor.realize(lr, *grads)
|
||||
|
||||
return lr.float().to("CPU")
|
||||
|
||||
@TinyJit
|
||||
@Tensor.train(False)
|
||||
def eval_step(model, tokens:Tensor):
|
||||
def eval_step(tokens:Tensor):
|
||||
tokens = tokens.to(None)
|
||||
if (DP := getenv("DP", 1)) > 1:
|
||||
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(DP))
|
||||
tokens = tokens.shard(device, 0)
|
||||
@@ -1414,7 +1444,7 @@ def train_llama3():
|
||||
tokens = tokens.shard(device)
|
||||
logits:Tensor = model(tokens[:, :-1], start_pos=0, temperature=math.nan)
|
||||
loss = logits.sparse_categorical_crossentropy(tokens[:, 1:])
|
||||
return loss.flatten().float()
|
||||
return loss.flatten().float().to("CPU")
|
||||
|
||||
# ** data iters **
|
||||
def fake_data(bs, samples):
|
||||
@@ -1426,45 +1456,79 @@ def train_llama3():
|
||||
return fake_data(BS, SAMPLES)
|
||||
else:
|
||||
from examples.mlperf.dataloader import batch_load_llama3
|
||||
return batch_load_llama3(BS, SAMPLES, SEQLEN, BASEDIR, seed=SEED, val=bool(TRAIN_ON_VAL), small=bool(SMALL))
|
||||
return batch_load_llama3(BS, SAMPLES, SEQLEN, BASEDIR, seed=DATA_SEED, val=bool(TRAIN_ON_VAL), small=bool(SMALL))
|
||||
|
||||
if getenv("FAKEDATA", 0):
|
||||
eval_dataset = None
|
||||
else:
|
||||
from examples.mlperf.dataloader import get_llama3_dataset
|
||||
eval_dataset = get_llama3_dataset(5760, SEQLEN, BASEDIR, val=True, small=bool(SMALL))
|
||||
eval_dataset = get_llama3_dataset(EVAL_SAMPLES, SEQLEN, BASEDIR, val=True, small=bool(SMALL))
|
||||
|
||||
def get_eval_iter():
|
||||
if eval_dataset is None:
|
||||
return fake_data(EVAL_BS, 5760)
|
||||
return fake_data(EVAL_BS, EVAL_SAMPLES)
|
||||
from examples.mlperf.dataloader import iterate_llama3_dataset
|
||||
return iterate_llama3_dataset(eval_dataset, EVAL_BS)
|
||||
|
||||
iter = get_train_iter()
|
||||
num_params = sum(p.numel() for p in params) - model_params["vocab_size"]*model_params["dim"]
|
||||
train_iter = get_train_iter()
|
||||
i, sequences_seen = resume_ckpt, 0
|
||||
for tokens in tqdm(iter, total=SAMPLES//GBS):
|
||||
step_times = []
|
||||
while i < MAX_STEPS:
|
||||
GlobalCounters.reset()
|
||||
if getenv("TRAIN", 1):
|
||||
t = time.perf_counter()
|
||||
loss, lr = train_step(model, tokens)
|
||||
profile_marker(f"train @ {i}")
|
||||
st = time.perf_counter()
|
||||
|
||||
stopped = False
|
||||
for _ in range(grad_acc):
|
||||
ist = time.perf_counter()
|
||||
try: tokens = next(train_iter)
|
||||
except StopIteration:
|
||||
stopped = True
|
||||
break
|
||||
dt = time.perf_counter()
|
||||
loss = minibatch(tokens)
|
||||
if stopped: break
|
||||
|
||||
gt = time.perf_counter()
|
||||
lr = optim_step()
|
||||
ot = time.perf_counter()
|
||||
|
||||
loss = loss.float().item()
|
||||
lr = lr.item()
|
||||
|
||||
et = time.perf_counter()
|
||||
step_time = et - st
|
||||
gbs_time = gt - st
|
||||
optim_time = ot - gt
|
||||
data_time = dt - ist
|
||||
dev_time = step_time - data_time * grad_acc
|
||||
if BENCHMARK: step_times.append(step_time)
|
||||
|
||||
i += 1
|
||||
sequences_seen += tokens.shape[0]
|
||||
sequences_seen += GBS
|
||||
|
||||
sec = time.perf_counter()-t
|
||||
mem_gb = GlobalCounters.mem_used / 1e9
|
||||
gflops = GlobalCounters.global_ops / 1e9 / sec
|
||||
gflops = GlobalCounters.global_ops / 1e9 / dev_time
|
||||
mfu = ((6 * num_params * SEQLEN * GBS) / (dev_time * max(getenv("DP", 1), getenv("MP", 1)) * 2.3e15)) * 100
|
||||
tqdm.write(
|
||||
f"{i:5} {sec:.2f} s run, {loss:.4f} loss, {lr:.12f} LR, {mem_gb:.2f} GB used, {gflops:9.2f} GFLOPS")
|
||||
|
||||
if (fname:=getenv("LOSS_FILE", "")):
|
||||
with open(fname, "a") as f:
|
||||
f.write(f"{i} {loss:.4f} {lr:.12f} {mem_gb:.2f}\n")
|
||||
f"{i:5} {step_time:.3f} s step, {gbs_time:.3f} s gbs, {optim_time:.3f} s optim, {data_time:.3f} s data, {loss:.4f} loss, " \
|
||||
f"{lr:.12f} LR, {mem_gb:.2f} GB used, {gflops:9.2f} GFLOPS, {mfu:5.2f}% MFU")
|
||||
|
||||
if WANDB:
|
||||
wandb.log({"lr": lr, "train/loss": loss, "train/step_time": sec, "train/GFLOPS": gflops, "train/sequences_seen": sequences_seen})
|
||||
wandb.log({
|
||||
"lr": lr, "train/loss": loss,
|
||||
"train/step_time": step_time,
|
||||
"train/gbs_time": gbs_time,
|
||||
"train/optim_time": optim_time,
|
||||
"train/dev_time": dev_time,
|
||||
"train/data_time": data_time,
|
||||
"train/mem": mem_gb,
|
||||
"train/GFLOPS": gflops,
|
||||
"train/MFU": mfu,
|
||||
"train/sequences_seen": sequences_seen
|
||||
})
|
||||
|
||||
if (ckpt_freq := getenv("CKPT")) and (i % ckpt_freq == 0 and (i != 1 or ckpt_freq == 1)):
|
||||
tqdm.write("saving checkpoint")
|
||||
@@ -1476,16 +1540,29 @@ def train_llama3():
|
||||
fn = f"{ckpt_dir}/llama3_{i}_optim.safe"
|
||||
safe_save(get_state_dict(scheduler), fn)
|
||||
|
||||
if sequences_seen % EVAL_FREQ == 0 and (i != 1 or EVAL_FREQ == 1):
|
||||
if i == BENCHMARK:
|
||||
median_step_time = sorted(step_times)[(BENCHMARK + 1) // 2]
|
||||
estimated_total_minutes = int(median_step_time * (SAMPLES // GBS) / 60)
|
||||
print(f"Estimated training time: {estimated_total_minutes // 60}h{estimated_total_minutes % 60}m")
|
||||
print(f"epoch global_ops: {GlobalCounters.global_ops:_}, "
|
||||
f"epoch global_mem: {GlobalCounters.global_mem:_}")
|
||||
|
||||
if (sequences_seen % EVAL_FREQ == 0 and (i != 1 or EVAL_FREQ == 1)) or (BENCHMARK and i == BENCHMARK):
|
||||
if EVAL_BS == 0: return
|
||||
tqdm.write(f"evaluating after {sequences_seen} sequences")
|
||||
profile_marker(f"eval @ {i}")
|
||||
|
||||
# run eval
|
||||
eval_losses = []
|
||||
eval_iter = get_eval_iter()
|
||||
tqdm.write(f"evaluating {5760//EVAL_BS} batches of {EVAL_BS} sequences")
|
||||
|
||||
for tokens in tqdm(eval_iter, total=5760//EVAL_BS):
|
||||
eval_losses += eval_step(model, tokens).tolist()
|
||||
for j,tokens in tqdm(enumerate(eval_iter), total=EVAL_SAMPLES//EVAL_BS):
|
||||
eval_losses += eval_step(tokens).tolist()
|
||||
|
||||
if BENCHMARK and (j+1) == min(BENCHMARK, EVAL_SAMPLES//EVAL_BS):
|
||||
return
|
||||
|
||||
log_perplexity = Tensor(eval_losses).mean().float().item()
|
||||
|
||||
tqdm.write(f"eval log perplexity: {log_perplexity:.4f}")
|
||||
@@ -1571,7 +1648,7 @@ def train_stable_diffusion():
|
||||
loss, out_lr = loss.detach().to("CPU"), optimizer.lr.to("CPU")
|
||||
Tensor.realize(loss, out_lr)
|
||||
return loss, out_lr
|
||||
|
||||
|
||||
# checkpointing takes ~9 minutes without this, and ~1 minute with this
|
||||
@TinyJit
|
||||
def ckpt_to_cpu():
|
||||
@@ -1610,7 +1687,7 @@ def train_stable_diffusion():
|
||||
if i == 3:
|
||||
for _ in range(3): ckpt_to_cpu() # do this at the beginning of run to prevent OOM surprises when checkpointing
|
||||
print("BEAM COMPLETE", flush=True) # allows wrapper script to detect BEAM search completion and retry if it failed
|
||||
|
||||
|
||||
total_train_time = time.perf_counter() - train_start_time
|
||||
if WANDB:
|
||||
wandb.log({"train/loss": loss_item, "train/lr": lr_item, "train/loop_time_prev": loop_time, "train/dl_time": dl_time, "train/step": i,
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ export PYTHONPATH="." AMD=1
|
||||
export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" GPUS=1 BS=128 EVAL_BS=128
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=4000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
export IGNORE_JIT_FIRST_BEAM=1
|
||||
|
||||
+1
-1
@@ -5,7 +5,7 @@ export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -8,7 +8,7 @@ export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
export TRAIN_STEPS=3900
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
export TRAIN_STEPS=3900
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -8,7 +8,7 @@ export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
export TRAIN_STEPS=3900
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=5000000
|
||||
|
||||
export BEAM=0 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -8,7 +8,7 @@ export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
export TRAIN_STEPS=3900
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=5000000
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ export DEFAULT_FLOAT="HALF" GPUS=8 BS=1024 EVAL_BS=1024
|
||||
export OPT_BASE_LEARNING_RATE=0.0011 OPT_LAMB_BETA_1=0.60466 OPT_LAMB_BETA_2=0.85437 DECAY=0.1
|
||||
export TRAIN_STEPS=3900
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=5000000
|
||||
|
||||
export BEAM=3 BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ export PYTHONPATH="." NV=1
|
||||
export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=72 EVAL_BS=72
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=8 BEAM_UOPS_MAX=10000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ export PYTHONPATH="." NV=1
|
||||
export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=72 EVAL_BS=72
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=8 BEAM_UOPS_MAX=10000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -7,7 +7,7 @@ export MODEL="bert"
|
||||
export SUBMISSION_PLATFORM="tinybox_green"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=72 EVAL_BS=72
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=8 BEAM_UOPS_MAX=10000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ export PYTHONPATH="." AMD=1
|
||||
export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=96 EVAL_BS=96
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=5 BEAM_UOPS_MAX=8000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ export PYTHONPATH="." AMD=1
|
||||
export MODEL="bert"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=96 EVAL_BS=96
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=5 BEAM_UOPS_MAX=8000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+1
-1
@@ -7,7 +7,7 @@ export MODEL="bert"
|
||||
export SUBMISSION_PLATFORM="tinybox_red"
|
||||
export DEFAULT_FLOAT="HALF" SUM_DTYPE="HALF" GPUS=6 BS=96 EVAL_BS=96
|
||||
|
||||
export IGNORE_OOB=1
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=500000
|
||||
|
||||
export BEAM=5 BEAM_UOPS_MAX=8000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
+37
@@ -0,0 +1,37 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
export PYTHONPATH="."
|
||||
export DEV=${DEV:-AMD}
|
||||
export EMULATE="AMD_CDNA4"
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
|
||||
|
||||
export DEBUG=${DEBUG:-2}
|
||||
export FLASH_ATTENTION=${FLASH_ATTENTION:-1}
|
||||
export ALL2ALL=${ALL2ALL:-1}
|
||||
export USE_ATOMICS=${USE_ATOMICS:-1}
|
||||
export ASM_GEMM=${ASM_GEMM:-1}
|
||||
|
||||
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
|
||||
export DP=${DP:-8} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-1}
|
||||
export GBS=$((BS * GRADIENT_ACC_STEPS))
|
||||
|
||||
export MODEL="llama3"
|
||||
export BASEDIR="/raid/datasets/c4-8b/"
|
||||
export SMALL=1
|
||||
export LLAMA3_SIZE=${LLAMA3_SIZE:-"8B"}
|
||||
export EVAL_TARGET=3.3 EVAL_FREQ=12288
|
||||
export LR="4e-4" END_LR="4e-5" WARMUP_SAMPLES=256 MAX_STEPS=1200000
|
||||
export WARMUP_STEPS=$((WARMUP_SAMPLES / GBS))
|
||||
export SAMPLES=$((MAX_STEPS * GBS))
|
||||
export SEQLEN=${SEQLEN:-8192}
|
||||
|
||||
export SEED=${SEED:-5760}
|
||||
export DATA_SEED=${DATA_SEED:-5760}
|
||||
|
||||
export JITBEAM=${JITBEAM:-3}
|
||||
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
export FAKEDATA=1 BENCHMARK=10 LLAMA_LAYERS=2
|
||||
|
||||
python3 examples/mlperf/model_train.py
|
||||
+35
@@ -0,0 +1,35 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
export PYTHONPATH="."
|
||||
export DEV=${DEV:-AMD}
|
||||
export EMULATE="AMD_CDNA4"
|
||||
export CHECK_OOB=0
|
||||
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
|
||||
|
||||
export DEBUG=${DEBUG:-0}
|
||||
export FLASH_ATTENTION=${FLASH_ATTENTION:-1}
|
||||
export ALL2ALL=${ALL2ALL:-1}
|
||||
export USE_ATOMICS=${USE_ATOMICS:-1}
|
||||
export ASM_GEMM=${ASM_GEMM:-1}
|
||||
|
||||
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
|
||||
export DP=${DP:-8} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-1}
|
||||
export GBS=$((BS * GRADIENT_ACC_STEPS))
|
||||
|
||||
export MODEL="llama3"
|
||||
export BASEDIR="/raid/datasets/c4-8b/"
|
||||
export SMALL=1
|
||||
export LLAMA3_SIZE=${LLAMA3_SIZE:-"8B"}
|
||||
export EVAL_TARGET=3.3 EVAL_FREQ=12288
|
||||
export LR="4e-4" END_LR="4e-5" WARMUP_SAMPLES=256 MAX_STEPS=1200000
|
||||
export WARMUP_STEPS=$((WARMUP_SAMPLES / GBS))
|
||||
export SAMPLES=$((MAX_STEPS * GBS))
|
||||
export SEQLEN=${SEQLEN:-8192}
|
||||
|
||||
export SEED=${SEED:-$RANDOM}
|
||||
export DATA_SEED=${DATA_SEED:-5760}
|
||||
|
||||
export JITBEAM=${JITBEAM:-3}
|
||||
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
|
||||
|
||||
python3 examples/mlperf/model_train.py
|
||||
+6
@@ -0,0 +1,6 @@
|
||||
#!/bin/bash
|
||||
export BENCHMARK=5
|
||||
export EVAL_BS=0
|
||||
export VIZ=${VIZ:--1}
|
||||
examples/mlperf/training_submission_v6.0/tinycorp/benchmarks/llama8b/implementations/tinybox_8xMI350X/dev_run.sh
|
||||
PYTHONPATH="." extra/viz/cli.py --profile --device "AMD" --top 20
|
||||
+10
@@ -0,0 +1,10 @@
|
||||
#!/bin/bash
|
||||
export BENCHMARK=5
|
||||
export EVAL_BS=0
|
||||
export FAKEDATA=1
|
||||
export NULL_ALLOW_COPYOUT=1
|
||||
export HIP_VISIBLE_DEVICES=""
|
||||
export DEV=NULL
|
||||
export JITBEAM=0
|
||||
export LLAMA_LAYERS=${LLAMA_LAYERS:-"2"}
|
||||
time examples/mlperf/training_submission_v6.0/tinycorp/benchmarks/llama8b/implementations/tinybox_8xMI350X/dev_run.sh
|
||||
@@ -6,7 +6,6 @@ import argparse, time
|
||||
from collections import namedtuple
|
||||
from typing import Dict, Any
|
||||
|
||||
from PIL import Image
|
||||
import numpy as np
|
||||
from tinygrad import Device, GlobalCounters, dtypes, Tensor, TinyJit
|
||||
from tinygrad.helpers import Timing, Context, getenv, fetch, colored, tqdm, flatten, profile_marker
|
||||
@@ -336,6 +335,7 @@ if __name__ == "__main__":
|
||||
print(x.shape)
|
||||
|
||||
profile_marker("save image")
|
||||
from PIL import Image
|
||||
im = Image.fromarray(x.numpy())
|
||||
print(f"saving {args.out}")
|
||||
im.save(args.out)
|
||||
|
||||
@@ -48,7 +48,7 @@ def prepare_browser_chunks(model):
|
||||
weight_metadata = metadata.get(name, default)
|
||||
weight_metadata["parts"][part_num] = {"file": i, "file_start_pos": cursor, "size": size}
|
||||
metadata[name] = weight_metadata
|
||||
data = bytes(state_dict[name].uop.base.realized.as_buffer())
|
||||
data = bytes(state_dict[name].uop.base.realized.as_memoryview())
|
||||
data = data if not offsets else data[offsets[0]:offsets[1]]
|
||||
writer.write(data)
|
||||
cursor += size
|
||||
|
||||
@@ -93,7 +93,7 @@ if __name__ == "__main__":
|
||||
forward: Any = None
|
||||
|
||||
sub_steps = [
|
||||
Step(name = "textModel", input = [Tensor.randn(1, 77)], forward = model.cond_stage_model.transformer.text_model),
|
||||
Step(name = "textModel", input = [Tensor.randint(1, 77, low=0, high=49408, dtype=dtypes.int32)], forward = model.cond_stage_model.transformer.text_model),
|
||||
Step(name = "diffusor", input = [Tensor.randn(1, 77, 768), Tensor.randn(1, 77, 768), Tensor.randn(1,4,64,64), Tensor.rand(1), Tensor.randn(1), Tensor.randn(1), Tensor.randn(1)], forward = model),
|
||||
Step(name = "decoder", input = [Tensor.randn(1,4,64,64)], forward = model.decode),
|
||||
Step(name = "f16tof32", input = [Tensor.randn(2097120, dtype=dtypes.uint32)], forward = u32_to_f16)
|
||||
|
||||
+2
-1
@@ -7,6 +7,7 @@ from tinygrad import Tensor, TinyJit, Variable, nn, dtypes
|
||||
from tinygrad.nn.state import torch_load, load_state_dict
|
||||
from tinygrad.helpers import getenv, fetch
|
||||
|
||||
from examples.audio_helpers import mel
|
||||
import numpy as np
|
||||
import librosa
|
||||
|
||||
@@ -159,7 +160,7 @@ def prep_audio(waveforms: List[np.ndarray], batch_size: int, truncate=False) ->
|
||||
|
||||
stft = librosa.stft(waveforms, n_fft=N_FFT, hop_length=HOP_LENGTH, window='hann', dtype=np.csingle)
|
||||
magnitudes = np.absolute(stft[..., :-1]) ** 2
|
||||
mel_spec = librosa.filters.mel(sr=RATE, n_fft=N_FFT, n_mels=N_MELS) @ magnitudes
|
||||
mel_spec = mel(sr=RATE, n_fft=N_FFT, n_mels=N_MELS).numpy() @ magnitudes
|
||||
|
||||
log_spec = np.log10(np.clip(mel_spec, 1e-10, None))
|
||||
log_spec = np.maximum(log_spec, log_spec.max((1,2), keepdims=True) - 8.0)
|
||||
|
||||
@@ -92,7 +92,7 @@ class SMICtx:
|
||||
self.prev_terminal_width = 0
|
||||
self.prev_terminal_height = 0
|
||||
|
||||
remove_parts = ["Advanced Micro Devices, Inc. [AMD/ATI]", "VGA compatible controller:"]
|
||||
remove_parts = ["Advanced Micro Devices, Inc. [AMD/ATI]", "VGA compatible controller:", "Processing accelerators:"]
|
||||
lspci = subprocess.check_output(["lspci"]).decode("utf-8").splitlines()
|
||||
self.lspci = {l.split()[0]: l.split(" ", 1)[1] for l in lspci}
|
||||
for k,v in self.lspci.items():
|
||||
@@ -153,7 +153,8 @@ class SMICtx:
|
||||
tables = {}
|
||||
for dev in self.devs:
|
||||
match dev.ip_ver[am.MP1_HWIP]:
|
||||
case (13,0,6)|(13,0,12): table_t = dev.smu.smu_mod.MetricsTableX_t
|
||||
case (13,0,6): table_t = dev.smu.smu_mod.MetricsTableV0_t
|
||||
case (13,0,12): table_t = dev.smu.smu_mod.MetricsTableV2_t
|
||||
case _: table_t = dev.smu.smu_mod.SmuMetricsExternal_t
|
||||
tables[dev] = dev.smu.read_table(table_t, dev.smu.smu_mod.SMU_TABLE_SMU_METRICS) if dev.pci_state == "D0" else None
|
||||
return tables
|
||||
@@ -279,7 +280,7 @@ class SMICtx:
|
||||
device_line = [f"{bold(dev.pcibus)} {trim(self.lspci[dev.pcibus[5:]], col_size - 20)}"] + [pad("", col_size)]
|
||||
activity_line = [f"GFX Activity {draw_bar(self.get_gfx_activity(dev, metrics) / 100, activity_line_width)}"] \
|
||||
+ [f"MEM Activity {draw_bar(self.get_mem_activity(dev, metrics) / 100, activity_line_width)}"] \
|
||||
+ [f"MEM Usage {draw_bar((mem_used / mem_total) / 100, activity_line_width, opt_text=mem_fmt)}"] \
|
||||
+ [f"MEM Usage {draw_bar(mem_used / mem_total, activity_line_width, opt_text=mem_fmt)}"] \
|
||||
|
||||
temps_data, temps_data_compact = self.get_temps(dev, metrics), self.get_temps(dev, metrics, compact=True)
|
||||
temps_table = ["=== Temps (°C) ==="] + [f"{name:<16}: {color_temp(val)}" for name, val in temps_data.items()]
|
||||
|
||||
@@ -1,12 +1,18 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
import os
|
||||
from tinygrad.helpers import Context
|
||||
from tinygrad.runtime.support.system import System, PCIDevice, PCIDevImplBase
|
||||
from tinygrad.runtime.support.hcq import FileIOInterface
|
||||
from tinygrad.runtime.support.am.amdev import AMDev
|
||||
|
||||
if __name__ == "__main__":
|
||||
gpus = System.pci_scan_bus(0x1002, [(0xffff, [0x74a1, 0x75a0])])
|
||||
pcidevs = [PCIDevice(f"reset:{gpu}", gpu, bars=[0, 2, 5]) for gpu in gpus]
|
||||
for gpu in gpus:
|
||||
drv_path = f"/sys/bus/pci/devices/{gpu}/driver"
|
||||
if FileIOInterface.exists(drv_path) and os.path.basename(os.readlink(drv_path)) == "amdgpu":
|
||||
raise RuntimeError(f"amdgpu is bound to {gpu}. Stopping...")
|
||||
pcidevs = [PCIDevice("AM", gpu, bars=[0, 2, 5]) for gpu in gpus]
|
||||
amdevs = []
|
||||
with Context(DEBUG=2):
|
||||
for pcidev in pcidevs:
|
||||
|
||||
@@ -19,8 +19,9 @@ amdev = importlib.import_module("tinygrad.runtime.support.am.amdev")
|
||||
amdev.AMDev = AMDFake
|
||||
from tinygrad.runtime.ops_amd import PCIIface
|
||||
|
||||
def parse_amdgpu_logs(log_content, register_names=None, *, only_xcc0: bool = False):
|
||||
def parse_amdgpu_logs(log_content, register_names=None, register_objects=None, *, only_xcc0: bool = False):
|
||||
register_map = register_names or {}
|
||||
register_objs = register_objects or {}
|
||||
|
||||
def replace_register(match):
|
||||
reg = match.group(1)
|
||||
@@ -37,6 +38,28 @@ def parse_amdgpu_logs(log_content, register_names=None, *, only_xcc0: bool = Fal
|
||||
# remove timing prefix
|
||||
processed_log = re.sub(r'^\[\s*\d+(?:\.\d+)?\]\s*', '', processed_log, flags=re.MULTILINE)
|
||||
|
||||
# decode register values into field dicts
|
||||
def decode_value(match):
|
||||
reg_name = match.group(1)
|
||||
xcc_part = match.group(2) # "xcc=0 " or ""
|
||||
val_str = match.group(3)
|
||||
val = int(val_str, 16)
|
||||
|
||||
reg_obj = register_objs.get(reg_name)
|
||||
if reg_obj is not None and reg_obj.fields:
|
||||
fields = reg_obj.decode(val)
|
||||
# show raw for unaccounted bits
|
||||
accounted = 0
|
||||
for name, (start, end) in reg_obj.fields.items():
|
||||
accounted |= (((1 << (end - start + 1)) - 1) << start)
|
||||
unaccounted = val & ~accounted
|
||||
parts = {k: v for k, v in fields.items() if v != 0}
|
||||
if unaccounted: parts['_raw_unaccounted'] = hex(unaccounted)
|
||||
return f"register {reg_name}, {xcc_part}with value {val_str} {parts}"
|
||||
return match.group(0)
|
||||
|
||||
processed_log = re.sub(r'register (reg\w+), ((?:xcc=\d+ )?)with value (0x[0-9a-fA-F]+)', decode_value, processed_log)
|
||||
|
||||
# keep only xcc=0 lines (but keep lines with no xcc at all)
|
||||
if only_xcc0:
|
||||
kept = []
|
||||
@@ -50,16 +73,18 @@ def main():
|
||||
only_xcc0 = bool(getenv("ONLY_XCC0", 0))
|
||||
|
||||
reg_names = {}
|
||||
reg_objs = {}
|
||||
dev = PCIIface(None, 0)
|
||||
for x, y in dev.dev_impl.__dict__.items():
|
||||
if isinstance(y, AMRegister):
|
||||
for xcc, addr in y.addr.items():
|
||||
reg_names[addr] = f"{x}, xcc={xcc}"
|
||||
reg_objs[x] = y
|
||||
|
||||
with open(sys.argv[1], 'r') as f:
|
||||
log_content = f.read()
|
||||
|
||||
processed_log = parse_amdgpu_logs(log_content, reg_names, only_xcc0=only_xcc0)
|
||||
processed_log = parse_amdgpu_logs(log_content, reg_names, reg_objs, only_xcc0=only_xcc0)
|
||||
|
||||
with open(sys.argv[2], 'w') as f:
|
||||
f.write(processed_log)
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,83 +0,0 @@
|
||||
# Instruction format detection and decoding
|
||||
from __future__ import annotations
|
||||
from extra.assembly.amd.dsl import Inst, FixedBitField
|
||||
from extra.assembly.amd.autogen.rdna3.ins import (VOP1, VOP1_SDST, VOP2, VOP3, VOP3_SDST, VOP3SD, VOP3P, VOPC, VOPD, VINTERP,
|
||||
SOP1, SOP2, SOPC, SOPK, SOPP, SMEM, DS, FLAT)
|
||||
from extra.assembly.amd.autogen.rdna4.ins import (VOP1 as R4_VOP1, VOP1_SDST as R4_VOP1_SDST, VOP2 as R4_VOP2,
|
||||
VOP3 as R4_VOP3, VOP3_SDST as R4_VOP3_SDST, VOP3SD as R4_VOP3SD, VOP3P as R4_VOP3P,
|
||||
VOPC as R4_VOPC, VOPD as R4_VOPD, VINTERP as R4_VINTERP, SOP1 as R4_SOP1, SOP2 as R4_SOP2, SOPC as R4_SOPC, SOPK as R4_SOPK, SOPP as R4_SOPP,
|
||||
SMEM as R4_SMEM, DS as R4_DS)
|
||||
from extra.assembly.amd.autogen.cdna.ins import (VOP1 as C_VOP1, VOP2 as C_VOP2, VOPC as C_VOPC, VOP3A, VOP3B, VOP3P as C_VOP3P,
|
||||
SOP1 as C_SOP1, SOP2 as C_SOP2, SOPC as C_SOPC, SOPK as C_SOPK, SOPP as C_SOPP, SMEM as C_SMEM, DS as C_DS, FLAT as C_FLAT)
|
||||
|
||||
def _matches_encoding(word: int, cls: type[Inst]) -> bool:
|
||||
"""Check if word matches the encoding pattern of an instruction class."""
|
||||
enc = next(((n, f) for n, f in cls._fields if isinstance(f, FixedBitField) and n == 'encoding'), None)
|
||||
if enc is None: return False
|
||||
bf = enc[1]
|
||||
return ((word >> bf.lo) & bf.mask) == bf.default
|
||||
|
||||
# Order matters: more specific encodings first, VOP2 last (it's a catch-all for bit31=0)
|
||||
_RDNA_FORMATS_64 = [VOPD, VOP3P, VINTERP, VOP3, DS, FLAT, SMEM]
|
||||
_RDNA_FORMATS_32 = [SOP1, SOPC, SOPP, SOPK, VOPC, VOP1, SOP2, VOP2] # SOP2/VOP2 are catch-alls
|
||||
_CDNA_FORMATS_64 = [C_VOP3P, VOP3A, C_DS, C_FLAT, C_SMEM]
|
||||
_CDNA_FORMATS_32 = [C_SOP1, C_SOPC, C_SOPP, C_SOPK, C_VOPC, C_VOP1, C_SOP2, C_VOP2]
|
||||
_CDNA_VOP3B_OPS = {281, 282, 283, 284, 285, 286, 480, 481, 488, 489} # VOP3B opcodes
|
||||
_RDNA4_FORMATS_64 = [R4_VOPD, R4_VOP3P, R4_VINTERP, R4_VOP3, R4_DS, R4_SMEM]
|
||||
_RDNA4_FORMATS_32 = [R4_SOP1, R4_SOPC, R4_SOPP, R4_SOPK, R4_VOPC, R4_VOP1, R4_SOP2, R4_VOP2]
|
||||
_RDNA4_VOP3SD_OPS = {288, 289, 290, 764, 765, 766, 767, 768, 769, 770}
|
||||
_RDNA3_VOP3SD_OPS = {288, 289, 290, 764, 765, 766, 767, 768, 769, 770}
|
||||
# Instructions with SGPR destination (READLANE, READFIRSTLANE, and VOP3-encoded VOPC)
|
||||
_VOP1_SDST_OPS = {2} # V_READFIRSTLANE_B32_E32
|
||||
_VOP3_SDST_OPS = {386, 864} # V_READFIRSTLANE_B32_E64, V_READLANE_B32 (V_WRITELANE_B32=865 writes to VGPR)
|
||||
# VOP3-encoded VOPC instructions (opcodes < 256) also have SGPR destination
|
||||
|
||||
def detect_format(data: bytes, arch: str = "rdna3") -> type[Inst]:
|
||||
"""Detect instruction format from machine code bytes."""
|
||||
assert len(data) >= 4, f"need at least 4 bytes, got {len(data)}"
|
||||
word = int.from_bytes(data[:4], 'little')
|
||||
if arch == "cdna":
|
||||
# SDWA (0xf9) and DPP (0xfa) use special src0 encodings - not supported
|
||||
if (word & 0x1ff) in (0xf9, 0xfa): raise ValueError(f"CDNA SDWA/DPP not supported word={word:#010x}")
|
||||
if (word >> 30) == 0b11:
|
||||
for cls in _CDNA_FORMATS_64:
|
||||
if _matches_encoding(word, cls):
|
||||
return VOP3B if cls is VOP3A and ((word >> 16) & 0x3ff) in _CDNA_VOP3B_OPS else cls
|
||||
raise ValueError(f"unknown CDNA 64-bit format word={word:#010x}")
|
||||
for cls in _CDNA_FORMATS_32:
|
||||
if _matches_encoding(word, cls): return cls
|
||||
raise ValueError(f"unknown CDNA 32-bit format word={word:#010x}")
|
||||
if arch == "rdna4":
|
||||
if (word >> 30) == 0b11:
|
||||
for cls in _RDNA4_FORMATS_64:
|
||||
if _matches_encoding(word, cls):
|
||||
if cls is R4_VOP3:
|
||||
opcode = (word >> 16) & 0x3ff
|
||||
if opcode in _RDNA4_VOP3SD_OPS: return R4_VOP3SD
|
||||
if opcode in _VOP3_SDST_OPS or opcode < 256: return R4_VOP3_SDST # VOP3-encoded VOPC (op < 256) writes to SGPR
|
||||
return cls
|
||||
raise ValueError(f"unknown RDNA4 64-bit format word={word:#010x}")
|
||||
for cls in _RDNA4_FORMATS_32:
|
||||
if _matches_encoding(word, cls):
|
||||
if cls is R4_VOP1 and ((word >> 9) & 0xff) in _VOP1_SDST_OPS: return R4_VOP1_SDST
|
||||
return cls
|
||||
raise ValueError(f"unknown RDNA4 32-bit format word={word:#010x}")
|
||||
# RDNA3 (default)
|
||||
if (word >> 30) == 0b11:
|
||||
for cls in _RDNA_FORMATS_64:
|
||||
if _matches_encoding(word, cls):
|
||||
if cls is VOP3:
|
||||
opcode = (word >> 16) & 0x3ff
|
||||
if opcode in _RDNA3_VOP3SD_OPS: return VOP3SD
|
||||
if opcode in _VOP3_SDST_OPS or opcode < 256: return VOP3_SDST # VOP3-encoded VOPC (op < 256) writes to SGPR
|
||||
return cls
|
||||
raise ValueError(f"unknown 64-bit format word={word:#010x}")
|
||||
for cls in _RDNA_FORMATS_32:
|
||||
if _matches_encoding(word, cls):
|
||||
if cls is VOP1 and ((word >> 9) & 0xff) in _VOP1_SDST_OPS: return VOP1_SDST
|
||||
return cls
|
||||
raise ValueError(f"unknown 32-bit format word={word:#010x}")
|
||||
|
||||
def decode_inst(data: bytes, arch: str = "rdna3") -> Inst:
|
||||
"""Decode machine code bytes into an instruction."""
|
||||
return detect_format(data, arch).from_bytes(data)
|
||||
@@ -1,671 +0,0 @@
|
||||
# RDNA3/RDNA4/CDNA disassembler
|
||||
from __future__ import annotations
|
||||
import re, struct
|
||||
from extra.assembly.amd.dsl import Inst, Reg
|
||||
|
||||
# Special register mappings for disassembly
|
||||
SPECIAL_GPRS = {106: 'vcc_lo', 107: 'vcc_hi', 124: 'null', 125: 'm0', 126: 'exec_lo', 127: 'exec_hi',
|
||||
128: '0', 240: '0.5', 241: '-0.5', 242: '1.0', 243: '-1.0', 244: '2.0', 245: '-2.0', 246: '4.0', 247: '-4.0', 248: '0x3e22f983', 253: 'scc'}
|
||||
SPECIAL_GPRS_CDNA = {106: 'vcc_lo', 107: 'vcc_hi', 124: 'null', 125: 'm0', 126: 'exec_lo', 127: 'exec_hi',
|
||||
128: '0', 240: '0.5', 241: '-0.5', 242: '1.0', 243: '-1.0', 244: '2.0', 245: '-2.0', 246: '4.0', 247: '-4.0', 248: '0x3e22f983', 253: 'scc',
|
||||
102: 'flat_scratch_lo', 103: 'flat_scratch_hi', 104: 'xnack_mask_lo', 105: 'xnack_mask_hi'}
|
||||
SPECIAL_PAIRS = {106: 'vcc', 126: 'exec'}
|
||||
SPECIAL_PAIRS_CDNA = {106: 'vcc', 126: 'exec', 102: 'flat_scratch', 104: 'xnack_mask'}
|
||||
|
||||
def decode_src(v, cdna: bool = False) -> str:
|
||||
"""Decode a source operand encoding to its string representation."""
|
||||
v = _unwrap(v)
|
||||
gprs = SPECIAL_GPRS_CDNA if cdna else SPECIAL_GPRS
|
||||
if v in gprs: return gprs[v]
|
||||
if v < 106: return f's{v}'
|
||||
if 108 <= v < 124: return f'ttmp{v - 108}'
|
||||
if 129 <= v <= 192: return str(v - 128) # positive integers 1-64
|
||||
if 193 <= v <= 208: return str(-(v - 192)) # negative integers -1 to -16
|
||||
if v >= 256: return f'v{v - 256}'
|
||||
return f's{v}'
|
||||
|
||||
def _unwrap(v) -> int:
|
||||
"""Unwrap Reg to int offset, or return int as-is."""
|
||||
return v.offset if isinstance(v, Reg) else v
|
||||
|
||||
def _vi(v) -> int:
|
||||
"""Get VGPR index from Reg or int (for v[N] fields that encode as 256+N)."""
|
||||
off = _unwrap(v)
|
||||
return off - 256 if off >= 256 else off
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# LITERAL FORMATTING
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
_FLOAT_DEC = {240: 0.5, 241: -0.5, 242: 1.0, 243: -1.0, 244: 2.0, 245: -2.0, 246: 4.0, 247: -4.0}
|
||||
|
||||
def _lit(inst, v, neg=0) -> str:
|
||||
"""Format literal/inline constant value."""
|
||||
v = _unwrap(v)
|
||||
if v == 255:
|
||||
lit = inst._literal
|
||||
if lit is None: return "0"
|
||||
s = f"0x{lit:x}"
|
||||
elif v in _FLOAT_DEC: s = str(_FLOAT_DEC[v])
|
||||
elif 128 <= v <= 192: s = str(v - 128)
|
||||
elif 193 <= v <= 208: s = str(-(v - 192))
|
||||
elif v < 128: s = decode_src(v)
|
||||
elif v >= 256: s = f"v{v - 256}"
|
||||
else: s = decode_src(v)
|
||||
return f"-{s}" if neg else s
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# INSTRUCTION METADATA - fallback functions when inst.num_srcs()/inst.operands unavailable
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _num_srcs(inst) -> int:
|
||||
"""Fallback: get number of source operands from instruction name."""
|
||||
name = getattr(inst, 'op_name', '') or ''
|
||||
n = name.upper()
|
||||
# FMAC/MAC ops are 2-source (dst is implicit accumulator), but FMA/MAD ops are 3-source
|
||||
if 'FMAC' in n or 'V_MAC_' in n: return 2
|
||||
if any(x in n for x in ('FMA', 'MAD', 'CNDMASK', 'BFE', 'BFI', 'LERP', 'MED3', 'SAD', 'DIV_FMAS', 'DIV_FIXUP', 'DIV_SCALE', 'CUBE')): return 3
|
||||
# PERMLANE_VAR ops are 2-source, but PERMLANE (non-VAR) are 3-source
|
||||
if 'PERMLANE' in n and '_VAR' not in n: return 3
|
||||
if any(x in n for x in ('_ADD3', '_LSHL_ADD', '_ADD_LSHL', '_LSHL_OR', '_AND_OR', 'OR3_B32', 'AND_OR_B32', 'ALIGNBIT', 'ALIGNBYTE', 'V_PERM_', 'XOR3', 'XAD', 'MULLIT', 'MINMAX', 'MAXMIN', 'MINIMUMMAXIMUM', 'MAXIMUMMINIMUM', 'MINIMUM3', 'MAXIMUM3', 'MIN3', 'MAX3', 'DOT2', 'CVT_PK_U8_F32', 'DOT4', 'DOT8', 'WMMA', 'SWMMAC')): return 3
|
||||
return 2
|
||||
|
||||
# SWMMAC register counts: (dst, src0, src1, src2)
|
||||
def _swmmac_regs(name: str) -> tuple[int, int, int, int]:
|
||||
"""Return (dst, src0, src1, src2) register counts for SWMMAC instructions."""
|
||||
if 'f16_16x16x32' in name or 'bf16_16x16x32' in name: return (4, 4, 8, 1)
|
||||
if 'f32_16x16x32_f16' in name or 'f32_16x16x32_bf16' in name: return (8, 4, 8, 1)
|
||||
if 'i32_16x16x32_iu4' in name: return (8, 1, 2, 1)
|
||||
if 'i32_16x16x64_iu4' in name: return (8, 2, 4, 1)
|
||||
if 'i32_16x16x32_iu8' in name or 'f32_16x16x32_fp8' in name or 'f32_16x16x32_bf8' in name: return (8, 2, 4, 1)
|
||||
return (8, 8, 8, 8)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# IMPORTS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
from extra.assembly.amd.autogen.rdna3.ins import (VOP1, VOP1_SDST, VOP2, VOP3, VOP3_SDST, VOP3SD, VOP3P, VOPC, VOPD, VINTERP, SOP1, SOP2, SOPC, SOPK, SOPP, SMEM, DS, FLAT, GLOBAL, SCRATCH,
|
||||
VOP1Op, VOP2Op, VOP3Op, VOP3SDOp, VOPDOp, SOP1Op, SOPKOp, SOPPOp, SMEMOp, DSOp)
|
||||
from extra.assembly.amd.autogen.rdna4.ins import (VOP1 as R4_VOP1, VOP1_SDST as R4_VOP1_SDST, VOP2 as R4_VOP2, VOP3 as R4_VOP3, VOP3_SDST as R4_VOP3_SDST, VOP3SD as R4_VOP3SD, VOP3P as R4_VOP3P,
|
||||
VOPC as R4_VOPC, VOPD as R4_VOPD, VINTERP as R4_VINTERP, SOP1 as R4_SOP1, SOP2 as R4_SOP2, SOPC as R4_SOPC, SOPK as R4_SOPK, SOPP as R4_SOPP,
|
||||
SMEM as R4_SMEM, DS as R4_DS, VOPDOp as R4_VOPDOp)
|
||||
from extra.assembly.amd.autogen.cdna.ins import FLAT as C_FLAT
|
||||
|
||||
def _is_cdna(inst: Inst) -> bool: return 'cdna' in inst.__class__.__module__
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# CONSTANTS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
HWREG = {1: 'HW_REG_MODE', 2: 'HW_REG_STATUS', 3: 'HW_REG_TRAPSTS', 4: 'HW_REG_HW_ID', 5: 'HW_REG_GPR_ALLOC',
|
||||
6: 'HW_REG_LDS_ALLOC', 7: 'HW_REG_IB_STS', 15: 'HW_REG_SH_MEM_BASES', 18: 'HW_REG_PERF_SNAPSHOT_PC_LO',
|
||||
19: 'HW_REG_PERF_SNAPSHOT_PC_HI', 20: 'HW_REG_FLAT_SCR_LO', 21: 'HW_REG_FLAT_SCR_HI', 22: 'HW_REG_XNACK_MASK',
|
||||
23: 'HW_REG_HW_ID1', 24: 'HW_REG_HW_ID2', 25: 'HW_REG_POPS_PACKER', 28: 'HW_REG_IB_STS2'}
|
||||
HWREG_RDNA4 = {1: 'HW_REG_MODE', 2: 'HW_REG_STATUS', 4: 'HW_REG_STATE_PRIV', 5: 'HW_REG_GPR_ALLOC',
|
||||
6: 'HW_REG_LDS_ALLOC', 7: 'HW_REG_IB_STS', 10: 'HW_REG_PERF_SNAPSHOT_DATA', 11: 'HW_REG_PERF_SNAPSHOT_PC_LO',
|
||||
12: 'HW_REG_PERF_SNAPSHOT_PC_HI', 15: 'HW_REG_PERF_SNAPSHOT_DATA1', 16: 'HW_REG_PERF_SNAPSHOT_DATA2',
|
||||
17: 'HW_REG_EXCP_FLAG_PRIV', 18: 'HW_REG_EXCP_FLAG_USER', 19: 'HW_REG_TRAP_CTRL',
|
||||
20: 'HW_REG_SCRATCH_BASE_LO', 21: 'HW_REG_SCRATCH_BASE_HI', 23: 'HW_REG_HW_ID1',
|
||||
24: 'HW_REG_HW_ID2', 26: 'HW_REG_SCHED_MODE', 29: 'HW_REG_SHADER_CYCLES_LO',
|
||||
30: 'HW_REG_SHADER_CYCLES_HI', 31: 'HW_REG_DVGPR_ALLOC_LO', 32: 'HW_REG_DVGPR_ALLOC_HI'}
|
||||
MSG = {128: 'MSG_RTN_GET_DOORBELL', 129: 'MSG_RTN_GET_DDID', 130: 'MSG_RTN_GET_TMA',
|
||||
131: 'MSG_RTN_GET_REALTIME', 132: 'MSG_RTN_SAVE_WAVE', 133: 'MSG_RTN_GET_TBA',
|
||||
134: 'MSG_RTN_GET_TBA_TO_PC', 135: 'MSG_RTN_GET_SE_AID_ID'}
|
||||
# CDNA opcode name aliases for disasm (new name -> old name expected by tests)
|
||||
_CDNA_DISASM_ALIASES = {'v_fmac_f64': 'v_mul_legacy_f32', 'v_dot2c_f32_bf16': 'v_mac_f32', 'v_fmamk_f32': 'v_madmk_f32', 'v_fmaak_f32': 'v_madak_f32'}
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# HELPERS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _reg(p: str, b: int, n: int = 1) -> str: return f"{p}{_unwrap(b)}" if n == 1 else f"{p}[{_unwrap(b)}:{_unwrap(b)+n-1}]"
|
||||
def _sreg(b: int, n: int = 1) -> str: return _reg("s", _unwrap(b), n)
|
||||
def _vreg(b: int, n: int = 1) -> str: b = _unwrap(b); return _reg("v", b - 256 if b >= 256 else b, n)
|
||||
def _areg(b: int, n: int = 1) -> str: b = _unwrap(b); return _reg("a", b - 256 if b >= 256 else b, n) # accumulator registers for GFX90a
|
||||
def _ttmp(b, n: int = 1) -> str: b = _unwrap(b); return _reg("ttmp", b - 108, n) if 108 <= b <= 123 else None
|
||||
def _sreg_or_ttmp(b, n: int = 1) -> str: return _ttmp(b, n) or _sreg(b, n)
|
||||
|
||||
def _fmt_sdst(v, n: int = 1, cdna: bool = False) -> str:
|
||||
v = _unwrap(v)
|
||||
if t := _ttmp(v, n): return t
|
||||
pairs = SPECIAL_PAIRS_CDNA if cdna else SPECIAL_PAIRS
|
||||
gprs = SPECIAL_GPRS_CDNA if cdna else SPECIAL_GPRS
|
||||
if n > 1: return pairs.get(v) or gprs.get(v) or _sreg(v, n) # also check gprs for null/m0
|
||||
return gprs.get(v, f"s{v}")
|
||||
|
||||
def _fmt_src(v, n: int = 1, cdna: bool = False) -> str:
|
||||
v = _unwrap(v)
|
||||
if v == 253: return "src_scc" # SCC as source operand
|
||||
if n == 1: return decode_src(v, cdna)
|
||||
if v >= 256: return _vreg(v, n)
|
||||
if v <= 101: return _sreg(v, n) # s0-s101 can be pairs, but 102+ are special on CDNA
|
||||
pairs = SPECIAL_PAIRS_CDNA if cdna else SPECIAL_PAIRS
|
||||
if n == 2 and v in pairs: return pairs[v]
|
||||
if v <= 105: return _sreg(v, n) # s102-s105 regular pairs for RDNA
|
||||
if t := _ttmp(v, n): return t
|
||||
return decode_src(v, cdna)
|
||||
|
||||
def _fmt_v16(v, base: int = 256, hi_thresh: int = 384) -> str:
|
||||
v = _unwrap(v)
|
||||
return f"v{(v - base) & 0x7f}.{'h' if v >= hi_thresh else 'l'}"
|
||||
|
||||
def _has(op: str, *subs) -> bool: return any(s in op for s in subs)
|
||||
def _omod(v: int) -> str: return {1: " mul:2", 2: " mul:4", 3: " div:2"}.get(v, "")
|
||||
def _src16(inst, v: int) -> str: v = _unwrap(v); return _fmt_v16(v) if v >= 256 else _lit(inst, v) # format 16-bit src: vgpr.h/l or literal
|
||||
def _mods(*pairs) -> str: return " ".join(m for c, m in pairs if c)
|
||||
def _fmt_bits(label: str, val: int, count: int) -> str: return f"{label}:[{','.join(str((val >> i) & 1) for i in range(count))}]"
|
||||
|
||||
def _vop3_src(inst, v: int, neg: int, abs_: int, hi: int, n: int, f16: bool) -> str:
|
||||
"""Format VOP3 source operand with modifiers."""
|
||||
v = _unwrap(v)
|
||||
if v == 255: s = _lit(inst, v) # literal constant takes priority
|
||||
elif n > 1: s = _fmt_src(v, n)
|
||||
elif f16 and v >= 256: s = f"v{v - 256}.h" if hi else f"v{v - 256}.l"
|
||||
elif v == 253: s = "src_scc" # VOP3 sources use src_scc not scc
|
||||
else: s = _lit(inst, v)
|
||||
if abs_: s = f"|{s}|"
|
||||
return f"-{s}" if neg else s
|
||||
|
||||
def _opsel_str(opsel: int, n: int, need: bool, is16_d: bool) -> str:
|
||||
"""Format op_sel modifier string."""
|
||||
if not need: return ""
|
||||
dst_hi = (opsel >> 3) & 1
|
||||
if n == 1: return f" op_sel:[{opsel & 1},{dst_hi}]"
|
||||
if n == 2: return f" op_sel:[{opsel & 1},{(opsel >> 1) & 1},{dst_hi}]"
|
||||
return f" op_sel:[{opsel & 1},{(opsel >> 1) & 1},{(opsel >> 2) & 1},{dst_hi}]"
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# DISASSEMBLER
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _disasm_vop1(inst: VOP1) -> str:
|
||||
name, cdna = inst.op_name.lower() or f'vop1_op_{inst.op}', _is_cdna(inst)
|
||||
name = name.replace('_e32', '') # Strip _e32 suffix
|
||||
if any(x in name for x in ('v_nop', 'v_pipeflush', 'v_clrexcp')): return name # no operands
|
||||
if 'readfirstlane' in name:
|
||||
src = inst.src0.fmt() if inst.src0.offset >= 256 else decode_src(inst.src0.offset, cdna)
|
||||
vdst_off = inst.vdst.offset - 256 if inst.vdst.offset >= 256 else inst.vdst.offset
|
||||
return f"{name} {_fmt_sdst(vdst_off, 1, cdna)}, {src}"
|
||||
bits = inst.canonical_op_bits
|
||||
is16_dst, is16_src = not cdna and bits['d'] == 16, not cdna and bits['s0'] == 16
|
||||
# v_cvt_pk_f32_fp8/bf8: pcode has None dst type but outputs 2 VGPRs
|
||||
if 'cvt_pk_f32_fp8' in name or 'cvt_pk_f32_bf8' in name: is16_src = True
|
||||
# Format dst
|
||||
if is16_dst: dst = _fmt_v16(inst.vdst)
|
||||
else: dst = inst.vdst.fmt()
|
||||
# Format src
|
||||
if inst.src0.offset == 255: src = _lit(inst, inst.src0)
|
||||
elif is16_src and inst.src0.offset >= 256: src = _fmt_v16(inst.src0)
|
||||
elif inst.src0.sz > 1: src = _fmt_src(inst.src0, inst.src0.sz, cdna)
|
||||
else: src = _lit(inst, inst.src0)
|
||||
return f"{name} {dst}, {src}"
|
||||
|
||||
_VOP2_CARRY_OUT = {'v_add_co_u32', 'v_sub_co_u32', 'v_subrev_co_u32'} # carry out only
|
||||
_VOP2_CARRY_INOUT = {'v_addc_co_u32', 'v_subb_co_u32', 'v_subbrev_co_u32'} # carry in and out (CDNA)
|
||||
_VOP2_CARRY_INOUT_RDNA = {'v_add_co_ci_u32', 'v_sub_co_ci_u32', 'v_subrev_co_ci_u32'} # carry in and out (RDNA)
|
||||
def _disasm_vop2(inst: VOP2) -> str:
|
||||
name, cdna = inst.op_name.lower(), _is_cdna(inst)
|
||||
if cdna: name = _CDNA_DISASM_ALIASES.get(name, name) # apply CDNA aliases
|
||||
suf = "" if cdna or name.endswith('_e32') or (not cdna and inst.op == VOP2Op.V_DOT2ACC_F32_F16_E32) else "_e32"
|
||||
lit = getattr(inst, '_literal', None)
|
||||
is16 = not cdna and inst.canonical_op_bits['d'] == 16
|
||||
# fmaak/madak: dst = src0 * vsrc1 + K, fmamk/madmk: dst = src0 * K + vsrc1
|
||||
if 'fmaak' in name or 'madak' in name or (not cdna and inst.op in (VOP2Op.V_FMAAK_F32_E32, VOP2Op.V_FMAAK_F16_E32)):
|
||||
if lit is None: return f"op_{inst.op.value if hasattr(inst.op, 'value') else inst.op}"
|
||||
if is16: return f"{name}{suf} {_fmt_v16(inst.vdst)}, {_src16(inst, inst.src0)}, {_fmt_v16(inst.vsrc1)}, 0x{lit:x}"
|
||||
return f"{name}{suf} {inst.vdst.fmt()}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}, 0x{lit:x}"
|
||||
if 'fmamk' in name or 'madmk' in name or (not cdna and inst.op in (VOP2Op.V_FMAMK_F32_E32, VOP2Op.V_FMAMK_F16_E32)):
|
||||
if lit is None: return f"op_{inst.op.value if hasattr(inst.op, 'value') else inst.op}"
|
||||
if is16: return f"{name}{suf} {_fmt_v16(inst.vdst)}, {_src16(inst, inst.src0)}, 0x{lit:x}, {_fmt_v16(inst.vsrc1)}"
|
||||
return f"{name}{suf} {inst.vdst.fmt()}, {_lit(inst, inst.src0)}, 0x{lit:x}, {inst.vsrc1.fmt()}"
|
||||
if is16: return f"{name}{suf} {_fmt_v16(inst.vdst)}, {_src16(inst, inst.src0)}, {_fmt_v16(inst.vsrc1)}"
|
||||
vcc = "vcc" if cdna else "vcc_lo"
|
||||
if cdna and name in _VOP2_CARRY_OUT: return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}"
|
||||
if cdna and name in _VOP2_CARRY_INOUT: return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}, {vcc}"
|
||||
if not cdna and name in _VOP2_CARRY_INOUT_RDNA: return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}, {vcc}"
|
||||
sn0 = inst.canonical_op_regs.get('s0', 1)
|
||||
if inst.vdst.sz > 1 or sn0 > 1 or inst.vsrc1.sz > 1:
|
||||
src0 = _lit(inst, inst.src0) if inst.src0.offset == 255 else _fmt_src(inst.src0, sn0, cdna)
|
||||
return f"{name.replace('_e32', '')} {inst.vdst.fmt()}, {src0}, {inst.vsrc1.fmt()}"
|
||||
return f"{name}{suf} {inst.vdst.fmt()}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}" + (f", {vcc}" if name == 'v_cndmask_b32' else "")
|
||||
|
||||
def _disasm_vopc(inst: VOPC) -> str:
|
||||
name, cdna = inst.op_name.lower(), _is_cdna(inst)
|
||||
bits = inst.canonical_op_bits
|
||||
is16 = bits['s0'] == 16
|
||||
if cdna:
|
||||
s0 = _lit(inst, inst.src0) if inst.src0.offset == 255 else _fmt_src(inst.src0, inst.src0.sz, cdna)
|
||||
return f"{name} vcc, {s0}, {inst.vsrc1.fmt()}" # CDNA VOPC always outputs vcc
|
||||
# RDNA: v_cmpx_* writes to exec (no vcc), v_cmp_* writes to vcc_lo
|
||||
has_vcc = 'cmpx' not in name
|
||||
s0 = _lit(inst, inst.src0) if inst.src0.offset == 255 else inst.src0.fmt() if inst.src0.sz > 1 else _src16(inst, inst.src0.offset) if is16 else _lit(inst, inst.src0)
|
||||
s1 = inst.vsrc1.fmt() if inst.vsrc1.sz > 1 else _fmt_v16(inst.vsrc1) if is16 else inst.vsrc1.fmt()
|
||||
suf = "" if name.endswith('_e32') else "_e32"
|
||||
return f"{name}{suf} vcc_lo, {s0}, {s1}" if has_vcc else f"{name}{suf} {s0}, {s1}"
|
||||
|
||||
NO_ARG_SOPP = {SOPPOp.S_BARRIER, SOPPOp.S_WAKEUP, SOPPOp.S_ICACHE_INV,
|
||||
SOPPOp.S_WAIT_IDLE, SOPPOp.S_ENDPGM_SAVED, SOPPOp.S_CODE_END, SOPPOp.S_ENDPGM_ORDERED_PS_DONE, SOPPOp.S_TTRACEDATA}
|
||||
_CDNA_NO_ARG_SOPP = {'s_endpgm', 's_barrier', 's_wakeup', 's_icache_inv', 's_ttracedata', 's_nop', 's_sethalt', 's_sleep',
|
||||
's_setprio', 's_trap', 's_incperflevel', 's_decperflevel', 's_sendmsg', 's_sendmsghalt'}
|
||||
|
||||
def _disasm_sopp(inst: SOPP) -> str:
|
||||
name, cdna = inst.op_name.lower(), _is_cdna(inst)
|
||||
is_rdna4 = 'rdna4' in inst.__class__.__module__
|
||||
# Ops that have no argument when simm16 == 0
|
||||
no_arg_zero = {'s_barrier', 's_wakeup', 's_icache_inv', 's_ttracedata', 's_wait_idle', 's_endpgm_saved',
|
||||
's_endpgm_ordered_ps_done', 's_code_end'}
|
||||
if name in no_arg_zero: return name if inst.simm16 == 0 else f"{name} {inst.simm16}"
|
||||
if name == 's_endpgm': return name if inst.simm16 == 0 else f"{name} {inst.simm16}"
|
||||
if cdna:
|
||||
if name == 's_waitcnt':
|
||||
vm, lgkm, exp = inst.simm16 & 0xf, (inst.simm16 >> 8) & 0x3f, (inst.simm16 >> 4) & 0x7
|
||||
p = [f"vmcnt({vm})" if vm != 0xf else "", f"expcnt({exp})" if exp != 7 else "", f"lgkmcnt({lgkm})" if lgkm != 0x3f else ""]
|
||||
return f"s_waitcnt {' '.join(x for x in p if x) or '0'}"
|
||||
if name.startswith(('s_cbranch', 's_branch')): return f"{name} {inst.simm16}"
|
||||
return f"{name} 0x{inst.simm16:x}" if inst.simm16 else name
|
||||
# RDNA (use name-based checks instead of enum-based for cross-arch compatibility)
|
||||
if name == 's_waitcnt':
|
||||
if is_rdna4:
|
||||
return f"{name} {inst.simm16}" if inst.simm16 else f"{name} 0"
|
||||
vm, exp, lgkm = (inst.simm16 >> 10) & 0x3f, inst.simm16 & 0xf, (inst.simm16 >> 4) & 0x3f
|
||||
p = [f"vmcnt({vm})" if vm != 0x3f else "", f"expcnt({exp})" if exp != 7 else "", f"lgkmcnt({lgkm})" if lgkm != 0x3f else ""]
|
||||
return f"s_waitcnt {' '.join(x for x in p if x) or '0'}"
|
||||
if name == 's_delay_alu':
|
||||
deps = ['VALU_DEP_1','VALU_DEP_2','VALU_DEP_3','VALU_DEP_4','TRANS32_DEP_1','TRANS32_DEP_2','TRANS32_DEP_3','FMA_ACCUM_CYCLE_1','SALU_CYCLE_1','SALU_CYCLE_2','SALU_CYCLE_3']
|
||||
skips = ['SAME','NEXT','SKIP_1','SKIP_2','SKIP_3','SKIP_4']
|
||||
id0, skip, id1 = inst.simm16 & 0xf, (inst.simm16 >> 4) & 0x7, (inst.simm16 >> 7) & 0xf
|
||||
dep = lambda v: deps[v-1] if 0 < v <= len(deps) else str(v)
|
||||
p = [f"instid0({dep(id0)})" if id0 else "", f"instskip({skips[skip]})" if skip else "", f"instid1({dep(id1)})" if id1 else ""]
|
||||
return f"s_delay_alu {' | '.join(x for x in p if x) or '0'}"
|
||||
if name.startswith(('s_cbranch', 's_branch')): return f"{name} 0x{inst.simm16:x}"
|
||||
return f"{name} 0x{inst.simm16:x}"
|
||||
|
||||
def _disasm_smem(inst: SMEM) -> str:
|
||||
name, cdna = inst.op_name.lower(), _is_cdna(inst)
|
||||
if name in ('s_gl1_inv', 's_dcache_inv'): return name
|
||||
soe, imm = getattr(inst, 'soe', 0), getattr(inst, 'imm', 1)
|
||||
is_rdna4 = 'rdna4' in inst.__class__.__module__
|
||||
offset = inst.ioffset if is_rdna4 else getattr(inst, 'offset', 0)
|
||||
if cdna:
|
||||
if soe and imm: off_s = f"{decode_src(inst.soffset, cdna)} offset:0x{offset:x}"
|
||||
elif imm: off_s = f"0x{offset:x}"
|
||||
elif offset < 256: off_s = decode_src(offset, cdna)
|
||||
else: off_s = decode_src(inst.soffset, cdna)
|
||||
elif offset and inst.soffset != 124: off_s = f"{decode_src(inst.soffset, cdna)} offset:0x{offset:x}"
|
||||
elif offset: off_s = f"0x{offset:x}"
|
||||
else: off_s = decode_src(inst.soffset, cdna)
|
||||
is_buffer = 'buffer' in name or 's_atc_probe_buffer' == name
|
||||
sbase_idx, sbase_count = _unwrap(inst.sbase), 4 if is_buffer else 2
|
||||
sbase_str = _fmt_src(sbase_idx, sbase_count, cdna) if sbase_count == 2 else _sreg(sbase_idx, sbase_count) if sbase_idx <= 105 else _reg("ttmp", sbase_idx - 108, sbase_count)
|
||||
if name in ('s_atc_probe', 's_atc_probe_buffer'): return f"{name} {_unwrap(inst.sdata)}, {sbase_str}, {off_s}"
|
||||
if 'prefetch' in name:
|
||||
off = getattr(inst, 'ioffset', getattr(inst, 'offset', 0))
|
||||
if off >= 0x800000: off = off - 0x1000000
|
||||
off_s = f"0x{off:x}" if off > 255 else str(off)
|
||||
soff_s = decode_src(inst.soffset, cdna) if inst.soffset != 124 else "null"
|
||||
if 'pc_rel' in name: return f"{name} {off_s}, {soff_s}, {_unwrap(inst.sdata)}"
|
||||
return f"{name} {sbase_str}, {off_s}, {soff_s}, {_unwrap(inst.sdata)}"
|
||||
# Use get_field_bits for register count
|
||||
dst_n = inst.canonical_op_regs.get('d', 1)
|
||||
th, scope = getattr(inst, 'th', 0), getattr(inst, 'scope', 0)
|
||||
if is_rdna4: # RDNA4 uses th/scope instead of glc/dlc
|
||||
th_names = ['TH_LOAD_RT', 'TH_LOAD_NT', 'TH_LOAD_HT', 'TH_LOAD_LU']
|
||||
scope_names = ['SCOPE_CU', 'SCOPE_SE', 'SCOPE_DEV', 'SCOPE_SYS']
|
||||
mods = (f" th:{th_names[th]}" if th else "") + (f" scope:{scope_names[scope]}" if scope else "")
|
||||
return f"{name} {_fmt_sdst(inst.sdata, dst_n, cdna)}, {sbase_str}, {off_s}{mods}"
|
||||
if th or scope:
|
||||
th_names = ['TH_LOAD_RT', 'TH_LOAD_NT', 'TH_LOAD_HT', 'TH_LOAD_LU']
|
||||
scope_names = ['SCOPE_CU', 'SCOPE_SE', 'SCOPE_DEV', 'SCOPE_SYS']
|
||||
mods = (f" th:{th_names[th]}" if th else "") + (f" scope:{scope_names[scope]}" if scope else "")
|
||||
return f"{name} {_fmt_sdst(inst.sdata, dst_n, cdna)}, {sbase_str}, {off_s}{mods}"
|
||||
return f"{name} {_fmt_sdst(inst.sdata, dst_n, cdna)}, {sbase_str}, {off_s}" + _mods((inst.glc, " glc"), (getattr(inst, 'dlc', 0), " dlc"))
|
||||
|
||||
def _disasm_flat(inst: FLAT) -> str:
|
||||
name, cdna = inst.op_name.lower(), _is_cdna(inst)
|
||||
acc = getattr(inst, 'acc', 0)
|
||||
reg_fn = _areg if acc else _vreg
|
||||
seg = ['flat', 'scratch', 'global'][inst.seg] if inst.seg < 3 else 'flat'
|
||||
instr = f"{seg}_{name.split('_', 1)[1] if '_' in name else name}"
|
||||
off_val = inst.offset if seg == 'flat' else (inst.offset if inst.offset < 4096 else inst.offset - 8192)
|
||||
# Use get_field_bits: data for stores/atomics, d for loads
|
||||
regs = inst.canonical_op_regs
|
||||
w = regs.get('data', regs.get('d', 1)) if 'store' in name or 'atomic' in name else regs.get('d', 1)
|
||||
off_s = f" offset:{off_val}" if off_val else ""
|
||||
if cdna: mods = f"{off_s}{' glc' if inst.sc0 else ''}{' slc' if inst.nt else ''}"
|
||||
else: mods = f"{off_s}{' glc' if inst.glc else ''}{' slc' if inst.slc else ''}{' dlc' if inst.dlc else ''}"
|
||||
if seg == 'flat' or _unwrap(inst.saddr) == 0x7F: saddr_s = ""
|
||||
elif _unwrap(inst.saddr) == 124: saddr_s = ", off"
|
||||
elif seg == 'scratch': saddr_s = f", {decode_src(inst.saddr, cdna)}"
|
||||
elif _unwrap(inst.saddr) in (SPECIAL_PAIRS_CDNA if cdna else SPECIAL_PAIRS): saddr_s = f", {(SPECIAL_PAIRS_CDNA if cdna else SPECIAL_PAIRS)[_unwrap(inst.saddr)]}"
|
||||
elif t := _ttmp(inst.saddr, 2): saddr_s = f", {t}"
|
||||
else: saddr_s = f", {_sreg(inst.saddr, 2) if _unwrap(inst.saddr) < 106 else decode_src(_unwrap(inst.saddr), cdna)}"
|
||||
if 'addtid' in name: return f"{instr} {reg_fn(inst.data if 'store' in name else inst.vdst)}{saddr_s}{mods}"
|
||||
if cdna: addr_w = 1 if seg == 'scratch' else 2
|
||||
else: addr_w = 1 if seg == 'scratch' or (_unwrap(inst.saddr) not in (0x7F, 124)) else 2
|
||||
addr_s = "off" if not inst.sve and seg == 'scratch' else _vreg(inst.addr, addr_w)
|
||||
data_s, vdst_s = reg_fn(inst.data, w), reg_fn(inst.vdst, w // 2 if 'cmpswap' in name else w)
|
||||
glc_or_sc0 = inst.sc0 if cdna else inst.glc
|
||||
if 'atomic' in name:
|
||||
return f"{instr} {vdst_s}, {addr_s}, {data_s}{saddr_s if seg != 'flat' else ''}{mods}" if glc_or_sc0 else f"{instr} {addr_s}, {data_s}{saddr_s if seg != 'flat' else ''}{mods}"
|
||||
if 'store' in name: return f"{instr} {addr_s}, {data_s}{saddr_s}{mods}"
|
||||
return f"{instr} {reg_fn(inst.vdst, w)}, {addr_s}{saddr_s}{mods}"
|
||||
|
||||
def _disasm_ds(inst: DS) -> str:
|
||||
op, name = inst.op, inst.op_name.lower()
|
||||
acc = getattr(inst, 'acc', 0)
|
||||
reg_fn = _areg if acc else _vreg
|
||||
gds = " gds" if getattr(inst, 'gds', 0) else ""
|
||||
off = f" offset:{inst.offset0 | (inst.offset1 << 8)}" if inst.offset0 or inst.offset1 else ""
|
||||
off2 = (" offset0:" + str(inst.offset0) if inst.offset0 else "") + (" offset1:" + str(inst.offset1) if inst.offset1 else "")
|
||||
# Use get_field_bits: data for stores/writes/atomics, d for loads
|
||||
regs = inst.canonical_op_regs
|
||||
w = regs.get('data', regs.get('d', 1)) if 'store' in name or 'write' in name or ('load' not in name and 'read' not in name) else regs.get('d', 1)
|
||||
d0, d1, dst, addr = reg_fn(inst.data0, w), reg_fn(inst.data1, w), reg_fn(inst.vdst, w), _vreg(inst.addr)
|
||||
|
||||
if name == 'ds_nop': return name
|
||||
if name == 'ds_bvh_stack_rtn_b32': return f"{name} {_vreg(inst.vdst)}, {addr}, {_vreg(inst.data0)}, {_vreg(inst.data1, 4)}{off}{gds}"
|
||||
if 'bvh_stack_push' in name:
|
||||
d1_regs = 8 if 'push8' in name else 4
|
||||
vdst_regs = 2 if 'pop2' in name else 1
|
||||
vdst_s = _vreg(inst.vdst, vdst_regs) if vdst_regs > 1 else _vreg(inst.vdst)
|
||||
return f"{name} {vdst_s}, {addr}, {_vreg(inst.data0)}, {_vreg(inst.data1, d1_regs)}{off}{gds}"
|
||||
if 'gws_sema' in name and 'sema_br' not in name: return f"{name}{off}{gds}"
|
||||
if 'gws_' in name: return f"{name} {addr}{off}{gds}"
|
||||
if name in ('ds_consume', 'ds_append'): return f"{name} {reg_fn(inst.vdst)}{off}{gds}"
|
||||
if 'gs_reg' in name: return f"{name} {reg_fn(inst.vdst, 2)}, {reg_fn(inst.data0)}{off}{gds}"
|
||||
if '2addr' in name:
|
||||
if 'load' in name: return f"{name} {reg_fn(inst.vdst, regs.get('d', 1))}, {addr}{off2}{gds}"
|
||||
if 'store' in name and 'xchg' not in name: return f"{name} {addr}, {d0}, {d1}{off2}{gds}"
|
||||
return f"{name} {reg_fn(inst.vdst, regs.get('d', 1))}, {addr}, {d0}, {d1}{off2}{gds}"
|
||||
if 'write2' in name: return f"{name} {addr}, {d0}, {d1}{off2}{gds}"
|
||||
if 'read2' in name: return f"{name} {reg_fn(inst.vdst, regs.get('d', 1))}, {addr}{off2}{gds}"
|
||||
if 'load' in name: return f"{name} {reg_fn(inst.vdst)}{off}{gds}" if 'addtid' in name else f"{name} {dst}, {addr}{off}{gds}"
|
||||
if 'store' in name and not _has(name, 'cmp', 'xchg'):
|
||||
return f"{name} {reg_fn(inst.data0)}{off}{gds}" if 'addtid' in name else f"{name} {addr}, {d0}{off}{gds}"
|
||||
if 'swizzle' in name or name == 'ds_ordered_count': return f"{name} {reg_fn(inst.vdst)}, {addr}{off}{gds}"
|
||||
if 'permute' in name: return f"{name} {reg_fn(inst.vdst)}, {addr}, {reg_fn(inst.data0)}{off}{gds}"
|
||||
if 'condxchg' in name: return f"{name} {reg_fn(inst.vdst, 2)}, {addr}, {reg_fn(inst.data0, 2)}{off}{gds}"
|
||||
if _has(name, 'cmpstore', 'mskor', 'wrap'):
|
||||
return f"{name} {dst}, {addr}, {d0}, {d1}{off}{gds}" if '_rtn' in name else f"{name} {addr}, {d0}, {d1}{off}{gds}"
|
||||
return f"{name} {dst}, {addr}, {d0}{off}{gds}" if '_rtn' in name else f"{name} {addr}, {d0}{off}{gds}"
|
||||
|
||||
def _disasm_vop3(inst: VOP3) -> str:
|
||||
op, name = inst.op, inst.op_name.lower()
|
||||
n_up = name.upper()
|
||||
bits = inst.canonical_op_bits
|
||||
|
||||
# RDNA4 v_s_* scalar VOP3 instructions - vdst is SGPR (VGPRField adds 256)
|
||||
if name.startswith('v_s_'):
|
||||
src = _lit(inst, inst.src0) if _unwrap(inst.src0) == 255 else ("src_scc" if _unwrap(inst.src0) == 253 else _fmt_src(inst.src0, max(1, bits['s0'] // 32)))
|
||||
if inst.neg & 1: src = f"-{src}"
|
||||
if inst.abs & 1: src = f"|{src}|"
|
||||
clamp = getattr(inst, 'cm', None) or getattr(inst, 'clmp', 0)
|
||||
vdst_raw = _unwrap(inst.vdst)
|
||||
return f"{name} s{vdst_raw - 256 if vdst_raw >= 256 else vdst_raw}, {src}" + (" clamp" if clamp else "") + _omod(inst.omod)
|
||||
|
||||
# Use get_field_bits for register sizes and 16-bit detection
|
||||
r0, r1, r2 = max(1, bits['s0'] // 32), max(1, bits['s1'] // 32), max(1, bits['s2'] // 32)
|
||||
dn = max(1, bits['d'] // 32)
|
||||
is16_d, is16_s, is16_s2 = bits['d'] == 16, bits['s0'] == 16, bits['s2'] == 16
|
||||
|
||||
s0 = _vop3_src(inst, inst.src0, inst.neg&1, inst.abs&1, inst.opsel&1, r0, is16_s)
|
||||
s1 = _vop3_src(inst, inst.src1, inst.neg&2, inst.abs&2, inst.opsel&2, r1, is16_s)
|
||||
s2 = _vop3_src(inst, inst.src2, inst.neg&4, inst.abs&4, inst.opsel&4, r2, is16_s2)
|
||||
|
||||
# Format destination
|
||||
if 'readlane' in name:
|
||||
vdst_off = inst.vdst.offset - 256 if inst.vdst.offset >= 256 else inst.vdst.offset
|
||||
dst = _fmt_sdst(vdst_off, 1)
|
||||
elif is16_d: dst = f"{inst.vdst.fmt()}.h" if (inst.opsel & 8) else f"{inst.vdst.fmt()}.l"
|
||||
else: dst = inst.vdst.fmt()
|
||||
|
||||
clamp = getattr(inst, 'cm', None) or getattr(inst, 'clmp', 0)
|
||||
cl, om = " clamp" if clamp else "", _omod(inst.omod)
|
||||
nonvgpr_opsel = (inst.src0.offset < 256 and (inst.opsel & 1)) or (inst.src1.offset < 256 and (inst.opsel & 2)) or (inst.src2.offset < 256 and (inst.opsel & 4))
|
||||
need_opsel = nonvgpr_opsel or (inst.opsel and not is16_s)
|
||||
|
||||
op_val = inst.op.value if hasattr(inst.op, 'value') else inst.op
|
||||
e64 = "" if name.endswith('_e64') else "_e64"
|
||||
if op_val < 256: # VOPC
|
||||
vdst_off = inst.vdst.offset - 256 if inst.vdst.offset >= 256 else inst.vdst.offset
|
||||
return f"{name}{e64} {s0}, {s1}{cl}" if name.startswith('v_cmpx') else f"{name}{e64} {_fmt_sdst(vdst_off, 1)}, {s0}, {s1}{cl}"
|
||||
if op_val < 384: # VOP2
|
||||
n = inst.num_srcs() or 2
|
||||
os = _opsel_str(inst.opsel, n, need_opsel, is16_d)
|
||||
return f"{name}{e64} {dst}, {s0}, {s1}, {s2}{os}{cl}{om}" if n == 3 else f"{name}{e64} {dst}, {s0}, {s1}{os}{cl}{om}"
|
||||
if op_val < 512: # VOP1
|
||||
if re.match(r'v_cvt_f32_(bf|fp)8', name) and inst.opsel:
|
||||
os = f" byte_sel:{((inst.opsel & 1) << 1) | ((inst.opsel >> 1) & 1)}"
|
||||
else:
|
||||
os = _opsel_str(inst.opsel, 1, need_opsel, is16_d)
|
||||
if 'v_nop' in name or 'v_pipeflush' in name: return f"{name}{e64}"
|
||||
return f"{name}{e64} {dst}, {s0}{os}{cl}{om}"
|
||||
# Native VOP3
|
||||
n = inst.num_srcs() or 2
|
||||
os = f" byte_sel:{inst.opsel >> 2}" if 'cvt_sr' in name and inst.opsel else _opsel_str(inst.opsel, n, need_opsel, is16_d)
|
||||
return f"{name} {dst}, {s0}, {s1}, {s2}{os}{cl}{om}" if n == 3 else f"{name} {dst}, {s0}, {s1}{os}{cl}{om}"
|
||||
|
||||
def _disasm_vop3sd(inst: VOP3SD) -> str:
|
||||
name = inst.op_name.lower()
|
||||
def src(reg, neg):
|
||||
s = _lit(inst, reg.offset) if reg.offset == 255 else ("src_scc" if reg.offset == 253 else (reg.fmt() if reg.sz > 1 else _lit(inst, reg.offset)))
|
||||
return f"neg({s})" if neg and reg.offset == 255 else (f"-{s}" if neg else s)
|
||||
s0, s1, s2 = src(inst.src0, inst.neg & 1), src(inst.src1, inst.neg & 2), src(inst.src2, inst.neg & 4)
|
||||
# VOP3SD: _co_ ops (add/sub) without _ci_ have only 2 sources, all others (mad, div_scale, _co_ci_) have 3 sources
|
||||
has_only_two_srcs = '_co_' in name and '_ci_' not in name and 'mad' not in name
|
||||
srcs = f"{s0}, {s1}" if has_only_two_srcs else f"{s0}, {s1}, {s2}"
|
||||
clamp = getattr(inst, 'cm', None) or getattr(inst, 'clmp', 0)
|
||||
return f"{name} {inst.vdst.fmt()}, {_fmt_sdst(inst.sdst, 1)}, {srcs}{' clamp' if clamp else ''}{_omod(inst.omod)}"
|
||||
|
||||
def _disasm_vopd(inst: VOPD) -> str:
|
||||
lit = inst._literal or getattr(inst, 'literal', None)
|
||||
is_rdna4 = 'rdna4' in inst.__class__.__module__
|
||||
op_enum = R4_VOPDOp if is_rdna4 else VOPDOp
|
||||
vdst_y, nx, ny = (_unwrap(inst.vdsty) << 1) | ((_unwrap(inst.vdstx) & 1) ^ 1), op_enum(inst.opx).name.lower(), op_enum(inst.opy).name.lower()
|
||||
def half(n, vd, s0, vs1):
|
||||
vd, vs1 = _vi(vd), _vi(vs1)
|
||||
if 'mov' in n: return f"{n} v{vd}, {_lit(inst, s0)}"
|
||||
if 'fmamk' in n and lit: return f"{n} v{vd}, {_lit(inst, s0)}, 0x{lit:x}, v{vs1}"
|
||||
if 'fmaak' in n and lit: return f"{n} v{vd}, {_lit(inst, s0)}, v{vs1}, 0x{lit:x}"
|
||||
return f"{n} v{vd}, {_lit(inst, s0)}, v{vs1}"
|
||||
return f"{half(nx, inst.vdstx, inst.srcx0, inst.vsrcx1)} :: {half(ny, vdst_y, inst.srcy0, inst.vsrcy1)}"
|
||||
|
||||
def _disasm_vop3p(inst: VOP3P) -> str:
|
||||
name = inst.op_name.lower()
|
||||
is_wmma, is_swmmac, n, is_fma_mix = 'wmma' in name, 'swmmac' in name, inst.num_srcs() or 2, 'fma_mix' in name
|
||||
def get_src(reg):
|
||||
return _lit(inst, reg.offset) if reg.offset == 255 else reg.fmt()
|
||||
src0, src1, src2, dst = get_src(inst.src0), get_src(inst.src1), get_src(inst.src2), inst.vdst.fmt()
|
||||
opsel_hi = inst.opsel_hi | (inst.opsel_hi2 << 2)
|
||||
clamp = getattr(inst, 'cm', None) or getattr(inst, 'clmp', 0)
|
||||
if is_fma_mix:
|
||||
def m(s, neg, abs_): return f"-{f'|{s}|' if abs_ else s}" if neg else (f"|{s}|" if abs_ else s)
|
||||
src0, src1, src2 = m(src0, inst.neg & 1, inst.neg_hi & 1), m(src1, inst.neg & 2, inst.neg_hi & 2), m(src2, inst.neg & 4, inst.neg_hi & 4)
|
||||
mods = ([_fmt_bits("op_sel", inst.opsel, n)] if inst.opsel else []) + ([_fmt_bits("op_sel_hi", opsel_hi, n)] if opsel_hi else []) + (["clamp"] if clamp else [])
|
||||
elif is_swmmac:
|
||||
mods = ([f"index_key:{inst.opsel}"] if inst.opsel else []) + ([_fmt_bits("neg_lo", inst.neg, n)] if inst.neg else []) + \
|
||||
([_fmt_bits("neg_hi", inst.neg_hi, n)] if inst.neg_hi else []) + (["clamp"] if clamp else [])
|
||||
else:
|
||||
opsel_hi_default = 7 if n == 3 else 3
|
||||
mods = ([_fmt_bits("op_sel", inst.opsel, n)] if inst.opsel else []) + ([_fmt_bits("op_sel_hi", opsel_hi, n)] if opsel_hi != opsel_hi_default else []) + \
|
||||
([_fmt_bits("neg_lo", inst.neg, n)] if inst.neg else []) + ([_fmt_bits("neg_hi", inst.neg_hi, n)] if inst.neg_hi else []) + (["clamp"] if clamp else [])
|
||||
return f"{name} {dst}, {src0}, {src1}, {src2}{' ' + ' '.join(mods) if mods else ''}" if n == 3 else f"{name} {dst}, {src0}, {src1}{' ' + ' '.join(mods) if mods else ''}"
|
||||
|
||||
def _disasm_sop1(inst: SOP1) -> str:
|
||||
op, name, cdna = inst.op, inst.op_name.lower(), _is_cdna(inst)
|
||||
# Use get_field_bits for register sizes
|
||||
regs = inst.canonical_op_regs
|
||||
dst_regs, src_regs = regs.get('d', 1), regs.get('s0', 1)
|
||||
src = _lit(inst, inst.ssrc0) if _unwrap(inst.ssrc0) == 255 else _fmt_src(inst.ssrc0, src_regs, cdna)
|
||||
if not cdna:
|
||||
if 'getpc_b64' in name: return f"{name} {_fmt_sdst(inst.sdst, 2)}"
|
||||
if 'setpc_b64' in name or 'rfe_b64' in name: return f"{name} {src}"
|
||||
if 'swappc_b64' in name: return f"{name} {_fmt_sdst(inst.sdst, 2)}, {src}"
|
||||
if 'sendmsg_rtn' in name:
|
||||
v = _unwrap(inst.ssrc0)
|
||||
msg_str = MSG.get(v)
|
||||
return f"{name} {_fmt_sdst(inst.sdst, dst_regs)}, sendmsg({msg_str})" if msg_str else f"{name} {_fmt_sdst(inst.sdst, dst_regs)}, 0x{v:x}"
|
||||
sop1_src_only = ('S_ALLOC_VGPR', 'S_SLEEP_VAR', 'S_BARRIER_SIGNAL', 'S_BARRIER_SIGNAL_ISFIRST', 'S_BARRIER_INIT', 'S_BARRIER_JOIN')
|
||||
if inst.op_name in sop1_src_only: return f"{name} {src}"
|
||||
return f"{name} {_fmt_sdst(inst.sdst, dst_regs, cdna)}, {src}"
|
||||
|
||||
def _disasm_sop2(inst: SOP2) -> str:
|
||||
cdna, name = _is_cdna(inst), inst.op_name.lower()
|
||||
lit = getattr(inst, '_literal', None)
|
||||
# Use get_field_bits for register sizes
|
||||
regs = inst.canonical_op_regs
|
||||
dn, s0n, s1n = regs['d'], regs['s0'], regs['s1']
|
||||
s0 = _lit(inst, inst.ssrc0) if _unwrap(inst.ssrc0) == 255 else _fmt_src(inst.ssrc0, s0n, cdna)
|
||||
s1 = _lit(inst, inst.ssrc1) if _unwrap(inst.ssrc1) == 255 else _fmt_src(inst.ssrc1, s1n, cdna)
|
||||
dst = _fmt_sdst(inst.sdst, dn, cdna)
|
||||
if 'fmamk' in name and lit is not None: return f"{name} {dst}, {s0}, 0x{lit:x}, {s1}"
|
||||
if 'fmaak' in name and lit is not None: return f"{name} {dst}, {s0}, {s1}, 0x{lit:x}"
|
||||
return f"{name} {dst}, {s0}, {s1}"
|
||||
|
||||
def _disasm_sopc(inst: SOPC) -> str:
|
||||
cdna, regs = _is_cdna(inst), inst.canonical_op_regs
|
||||
s0 = _lit(inst, inst.ssrc0) if _unwrap(inst.ssrc0) == 255 else _fmt_src(inst.ssrc0, regs['s0'], cdna)
|
||||
s1 = _lit(inst, inst.ssrc1) if _unwrap(inst.ssrc1) == 255 else _fmt_src(inst.ssrc1, regs['s1'], cdna)
|
||||
return f"{inst.op_name.lower()} {s0}, {s1}"
|
||||
|
||||
def _disasm_sopk(inst: SOPK) -> str:
|
||||
op, name, cdna = inst.op, inst.op_name.lower(), _is_cdna(inst)
|
||||
is_rdna4 = 'rdna4' in inst.__class__.__module__
|
||||
hw = HWREG_RDNA4 if is_rdna4 else HWREG
|
||||
def fmt_hwreg(hid, hoff, hsz):
|
||||
if hid not in hw: return f"0x{inst.simm16:x}"
|
||||
hr_name = hw[hid]
|
||||
return f"hwreg({hr_name})" if hoff == 0 and hsz == 32 else f"hwreg({hr_name}, {hoff}, {hsz})"
|
||||
if name == 's_setreg_imm32_b32':
|
||||
hid, hoff, hsz = inst.simm16 & 0x3f, (inst.simm16 >> 6) & 0x1f, ((inst.simm16 >> 11) & 0x1f) + 1
|
||||
return f"{name} {fmt_hwreg(hid, hoff, hsz)}, 0x{inst._literal:x}"
|
||||
if name == 's_version': return f"{name} 0x{inst.simm16:x}"
|
||||
if name in ('s_setreg_b32', 's_getreg_b32'):
|
||||
hid, hoff, hsz = inst.simm16 & 0x3f, (inst.simm16 >> 6) & 0x1f, ((inst.simm16 >> 11) & 0x1f) + 1
|
||||
hs = fmt_hwreg(hid, hoff, hsz)
|
||||
return f"{name} {hs}, {_fmt_sdst(inst.sdst, 1, cdna)}" if 'setreg' in name else f"{name} {_fmt_sdst(inst.sdst, 1, cdna)}, {hs}"
|
||||
if name in ('s_subvector_loop_begin', 's_subvector_loop_end'):
|
||||
return f"{name} {_fmt_sdst(inst.sdst, 1)}, 0x{inst.simm16:x}"
|
||||
return f"{name} {_fmt_sdst(inst.sdst, inst.canonical_op_regs['d'], cdna)}, 0x{inst.simm16:x}"
|
||||
|
||||
def _disasm_vinterp(inst: VINTERP) -> str:
|
||||
mods = _mods((inst.waitexp, f"wait_exp:{inst.waitexp}"), (inst.clmp, "clamp"))
|
||||
return f"{inst.op_name.lower()} {inst.vdst.fmt()}, {_lit(inst, inst.src0, inst.neg & 1)}, {_lit(inst, inst.src1, inst.neg & 2)}, {_lit(inst, inst.src2, inst.neg & 4)}" + (" " + mods if mods else "")
|
||||
|
||||
DISASM_HANDLERS: dict[type, callable] = {
|
||||
VOP1: _disasm_vop1, VOP1_SDST: _disasm_vop1, VOP2: _disasm_vop2, VOPC: _disasm_vopc, VOP3: _disasm_vop3, VOP3_SDST: _disasm_vop3, VOP3SD: _disasm_vop3sd, VOPD: _disasm_vopd, VOP3P: _disasm_vop3p,
|
||||
VINTERP: _disasm_vinterp, SOPP: _disasm_sopp, SMEM: _disasm_smem, DS: _disasm_ds, FLAT: _disasm_flat, GLOBAL: _disasm_flat, SCRATCH: _disasm_flat,
|
||||
SOP1: _disasm_sop1, SOP2: _disasm_sop2, SOPC: _disasm_sopc, SOPK: _disasm_sopk,
|
||||
# RDNA4
|
||||
R4_VOP1: _disasm_vop1, R4_VOP1_SDST: _disasm_vop1, R4_VOP2: _disasm_vop2, R4_VOPC: _disasm_vopc, R4_VOP3: _disasm_vop3, R4_VOP3_SDST: _disasm_vop3, R4_VOP3SD: _disasm_vop3sd,
|
||||
R4_VOPD: _disasm_vopd, R4_VOP3P: _disasm_vop3p, R4_VINTERP: _disasm_vinterp, R4_SOPP: _disasm_sopp, R4_SMEM: _disasm_smem,
|
||||
R4_DS: _disasm_ds, R4_SOP1: _disasm_sop1, R4_SOP2: _disasm_sop2, R4_SOPC: _disasm_sopc, R4_SOPK: _disasm_sopk}
|
||||
|
||||
def disasm(inst: Inst) -> str: return DISASM_HANDLERS[type(inst)](inst)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# CDNA DISASSEMBLER SUPPORT
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
try:
|
||||
from extra.assembly.amd.autogen.cdna.ins import (VOP1 as CDNA_VOP1, VOP2 as CDNA_VOP2, VOPC as CDNA_VOPC, VOP3A, VOP3B, VOP3P as CDNA_VOP3P,
|
||||
SOP1 as CDNA_SOP1, SOP2 as CDNA_SOP2, SOPC as CDNA_SOPC, SOPK as CDNA_SOPK, SOPP as CDNA_SOPP, SMEM as CDNA_SMEM, DS as CDNA_DS,
|
||||
FLAT as CDNA_FLAT, VOP1Op as CDNA_VOP1Op, VOP2Op as CDNA_VOP2Op, VOPCOp as CDNA_VOPCOp)
|
||||
|
||||
def _cdna_src(inst, v, neg, abs_=0, n=1):
|
||||
s = _lit(inst, v) if v == 255 else _fmt_src(v, n, cdna=True)
|
||||
if abs_: s = f"|{s}|"
|
||||
return f"neg({s})" if neg and v == 255 else (f"-{s}" if neg else s)
|
||||
|
||||
_CDNA_VOP3_ALIASES = {'v_fmac_f64': 'v_mul_legacy_f32', 'v_dot2c_f32_bf16': 'v_mac_f32'}
|
||||
|
||||
def _disasm_vop3a(inst) -> str:
|
||||
op_val = inst.op.value if hasattr(inst.op, 'value') else inst.op
|
||||
name = inst.op_name.lower() or f'vop3a_op_{op_val}'
|
||||
n = inst.num_srcs() or _num_srcs(inst)
|
||||
cl, om = " clamp" if inst.clmp else "", _omod(inst.omod)
|
||||
orig_name = name
|
||||
name = _CDNA_VOP3_ALIASES.get(name, name)
|
||||
if name != orig_name:
|
||||
s0, s1 = _cdna_src(inst, inst.src0, inst.neg&1, inst.abs&1, 1), _cdna_src(inst, inst.src1, inst.neg&2, inst.abs&2, 1)
|
||||
s2 = ""
|
||||
dst = _vreg(inst.vdst)
|
||||
else:
|
||||
regs = inst.canonical_op_regs
|
||||
dregs, r0, r1, r2 = regs['d'], regs['s0'], regs['s1'], regs['s2']
|
||||
s0, s1, s2 = _cdna_src(inst, inst.src0, inst.neg&1, inst.abs&1, r0), _cdna_src(inst, inst.src1, inst.neg&2, inst.abs&2, r1), _cdna_src(inst, inst.src2, inst.neg&4, inst.abs&4, r2)
|
||||
dst = _vreg(inst.vdst, dregs) if dregs > 1 else _vreg(inst.vdst)
|
||||
if op_val >= 512:
|
||||
return f"{name} {dst}, {s0}, {s1}, {s2}{cl}{om}" if n == 3 else f"{name} {dst}, {s0}, {s1}{cl}{om}"
|
||||
if op_val < 256:
|
||||
sdst = _fmt_sdst(inst.vdst, 2, cdna=True)
|
||||
return f"{name}_e64 {sdst}, {s0}, {s1}{cl}"
|
||||
if 320 <= op_val < 512:
|
||||
if name in ('v_nop', 'v_clrexcp'): return f"{name}_e64"
|
||||
return f"{name}_e64 {dst}, {s0}{cl}{om}"
|
||||
if name == 'v_cndmask_b32':
|
||||
s2 = _fmt_src(inst.src2, 2, cdna=True)
|
||||
return f"{name}_e64 {dst}, {s0}, {s1}, {s2}{cl}{om}"
|
||||
if name in ('v_mul_legacy_f32', 'v_mac_f32'):
|
||||
return f"{name}_e64 {dst}, {s0}, {s1}{cl}{om}"
|
||||
suf = "_e64" if op_val < 512 else ""
|
||||
return f"{name}{suf} {dst}, {s0}, {s1}, {s2}{cl}{om}" if n == 3 else f"{name}{suf} {dst}, {s0}, {s1}{cl}{om}"
|
||||
|
||||
def _disasm_vop3b(inst) -> str:
|
||||
op_val = inst.op.value if hasattr(inst.op, 'value') else inst.op
|
||||
name = inst.op_name.lower() or f'vop3b_op_{op_val}'
|
||||
n = inst.num_srcs() or _num_srcs(inst)
|
||||
regs = inst.canonical_op_regs
|
||||
dregs, r0, r1, r2 = regs['d'], regs['s0'], regs['s1'], regs['s2']
|
||||
s0, s1, s2 = _cdna_src(inst, inst.src0, inst.neg&1, n=r0), _cdna_src(inst, inst.src1, inst.neg&2, n=r1), _cdna_src(inst, inst.src2, inst.neg&4, n=r2)
|
||||
dst = _vreg(inst.vdst, dregs) if dregs > 1 else _vreg(inst.vdst)
|
||||
sdst = _fmt_sdst(inst.sdst, 2, cdna=True)
|
||||
cl, om = " clamp" if inst.clmp else "", _omod(inst.omod)
|
||||
if name in ('v_addc_co_u32', 'v_subb_co_u32', 'v_subbrev_co_u32'):
|
||||
s2 = _fmt_src(inst.src2, 2, cdna=True)
|
||||
return f"{name}_e64 {dst}, {sdst}, {s0}, {s1}, {s2}{cl}{om}"
|
||||
suf = "_e64" if 'co_' in name else ""
|
||||
return f"{name}{suf} {dst}, {sdst}, {s0}, {s1}, {s2}{cl}{om}" if n == 3 else f"{name}{suf} {dst}, {sdst}, {s0}, {s1}{cl}{om}"
|
||||
|
||||
def _disasm_cdna_vop3p(inst) -> str:
|
||||
name, n = inst.op_name.lower(), inst.num_srcs() or 2
|
||||
is_mfma = 'mfma' in name or 'smfmac' in name
|
||||
is_accvgpr = 'accvgpr' in name
|
||||
get_src = lambda v, sc: _lit(inst, v) if v == 255 else _fmt_src(v, sc, cdna=True)
|
||||
|
||||
# Handle accvgpr read/write (accumulator register operations)
|
||||
if is_accvgpr:
|
||||
src0_off = _unwrap(inst.src0)
|
||||
vdst_off = _vi(inst.vdst)
|
||||
if 'read' in name:
|
||||
# v_accvgpr_read_b32 vN, aM - reads from accumulator to VGPR
|
||||
return f"{name}_b32 v{vdst_off}, a{src0_off - 256 if src0_off >= 256 else src0_off}"
|
||||
if 'write' in name:
|
||||
# v_accvgpr_write_b32 aM, src - writes to accumulator from source
|
||||
src = _lit(inst, inst.src0) if src0_off == 255 else (f"v{src0_off - 256}" if src0_off >= 256 else decode_src(src0_off, cdna=True))
|
||||
return f"{name}_b32 a{vdst_off}, {src}"
|
||||
|
||||
# Handle MFMA instructions with accumulator destinations
|
||||
if is_mfma:
|
||||
sc = 2 if 'iu4' in name else 4 if 'iu8' in name or 'i4' in name else 8 if 'f16' in name or 'bf16' in name else 4
|
||||
src0, src1, src2 = get_src(inst.src0, sc), get_src(inst.src1, sc), get_src(inst.src2, 16)
|
||||
dst = _areg(inst.vdst, 16) # MFMA uses accumulator registers
|
||||
opsel_hi = inst.opsel_hi
|
||||
mods = ([_fmt_bits("op_sel", inst.opsel, n)] if inst.opsel else []) + ([_fmt_bits("op_sel_hi", opsel_hi, n)] if opsel_hi != 3 else []) + \
|
||||
([_fmt_bits("neg_lo", inst.neg, n)] if inst.neg else []) + ([_fmt_bits("neg_hi", inst.neg_hi, n)] if inst.neg_hi else []) + (["clamp"] if inst.clmp else [])
|
||||
return f"{name} {dst}, {src0}, {src1}, {src2}{' ' + ' '.join(mods) if mods else ''}"
|
||||
|
||||
# Standard VOP3P instructions
|
||||
src0, src1, src2, dst = get_src(inst.src0, 1), get_src(inst.src1, 1), get_src(inst.src2, 1), _vreg(inst.vdst)
|
||||
opsel_hi = inst.opsel_hi # CDNA VOP3P only has 2 bits for opsel_hi (no opsel_hi2)
|
||||
opsel_hi_default = 3 # CDNA default is 0b11 (2 bits), not 0b111 like RDNA
|
||||
mods = ([_fmt_bits("op_sel", inst.opsel, n)] if inst.opsel else []) + ([_fmt_bits("op_sel_hi", opsel_hi, n)] if opsel_hi != opsel_hi_default else []) + \
|
||||
([_fmt_bits("neg_lo", inst.neg, n)] if inst.neg else []) + ([_fmt_bits("neg_hi", inst.neg_hi, n)] if inst.neg_hi else []) + (["clamp"] if inst.clmp else [])
|
||||
return f"{name} {dst}, {src0}, {src1}, {src2}{' ' + ' '.join(mods) if mods else ''}" if n == 3 else f"{name} {dst}, {src0}, {src1}{' ' + ' '.join(mods) if mods else ''}"
|
||||
|
||||
DISASM_HANDLERS.update({CDNA_VOP1: _disasm_vop1, CDNA_VOP2: _disasm_vop2, CDNA_VOPC: _disasm_vopc,
|
||||
CDNA_SOP1: _disasm_sop1, CDNA_SOP2: _disasm_sop2, CDNA_SOPC: _disasm_sopc, CDNA_SOPK: _disasm_sopk, CDNA_SOPP: _disasm_sopp,
|
||||
CDNA_SMEM: _disasm_smem, CDNA_DS: _disasm_ds, CDNA_FLAT: _disasm_flat,
|
||||
VOP3A: _disasm_vop3a, VOP3B: _disasm_vop3b, CDNA_VOP3P: _disasm_cdna_vop3p})
|
||||
except ImportError:
|
||||
pass
|
||||
@@ -1,479 +0,0 @@
|
||||
# RDNA3 emulator - executes compiled pseudocode from AMD ISA PDF
|
||||
# mypy: ignore-errors
|
||||
from __future__ import annotations
|
||||
import ctypes, functools
|
||||
from enum import IntEnum
|
||||
from tinygrad.runtime.autogen import hsa
|
||||
from extra.assembly.amd.dsl import Inst, NULL, SCC, VCC_LO, VCC_HI, EXEC_LO, EXEC_HI, v, s
|
||||
from extra.assembly.amd.pcode import _f32, _i32, _sext, _f16, _i16, _f64, _i64
|
||||
from extra.assembly.amd.decode import decode_inst
|
||||
from extra.assembly.amd.pcode import compile_pseudocode
|
||||
from extra.assembly.amd.autogen.rdna3.str_pcode import PCODE
|
||||
from extra.assembly.amd.autogen.rdna3.ins import (SOP1, SOP2, SOPC, SOPK, SOPP, SMEM, VOP1, VOP2, VOP3, VOP3SD, VOP3P, VOPC, DS, FLAT, VOPD,
|
||||
SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, SMEMOp, VOP1Op, VOP2Op, VOP3Op, VOP3SDOp, VOP3POp, VOPCOp, DSOp, FLATOp, GLOBALOp, SCRATCHOp, VOPDOp)
|
||||
|
||||
# Constants and helpers defined locally (not imported from dsl.py)
|
||||
MASK32, MASK64 = 0xFFFFFFFF, 0xFFFFFFFFFFFFFFFF
|
||||
FLOAT_ENC = {0.5: 240, -0.5: 241, 1.0: 242, -1.0: 243, 2.0: 244, -2.0: 245, 4.0: 246, -4.0: 247}
|
||||
|
||||
class SGPRArray:
|
||||
"""SGPR array indexed by Reg or int."""
|
||||
__slots__ = ('_data',)
|
||||
def __init__(self, size: int): self._data = [0] * size
|
||||
def __getitem__(self, key): return self._data[getattr(key, 'offset', key)]
|
||||
def __setitem__(self, key, val): self._data[getattr(key, 'offset', key)] = val
|
||||
def __len__(self): return len(self._data)
|
||||
def __iter__(self): return iter(self._data)
|
||||
|
||||
class VGPRLane:
|
||||
"""Single lane of VGPRs indexed by Reg (offset 256-511) or int (0-255)."""
|
||||
__slots__ = ('_data',)
|
||||
def __init__(self, size: int): self._data = [0] * size
|
||||
def __getitem__(self, key):
|
||||
i = getattr(key, 'offset', key)
|
||||
return self._data[i - 256 if i >= 256 else i]
|
||||
def __setitem__(self, key, val):
|
||||
i = getattr(key, 'offset', key)
|
||||
self._data[i - 256 if i >= 256 else i] = val
|
||||
def __len__(self): return len(self._data)
|
||||
def __iter__(self): return iter(self._data)
|
||||
|
||||
WAVE_SIZE, SGPR_COUNT, VGPR_COUNT = 32, 128, 256
|
||||
|
||||
# Inline constants for src operands 128-254. Build tables for f32, f16, and f64 formats.
|
||||
_FLOAT_CONSTS = {v: k for k, v in FLOAT_ENC.items()} | {248: 0.15915494309189535} # INV_2PI
|
||||
def _build_inline_consts(mask, to_bits):
|
||||
tbl = list(range(65)) + [((-i) & mask) for i in range(1, 17)] + [0] * (127 - 81)
|
||||
for k, v in _FLOAT_CONSTS.items(): tbl[k - 128] = to_bits(v)
|
||||
return tbl
|
||||
_INLINE_CONSTS = _build_inline_consts(MASK32, _i32)
|
||||
_INLINE_CONSTS_F16 = _build_inline_consts(0xffff, _i16)
|
||||
_INLINE_CONSTS_F64 = _build_inline_consts(MASK64, _i64)
|
||||
|
||||
# Helper: extract/write 16-bit half from/to 32-bit value
|
||||
def _src16(raw: int, is_hi: bool) -> int: return ((raw >> 16) & 0xffff) if is_hi else (raw & 0xffff)
|
||||
def _dst16(cur: int, val: int, is_hi: bool) -> int: return (cur & 0x0000ffff) | ((val & 0xffff) << 16) if is_hi else (cur & 0xffff0000) | (val & 0xffff)
|
||||
def _vgpr_hi(src) -> bool: return src.offset >= 256 and ((src.offset - 256) & 0x80) != 0
|
||||
def _vgpr_masked(src): return v[(src.offset - 256) & 0x7f] if src.offset >= 256 else src
|
||||
|
||||
# VOP3 source modifier: apply abs/neg to value
|
||||
def _mod_src(val: int, idx: int, neg: int, abs_: int, is64: bool = False) -> int:
|
||||
to_f, to_i = (_f64, _i64) if is64 else (_f32, _i32)
|
||||
if (abs_ >> idx) & 1: val = to_i(abs(to_f(val)))
|
||||
if (neg >> idx) & 1: val = to_i(-to_f(val))
|
||||
return val
|
||||
|
||||
# Read source operand with VOP3 modifiers
|
||||
def _read_src(st, inst, src, idx: int, lane: int, neg: int, abs_: int, opsel: int) -> int:
|
||||
if src is None: return 0
|
||||
src_off = src.offset
|
||||
src_bits = inst.canonical_op_bits[f's{idx}']
|
||||
literal, is_src_64, is_src_16 = inst._literal, src_bits == 64, src_bits == 16
|
||||
if is_src_64: return _mod_src(st.rsrc64(src, lane, literal), idx, neg, abs_, is64=True)
|
||||
if isinstance(inst, VOP3P):
|
||||
opsel_hi = inst.opsel_hi | (inst.opsel_hi2 << 2)
|
||||
if 'FMA_MIX' in inst.op_name:
|
||||
raw = st.rsrc(src, lane, literal)
|
||||
sign_bit = (15 if not (opsel & (1 << idx)) else 31) if (opsel_hi >> idx) & 1 else 31
|
||||
if inst.neg_hi & (1 << idx): raw &= ~(1 << sign_bit)
|
||||
if neg & (1 << idx): raw ^= (1 << sign_bit)
|
||||
return raw
|
||||
raw = st.rsrc_f16(src, lane, literal)
|
||||
hi = _src16(raw, opsel_hi & (1 << idx)) ^ (0x8000 if inst.neg_hi & (1 << idx) else 0)
|
||||
lo = _src16(raw, opsel & (1 << idx)) ^ (0x8000 if neg & (1 << idx) else 0)
|
||||
return (hi << 16) | lo
|
||||
if is_src_16 and isinstance(inst, VOP3):
|
||||
raw = st.rsrc_f16(src, lane, literal) if 128 <= src_off < 255 else st.rsrc(src, lane, literal)
|
||||
val = _src16(raw, bool(opsel & (1 << idx)))
|
||||
if abs_ & (1 << idx): val &= 0x7fff
|
||||
if neg & (1 << idx): val ^= 0x8000
|
||||
return val
|
||||
if is_src_16 and isinstance(inst, (VOP1, VOP2, VOPC)):
|
||||
if src_off >= 256: return _src16(_mod_src(st.rsrc(_vgpr_masked(src), lane, literal), idx, neg, abs_), _vgpr_hi(src))
|
||||
return _mod_src(st.rsrc_f16(src, lane, literal), idx, neg, abs_) & 0xffff
|
||||
return _mod_src(st.rsrc(src, lane, literal), idx, neg, abs_)
|
||||
|
||||
# Helper: get number of dwords from memory op name
|
||||
def _op_ndwords(name: str) -> int:
|
||||
if '_B128' in name: return 4
|
||||
if '_B96' in name: return 3
|
||||
if any(s in name for s in ('_B64', '_U64', '_I64', '_F64')): return 2
|
||||
return 1
|
||||
|
||||
# Helper: build multi-dword int from consecutive VGPRs
|
||||
def _vgpr_read(V: VGPRLane, reg, ndwords: int) -> int:
|
||||
return sum(V[reg + i] << (32 * i) for i in range(ndwords))
|
||||
|
||||
# Helper: write multi-dword value to consecutive VGPRs
|
||||
def _vgpr_write(V: VGPRLane, reg, val: int, ndwords: int):
|
||||
for i in range(ndwords): V[reg + i] = (val >> (32 * i)) & MASK32
|
||||
|
||||
# Memory access
|
||||
_valid_mem_ranges: list[tuple[int, int]] = []
|
||||
def set_valid_mem_ranges(ranges: set[tuple[int, int]]) -> None: _valid_mem_ranges.clear(); _valid_mem_ranges.extend(ranges)
|
||||
def _mem_valid(addr: int, size: int) -> bool:
|
||||
return not _valid_mem_ranges or any(s <= addr and addr + size <= s + z for s, z in _valid_mem_ranges)
|
||||
def _ctypes_at(addr: int, size: int): return (ctypes.c_uint8 if size == 1 else ctypes.c_uint16 if size == 2 else ctypes.c_uint64 if size == 8 else ctypes.c_uint32).from_address(addr)
|
||||
def mem_read(addr: int, size: int) -> int: return _ctypes_at(addr, size).value if _mem_valid(addr, size) else 0
|
||||
def mem_write(addr: int, size: int, val: int) -> None:
|
||||
if _mem_valid(addr, size): _ctypes_at(addr, size).value = val
|
||||
|
||||
def _make_mem_accessor(read_fn, write_fn):
|
||||
"""Create a memory accessor class with the given read/write functions."""
|
||||
class _MemAccessor:
|
||||
__slots__ = ('_addr',)
|
||||
def __init__(self, addr: int): self._addr = int(addr)
|
||||
u8 = property(lambda s: read_fn(s._addr, 1), lambda s, v: write_fn(s._addr, 1, int(v)))
|
||||
u16 = property(lambda s: read_fn(s._addr, 2), lambda s, v: write_fn(s._addr, 2, int(v)))
|
||||
u32 = property(lambda s: read_fn(s._addr, 4), lambda s, v: write_fn(s._addr, 4, int(v)))
|
||||
u64 = property(lambda s: read_fn(s._addr, 8), lambda s, v: write_fn(s._addr, 8, int(v)))
|
||||
i8 = property(lambda s: _sext(read_fn(s._addr, 1), 8), lambda s, v: write_fn(s._addr, 1, int(v)))
|
||||
i16 = property(lambda s: _sext(read_fn(s._addr, 2), 16), lambda s, v: write_fn(s._addr, 2, int(v)))
|
||||
i32 = property(lambda s: _sext(read_fn(s._addr, 4), 32), lambda s, v: write_fn(s._addr, 4, int(v)))
|
||||
i64 = property(lambda s: _sext(read_fn(s._addr, 8), 64), lambda s, v: write_fn(s._addr, 8, int(v)))
|
||||
b8, b16, b32, b64 = u8, u16, u32, u64
|
||||
return _MemAccessor
|
||||
|
||||
_GlobalMemAccessor = _make_mem_accessor(mem_read, mem_write)
|
||||
|
||||
class _GlobalMem:
|
||||
"""Global memory wrapper that supports MEM[addr].u32 style access."""
|
||||
def __getitem__(self, addr) -> _GlobalMemAccessor: return _GlobalMemAccessor(addr)
|
||||
GlobalMem = _GlobalMem()
|
||||
|
||||
class LDSMem:
|
||||
"""LDS memory wrapper that supports MEM[addr].u32 style access."""
|
||||
__slots__ = ('_lds',)
|
||||
def __init__(self, lds: bytearray): self._lds = lds
|
||||
def _read(self, addr: int, size: int) -> int:
|
||||
addr = addr & 0xffff
|
||||
return int.from_bytes(self._lds[addr:addr+size], 'little') if addr + size <= len(self._lds) else 0
|
||||
def _write(self, addr: int, size: int, val: int):
|
||||
addr = addr & 0xffff
|
||||
if addr + size <= len(self._lds): self._lds[addr:addr+size] = (int(val) & ((1 << (size*8)) - 1)).to_bytes(size, 'little')
|
||||
def __getitem__(self, addr): return _make_mem_accessor(self._read, self._write)(addr)
|
||||
|
||||
# SMEM dst register count (for writing result back to SGPRs)
|
||||
SMEM_DST_COUNT = {SMEMOp.S_LOAD_B32: 1, SMEMOp.S_LOAD_B64: 2, SMEMOp.S_LOAD_B128: 4, SMEMOp.S_LOAD_B256: 8, SMEMOp.S_LOAD_B512: 16}
|
||||
|
||||
# VOPD op -> VOP3 op mapping (VOPD is dual-issue of VOP1/VOP2 ops, use VOP3 enums for pseudocode lookup)
|
||||
_VOPD_TO_VOP = {
|
||||
VOPDOp.V_DUAL_FMAC_F32: VOP3Op.V_FMAC_F32_E64, VOPDOp.V_DUAL_FMAAK_F32: VOP2Op.V_FMAAK_F32_E32, VOPDOp.V_DUAL_FMAMK_F32: VOP2Op.V_FMAMK_F32_E32,
|
||||
VOPDOp.V_DUAL_MUL_F32: VOP3Op.V_MUL_F32_E64, VOPDOp.V_DUAL_ADD_F32: VOP3Op.V_ADD_F32_E64, VOPDOp.V_DUAL_SUB_F32: VOP3Op.V_SUB_F32_E64,
|
||||
VOPDOp.V_DUAL_SUBREV_F32: VOP3Op.V_SUBREV_F32_E64, VOPDOp.V_DUAL_MUL_DX9_ZERO_F32: VOP3Op.V_MUL_DX9_ZERO_F32_E64,
|
||||
VOPDOp.V_DUAL_MOV_B32: VOP3Op.V_MOV_B32_E64, VOPDOp.V_DUAL_CNDMASK_B32: VOP3Op.V_CNDMASK_B32_E64,
|
||||
VOPDOp.V_DUAL_MAX_F32: VOP3Op.V_MAX_F32_E64, VOPDOp.V_DUAL_MIN_F32: VOP3Op.V_MIN_F32_E64,
|
||||
VOPDOp.V_DUAL_ADD_NC_U32: VOP3Op.V_ADD_NC_U32_E64, VOPDOp.V_DUAL_LSHLREV_B32: VOP3Op.V_LSHLREV_B32_E64, VOPDOp.V_DUAL_AND_B32: VOP3Op.V_AND_B32_E64,
|
||||
}
|
||||
|
||||
|
||||
class WaveState:
|
||||
__slots__ = ('sgpr', 'vgpr', 'scc', 'pc', '_pend_sgpr', 'lds', 'n_lanes')
|
||||
def __init__(self, lds: LDSMem | None = None, n_lanes: int = WAVE_SIZE):
|
||||
self.sgpr, self.vgpr = SGPRArray(SGPR_COUNT), [VGPRLane(VGPR_COUNT) for _ in range(WAVE_SIZE)]
|
||||
self.sgpr[EXEC_LO], self.scc, self.pc, self._pend_sgpr, self.lds, self.n_lanes = 0xffffffff, 0, 0, {}, lds, n_lanes
|
||||
|
||||
@property
|
||||
def vcc(self) -> int: return self.sgpr[VCC_LO] | (self.sgpr[VCC_HI] << 32)
|
||||
@vcc.setter
|
||||
def vcc(self, v: int): self.sgpr[VCC_LO], self.sgpr[VCC_HI] = v & MASK32, (v >> 32) & MASK32
|
||||
@property
|
||||
def exec_mask(self) -> int: return self.sgpr[EXEC_LO] | (self.sgpr[EXEC_HI] << 32)
|
||||
@exec_mask.setter
|
||||
def exec_mask(self, v: int): self.sgpr[EXEC_LO], self.sgpr[EXEC_HI] = v & MASK32, (v >> 32) & MASK32
|
||||
|
||||
def rsgpr(self, reg) -> int:
|
||||
if reg == NULL: return 0
|
||||
if reg == SCC: return self.scc
|
||||
return self.sgpr[reg]
|
||||
def wsgpr(self, reg, v: int):
|
||||
if reg != NULL: self.sgpr[reg] = v & MASK32
|
||||
def rsgpr64(self, reg) -> int:
|
||||
off = reg.offset
|
||||
return self.sgpr._data[off] | (self.sgpr._data[off + 1] << 32)
|
||||
def wsgpr64(self, reg, v: int):
|
||||
off = reg.offset
|
||||
self.sgpr._data[off] = v & MASK32; self.sgpr._data[off + 1] = (v >> 32) & MASK32
|
||||
|
||||
def _rsrc_base(self, reg, lane: int, consts, literal: int):
|
||||
off = reg.offset
|
||||
if off < SGPR_COUNT: return self.sgpr._data[off]
|
||||
if off == SCC.offset: return self.scc
|
||||
if off < 255: return consts[off - 128]
|
||||
if off == 255: return literal
|
||||
return self.vgpr[lane]._data[off - 256] if off <= 511 else 0
|
||||
def rsrc(self, reg, lane: int, literal: int = 0) -> int: return self._rsrc_base(reg, lane, _INLINE_CONSTS, literal)
|
||||
def rsrc_f16(self, reg, lane: int, literal: int = 0) -> int: return self._rsrc_base(reg, lane, _INLINE_CONSTS_F16, literal)
|
||||
def rsrc64(self, reg, lane: int, literal: int = 0) -> int:
|
||||
off = reg.offset
|
||||
if 128 <= off < 255: return _INLINE_CONSTS_F64[off - 128]
|
||||
if off == 255: return literal << 32 # 32-bit literal forms upper 32 bits of 64-bit value
|
||||
return self.rsrc(reg, lane, literal) | ((self.rsrc(reg + 1, lane, literal) if off < VCC_LO.offset or 256 <= off <= 511 else 0) << 32)
|
||||
|
||||
def pend_sgpr_lane(self, reg, lane: int, val: int):
|
||||
if reg not in self._pend_sgpr: self._pend_sgpr[reg] = 0
|
||||
if val: self._pend_sgpr[reg] |= (1 << lane)
|
||||
def commit_pends(self):
|
||||
for reg, val in self._pend_sgpr.items(): self.sgpr[reg] = val
|
||||
self._pend_sgpr.clear()
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# EXECUTION - All ops use pseudocode from PDF
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def exec_scalar(st: WaveState, inst: Inst):
|
||||
"""Execute scalar instruction. Returns 0 to continue execution."""
|
||||
# Get op enum and lookup compiled function
|
||||
if isinstance(inst, SMEM): ssrc0, sdst = None, None
|
||||
elif isinstance(inst, SOP1): ssrc0, sdst = inst.ssrc0, inst.sdst
|
||||
elif isinstance(inst, SOP2): ssrc0, sdst = inst.ssrc0, inst.sdst
|
||||
elif isinstance(inst, SOPC): ssrc0, sdst = inst.ssrc0, None
|
||||
elif isinstance(inst, SOPK): ssrc0, sdst = inst.sdst, inst.sdst # sdst is both src and dst
|
||||
elif isinstance(inst, SOPP): ssrc0, sdst = None, None
|
||||
else: raise NotImplementedError(f"Unknown scalar type {type(inst)}")
|
||||
|
||||
# SMEM: memory loads
|
||||
if isinstance(inst, SMEM):
|
||||
addr = st.rsgpr64(inst.sbase) + _sext(inst.offset, 21)
|
||||
if inst.soffset != NULL: addr += st.rsrc(inst.soffset, 0, inst._literal)
|
||||
result = inst._fn(GlobalMem, addr & MASK64)
|
||||
if 'SDATA' in result:
|
||||
sdata = result['SDATA']
|
||||
for i in range(SMEM_DST_COUNT.get(inst.op, 1)): st.wsgpr(inst.sdata + i, (sdata >> (i * 32)) & MASK32)
|
||||
st.pc += inst._words
|
||||
return 0
|
||||
|
||||
# Build context - use canonical_op_bits to determine operand sizes
|
||||
literal = inst._literal
|
||||
s0 = st.rsrc64(ssrc0, 0, literal) if inst.canonical_op_bits['s0'] == 64 else (st.rsrc(ssrc0, 0, literal) if not isinstance(inst, (SOPK, SOPP)) else (st.rsgpr(inst.sdst) if isinstance(inst, SOPK) else 0))
|
||||
s1 = st.rsrc64(inst.ssrc1, 0, literal) if inst.canonical_op_bits['s1'] == 64 else (st.rsrc(inst.ssrc1, 0, literal) if isinstance(inst, (SOP2, SOPC)) else inst.simm16 if isinstance(inst, SOPK) else 0)
|
||||
d0 = st.rsgpr64(sdst) if inst.canonical_op_bits['d'] == 64 and sdst is not None else (st.rsgpr(sdst) if sdst is not None else 0)
|
||||
literal = inst.simm16 if isinstance(inst, (SOPK, SOPP)) else inst._literal
|
||||
|
||||
# Call compiled function with int parameters
|
||||
result = inst._fn(s0, s1, 0, d0, st.scc, st.vcc & MASK32, 0, st.exec_mask & MASK32, literal, None, pc=st.pc * 4)
|
||||
|
||||
# Apply results (already int values)
|
||||
if sdst is not None and 'D0' in result:
|
||||
(st.wsgpr64 if inst.canonical_op_bits['d'] == 64 else st.wsgpr)(sdst, result['D0'])
|
||||
if 'SCC' in result: st.scc = result['SCC'] & 1
|
||||
if 'EXEC' in result: st.exec_mask = result['EXEC']
|
||||
if 'PC' in result:
|
||||
# Convert absolute byte address to word offset
|
||||
pc_val = result['PC']
|
||||
new_pc = pc_val if pc_val < 0x8000000000000000 else pc_val - 0x10000000000000000
|
||||
st.pc = new_pc // 4
|
||||
else:
|
||||
st.pc += inst._words
|
||||
return 0
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# VECTOR INSTRUCTIONS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def exec_vopd(st: WaveState, inst, V: VGPRLane, lane: int) -> None:
|
||||
"""VOPD: dual-issue, execute two ops simultaneously (read all inputs before writes)."""
|
||||
literal, vdstx = inst._literal, inst.vdstx
|
||||
vdsty = v[(inst.vdsty << 1) | ((inst.vdstx.offset & 1) ^ 1)] # vdsty is raw int from VDSTYField.decode
|
||||
sx0, sx1, dx, sy0, sy1, dy = st.rsrc(inst.srcx0, lane, literal), V[inst.vsrcx1], V[vdstx], st.rsrc(inst.srcy0, lane, literal), V[inst.vsrcy1], V[vdsty]
|
||||
V[vdstx] = inst._fnx(sx0, sx1, 0, dx, st.scc, st.vcc, lane, st.exec_mask, literal, None)['D0']
|
||||
V[vdsty] = inst._fny(sy0, sy1, 0, dy, st.scc, st.vcc, lane, st.exec_mask, literal, None)['D0']
|
||||
|
||||
def exec_flat(st: WaveState, inst, V: VGPRLane, lane: int) -> None:
|
||||
"""FLAT/GLOBAL/SCRATCH memory ops."""
|
||||
ndwords = _op_ndwords(inst.op_name)
|
||||
addr = V[inst.addr] | (V[inst.addr + 1] << 32)
|
||||
ADDR = (st.rsgpr64(inst.saddr) + V[inst.addr] + _sext(inst.offset, 13)) & MASK64 if inst.saddr != NULL else (addr + _sext(inst.offset, 13)) & MASK64
|
||||
vdata_src = inst.vdst if 'LOAD' in inst.op_name else inst.data
|
||||
result = inst._fn(GlobalMem, ADDR, _vgpr_read(V, vdata_src, ndwords), V[inst.vdst])
|
||||
if 'VDATA' in result: _vgpr_write(V, inst.vdst, result['VDATA'], ndwords)
|
||||
if 'RETURN_DATA' in result: _vgpr_write(V, inst.vdst, result['RETURN_DATA'], ndwords)
|
||||
|
||||
def exec_ds(st: WaveState, inst, V: VGPRLane, lane: int) -> None:
|
||||
"""DS (LDS) memory ops."""
|
||||
ndwords = _op_ndwords(inst.op_name)
|
||||
data0, data1 = _vgpr_read(V, inst.data0, ndwords), _vgpr_read(V, inst.data1, ndwords) if inst.data1 is not None else 0
|
||||
result = inst._fn(st.lds, V[inst.addr], data0, data1, inst.offset0, inst.offset1)
|
||||
if 'RETURN_DATA' in result and ('_RTN' in inst.op_name or '_LOAD' in inst.op_name):
|
||||
_vgpr_write(V, inst.vdst, result['RETURN_DATA'], ndwords * 2 if '_2ADDR_' in inst.op_name else ndwords)
|
||||
|
||||
def exec_vop(st: WaveState, inst: Inst, V: VGPRLane, lane: int) -> None:
|
||||
"""VOP1/VOP2/VOP3/VOP3SD/VOP3P/VOPC: standard ALU ops."""
|
||||
is_dst_16 = inst.canonical_op_bits['d'] == 16
|
||||
if isinstance(inst, VOP3P):
|
||||
src0, src1, src2, vdst, dst_hi = inst.src0, inst.src1, inst.src2, inst.vdst, False
|
||||
neg, abs_, opsel = inst.neg, 0, inst.opsel
|
||||
elif isinstance(inst, VOP1):
|
||||
src0, src1, src2, vdst = inst.src0, None, None, inst.vdst
|
||||
neg, abs_, opsel, dst_hi = 0, 0, 0, (inst.vdst.offset & 0x80) != 0 and is_dst_16
|
||||
if is_dst_16: vdst = v[inst.vdst.offset & 0x7f]
|
||||
elif isinstance(inst, VOP2):
|
||||
src0, src1, src2, vdst = inst.src0, inst.vsrc1, None, inst.vdst
|
||||
neg, abs_, opsel, dst_hi = 0, 0, 0, (inst.vdst.offset & 0x80) != 0 and is_dst_16
|
||||
if is_dst_16: vdst = v[inst.vdst.offset & 0x7f]
|
||||
elif isinstance(inst, (VOP3, VOP3SD)):
|
||||
src0, src1, src2, vdst = inst.src0, inst.src1, (None if isinstance(inst, VOP3) and inst.op.value < 256 else inst.src2), inst.vdst
|
||||
neg, abs_, opsel, dst_hi = (inst.neg, inst.abs, inst.opsel, False) if isinstance(inst, VOP3) else (0, 0, 0, False)
|
||||
elif isinstance(inst, VOPC):
|
||||
src0, src1, src2, vdst, neg, abs_, opsel, dst_hi = inst.src0, inst.vsrc1, None, VCC_LO, 0, 0, 0, False
|
||||
else:
|
||||
raise NotImplementedError(f"exec_vop: unhandled instruction type {type(inst).__name__}")
|
||||
|
||||
s0 = _read_src(st, inst, src0, 0, lane, neg, abs_, opsel)
|
||||
s1 = _read_src(st, inst, src1, 1, lane, neg, abs_, opsel)
|
||||
s2 = _read_src(st, inst, src2, 2, lane, neg, abs_, opsel)
|
||||
if isinstance(inst, VOP2) and is_dst_16: d0 = _src16(V[vdst], dst_hi)
|
||||
elif inst.canonical_op_bits['d'] == 64: d0 = V[vdst] | (V[vdst + 1] << 32)
|
||||
else: d0 = V[vdst]
|
||||
|
||||
if isinstance(inst, VOP3SD) and 'CO_CI' in inst.op_name: vcc_for_fn = st.rsgpr64(inst.src2)
|
||||
elif isinstance(inst, VOP3) and inst.op in (VOP3Op.V_CNDMASK_B32_E64, VOP3Op.V_CNDMASK_B16) and src2 is not None and src2.offset < 256: vcc_for_fn = st.rsgpr64(src2)
|
||||
else: vcc_for_fn = st.vcc
|
||||
src0_off = src0.offset if src0 is not None else 0
|
||||
src0_idx = (src0_off - 256) if src0_off >= 256 else src0_off
|
||||
vdst_off = vdst.offset
|
||||
extra_kwargs = {'opsel': opsel, 'opsel_hi': inst.opsel_hi | (inst.opsel_hi2 << 2)} if isinstance(inst, VOP3P) and 'FMA_MIX' in inst.op_name else {}
|
||||
result = inst._fn(s0, s1, s2, d0, st.scc, vcc_for_fn, lane, st.exec_mask, inst._literal, st.vgpr, src0_idx, vdst_off, **extra_kwargs)
|
||||
|
||||
# Check if this is a VOPC instruction (either standalone VOPC or VOP3 with VOPC opcode)
|
||||
is_vopc = isinstance(inst.op, VOPCOp) or (isinstance(inst, VOP3) and inst.op.value < 256)
|
||||
if 'VCC' in result:
|
||||
if isinstance(inst, VOP3SD): st.pend_sgpr_lane(inst.sdst, lane, (result['VCC'] >> lane) & 1)
|
||||
elif isinstance(inst, VOP2) and 'CO_CI' in inst.op_name: st.pend_sgpr_lane(VCC_LO, lane, (result['VCC'] >> lane) & 1)
|
||||
elif is_vopc: st.pend_sgpr_lane(vdst, lane, (result['VCC'] >> lane) & 1) # vdst is VCC_LO for VOPC
|
||||
else: st.pend_sgpr_lane(VCC_LO, lane, (result['VCC'] >> lane) & 1)
|
||||
if 'EXEC' in result:
|
||||
st.pend_sgpr_lane(EXEC_LO, lane, (result['EXEC'] >> lane) & 1)
|
||||
elif is_vopc:
|
||||
st.pend_sgpr_lane(vdst, lane, (result['D0'] >> lane) & 1)
|
||||
if not is_vopc:
|
||||
d0_val = result['D0']
|
||||
if inst.canonical_op_bits['d'] == 64: V[vdst], V[vdst + 1] = d0_val & MASK32, (d0_val >> 32) & MASK32
|
||||
elif not isinstance(inst, VOP3P) and is_dst_16: V[vdst] = _dst16(V[vdst], d0_val, bool(opsel & 8) if isinstance(inst, VOP3) else dst_hi)
|
||||
else: V[vdst] = d0_val & MASK32
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# WMMA (Wave Matrix Multiply-Accumulate)
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def exec_wmma(st: WaveState, inst, op: VOP3POp) -> None:
|
||||
"""Execute WMMA instruction - 16x16x16 matrix multiply across the wave."""
|
||||
src0, src1, src2, vdst = inst.src0.offset, inst.src1.offset, inst.src2.offset, inst.vdst.offset
|
||||
# Read 16x16 f16 matrix from 16 lanes × 8 VGPRs (2 f16 per VGPR)
|
||||
def read_f16_mat(src):
|
||||
return [f for l in range(16) for r in range(8) for v in [st.vgpr[l][src-256+r] if src >= 256 else st.rsgpr(src+r)] for f in [_f16(v&0xffff), _f16((v>>16)&0xffff)]]
|
||||
mat_a, mat_b = read_f16_mat(src0), read_f16_mat(src1)
|
||||
# Read matrix C (16x16 f32) from lanes 0-31, VGPRs src2 to src2+7
|
||||
mat_c = [_f32(st.vgpr[i % 32][src2 - 256 + i // 32] if src2 >= 256 else st.rsgpr(src2 + i // 32)) for i in range(256)]
|
||||
# Compute D = A × B + C (16x16 matrix multiply)
|
||||
mat_d = [sum(mat_a[row*16+k] * mat_b[col*16+k] for k in range(16)) + mat_c[row*16+col] for row in range(16) for col in range(16)]
|
||||
# Write result - f16 packed or f32
|
||||
if op == VOP3POp.V_WMMA_F16_16X16X16_F16:
|
||||
for i in range(0, 256, 2):
|
||||
st.vgpr[(i//2) % 32][vdst - 256 + (i//2)//32] = ((_i16(mat_d[i+1]) & 0xffff) << 16) | (_i16(mat_d[i]) & 0xffff)
|
||||
else:
|
||||
for i in range(256): st.vgpr[i % 32][vdst - 256 + i//32] = _i32(mat_d[i])
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PROGRAM DECODE
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
# Wave-level dispatch functions: (st, inst) -> return_code (0 = continue, -1 = end, -2 = barrier)
|
||||
def dispatch_endpgm(st, inst): return -1
|
||||
def dispatch_barrier(st, inst): st.pc += inst._words; return -2
|
||||
def dispatch_nop(st, inst): st.pc += inst._words; return 0
|
||||
def dispatch_wmma(st, inst): exec_wmma(st, inst, inst.op); st.pc += inst._words; return 0
|
||||
def dispatch_writelane(st, inst): st.vgpr[st.rsrc(inst.src1, 0, inst._literal) & 0x1f][inst.vdst.offset - 256] = st.rsrc(inst.src0, 0, inst._literal) & MASK32; st.pc += inst._words; return 0
|
||||
def dispatch_readlane(st, inst):
|
||||
src0_off = inst.src0.offset
|
||||
src0_idx = (src0_off - 256) if src0_off >= 256 else src0_off
|
||||
s1 = st.rsrc(inst.src1, 0, inst._literal) if getattr(inst, 'src1', None) is not None else 0
|
||||
result = inst._fn(0, s1, 0, 0, st.scc, st.vcc, 0, st.exec_mask, inst._literal, st.vgpr, src0_idx, inst.vdst.offset)
|
||||
st.wsgpr(inst.vdst.offset, result['D0'])
|
||||
st.pc += inst._words; return 0
|
||||
|
||||
# Per-lane dispatch wrapper: wraps per-lane exec functions into wave-level dispatch
|
||||
@functools.cache
|
||||
def dispatch_lane(exec_fn):
|
||||
def dispatch(st, inst):
|
||||
exec_mask, vgpr, n_lanes = st.exec_mask, st.vgpr, st.n_lanes
|
||||
for lane in range(n_lanes):
|
||||
if exec_mask >> lane & 1: exec_fn(st, inst, vgpr[lane], lane)
|
||||
st.commit_pends()
|
||||
st.pc += inst._words
|
||||
return 0
|
||||
return dispatch
|
||||
|
||||
def decode_program(data: bytes) -> dict[int, Inst]:
|
||||
result: dict[int, Inst] = {}
|
||||
i = 0
|
||||
while i < len(data):
|
||||
inst = decode_inst(data[i:])
|
||||
inst._words = inst.size() // 4
|
||||
|
||||
# Determine dispatch function and pcode function
|
||||
if isinstance(inst, SOPP) and inst.op == SOPPOp.S_CODE_END: break
|
||||
elif isinstance(inst, SOPP) and inst.op == SOPPOp.S_ENDPGM: inst._dispatch = dispatch_endpgm
|
||||
elif isinstance(inst, SOPP) and inst.op == SOPPOp.S_BARRIER: inst._dispatch = dispatch_barrier
|
||||
elif isinstance(inst, SOPP) and inst.op in (SOPPOp.S_CLAUSE, SOPPOp.S_WAITCNT, SOPPOp.S_WAITCNT_DEPCTR, SOPPOp.S_SENDMSG, SOPPOp.S_SET_INST_PREFETCH_DISTANCE, SOPPOp.S_DELAY_ALU): inst._dispatch = dispatch_nop
|
||||
elif isinstance(inst, (SOP1, SOP2, SOPC, SOPK, SOPP, SMEM)): inst._dispatch = exec_scalar
|
||||
elif isinstance(inst, VOP1) and inst.op == VOP1Op.V_NOP_E32: inst._dispatch = dispatch_nop
|
||||
elif isinstance(inst, VOP3P) and 'WMMA' in inst.op_name: inst._dispatch = dispatch_wmma
|
||||
elif isinstance(inst, VOP3) and inst.op == VOP3Op.V_WRITELANE_B32: inst._dispatch = dispatch_writelane
|
||||
elif isinstance(inst, (VOP1, VOP3)) and inst.op in (VOP1Op.V_READFIRSTLANE_B32_E32, VOP3Op.V_READFIRSTLANE_B32, VOP3Op.V_READLANE_B32): inst._dispatch = dispatch_readlane
|
||||
elif isinstance(inst, VOPD): inst._dispatch = dispatch_lane(exec_vopd)
|
||||
elif isinstance(inst, FLAT): inst._dispatch = dispatch_lane(exec_flat)
|
||||
elif isinstance(inst, DS): inst._dispatch = dispatch_lane(exec_ds)
|
||||
else: inst._dispatch = dispatch_lane(exec_vop)
|
||||
|
||||
# Compile pcode for instructions that use it (not VOPD which has _fnx/_fny, not special dispatches)
|
||||
# VOPD needs separate functions for X and Y ops
|
||||
if isinstance(inst, VOPD):
|
||||
def _compile_vopd_op(op): return compile_pseudocode(type(op).__name__, op.name, PCODE[op])
|
||||
inst._fnx, inst._fny = _compile_vopd_op(_VOPD_TO_VOP[inst.opx]), _compile_vopd_op(_VOPD_TO_VOP[inst.opy])
|
||||
elif inst._dispatch not in (dispatch_endpgm, dispatch_barrier, dispatch_nop, dispatch_wmma, dispatch_writelane):
|
||||
assert type(inst.op) != int, f"inst op of {inst} is int"
|
||||
inst._fn = compile_pseudocode(type(inst.op).__name__, inst.op.name, PCODE[inst.op])
|
||||
result[i // 4] = inst
|
||||
i += inst._words * 4
|
||||
return result
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# MAIN EXECUTION LOOP
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def exec_wave(program: dict[int, Inst], st: WaveState) -> int:
|
||||
while (inst := program.get(st.pc)) and (result := inst._dispatch(st, inst)) == 0: pass
|
||||
return result
|
||||
|
||||
def exec_workgroup(program: dict[int, Inst], workgroup_id: tuple[int, int, int], local_size: tuple[int, int, int], args_ptr: int, rsrc2: int) -> None:
|
||||
lx, ly, lz = local_size
|
||||
total_threads = lx * ly * lz
|
||||
# GRANULATED_LDS_SIZE is in 512-byte units (see ops_amd.py: lds_size = ((group_segment_size + 511) // 512))
|
||||
lds_size = ((rsrc2 & hsa.AMD_COMPUTE_PGM_RSRC_TWO_GRANULATED_LDS_SIZE) >> hsa.AMD_COMPUTE_PGM_RSRC_TWO_GRANULATED_LDS_SIZE_SHIFT) * 512
|
||||
lds = LDSMem(bytearray(lds_size)) if lds_size else None
|
||||
waves: list[WaveState] = []
|
||||
for wave_start in range(0, total_threads, WAVE_SIZE):
|
||||
n_lanes = min(WAVE_SIZE, total_threads - wave_start)
|
||||
st = WaveState(lds, n_lanes)
|
||||
st.exec_mask = (1 << n_lanes) - 1
|
||||
st.wsgpr64(s[0:1], args_ptr) # s[0:1] = kernel arguments pointer
|
||||
# COMPUTE_PGM_RSRC2: USER_SGPR_COUNT is where workgroup IDs start, ENABLE_SGPR_WORKGROUP_ID_X/Y/Z control which are passed
|
||||
sgpr_idx = (rsrc2 & hsa.AMD_COMPUTE_PGM_RSRC_TWO_USER_SGPR_COUNT) >> hsa.AMD_COMPUTE_PGM_RSRC_TWO_USER_SGPR_COUNT_SHIFT
|
||||
if rsrc2 & hsa.AMD_COMPUTE_PGM_RSRC_TWO_ENABLE_SGPR_WORKGROUP_ID_X: st.sgpr[sgpr_idx] = workgroup_id[0]; sgpr_idx += 1
|
||||
if rsrc2 & hsa.AMD_COMPUTE_PGM_RSRC_TWO_ENABLE_SGPR_WORKGROUP_ID_Y: st.sgpr[sgpr_idx] = workgroup_id[1]; sgpr_idx += 1
|
||||
if rsrc2 & hsa.AMD_COMPUTE_PGM_RSRC_TWO_ENABLE_SGPR_WORKGROUP_ID_Z: st.sgpr[sgpr_idx] = workgroup_id[2]
|
||||
# VGPR0 = packed workitem IDs: (Z << 20) | (Y << 10) | X
|
||||
for tid in range(wave_start, wave_start + n_lanes):
|
||||
st.vgpr[tid - wave_start][0] = ((tid // (lx * ly)) << 20) | (((tid // lx) % ly) << 10) | (tid % lx)
|
||||
waves.append(st)
|
||||
while waves:
|
||||
waves = [st for st in waves if exec_wave(program, st) != -1]
|
||||
|
||||
def run_asm(lib: int, lib_sz: int, gx: int, gy: int, gz: int, lx: int, ly: int, lz: int, args_ptr: int, rsrc2: int = 0x19c) -> int:
|
||||
program = decode_program((ctypes.c_char * lib_sz).from_address(lib).raw)
|
||||
for gidz in range(gz):
|
||||
for gidy in range(gy):
|
||||
for gidx in range(gx): exec_workgroup(program, (gidx, gidy, gidz), (lx, ly, lz), args_ptr, rsrc2)
|
||||
return 0
|
||||
@@ -1,822 +0,0 @@
|
||||
# DSL for RDNA3 pseudocode - makes pseudocode expressions work directly as Python
|
||||
import struct, math, re, functools
|
||||
|
||||
MASK32, MASK64 = 0xFFFFFFFF, 0xFFFFFFFFFFFFFFFF
|
||||
|
||||
# Float/int bit conversion functions
|
||||
_struct_f, _struct_I = struct.Struct("<f"), struct.Struct("<I")
|
||||
_struct_e, _struct_H = struct.Struct("<e"), struct.Struct("<H")
|
||||
_struct_d, _struct_Q = struct.Struct("<d"), struct.Struct("<Q")
|
||||
def _f32(i):
|
||||
i = i & MASK32
|
||||
# RDNA3 default mode: flush f32 denormals to zero (FTZ)
|
||||
# Denormal: exponent=0 (bits 23-30) and mantissa!=0 (bits 0-22)
|
||||
if (i & 0x7f800000) == 0 and (i & 0x007fffff) != 0: return 0.0
|
||||
return _struct_f.unpack(_struct_I.pack(i))[0]
|
||||
def _i32(f):
|
||||
if isinstance(f, int): f = float(f)
|
||||
if math.isnan(f): return 0xffc00000 if math.copysign(1.0, f) < 0 else 0x7fc00000
|
||||
if math.isinf(f): return 0x7f800000 if f > 0 else 0xff800000
|
||||
try:
|
||||
bits = _struct_I.unpack(_struct_f.pack(f))[0]
|
||||
# RDNA3 default mode: flush f32 denormals to zero (FTZ)
|
||||
if (bits & 0x7f800000) == 0 and (bits & 0x007fffff) != 0: return 0x80000000 if bits & 0x80000000 else 0
|
||||
return bits
|
||||
except (OverflowError, struct.error): return 0x7f800000 if f > 0 else 0xff800000
|
||||
def _sext(v, b): return v - (1 << b) if v & (1 << (b - 1)) else v
|
||||
def _f16(i): return _struct_e.unpack(_struct_H.pack(i & 0xffff))[0]
|
||||
def _i16(f):
|
||||
if math.isnan(f): return 0x7e00
|
||||
if math.isinf(f): return 0x7c00 if f > 0 else 0xfc00
|
||||
try: return _struct_H.unpack(_struct_e.pack(f))[0]
|
||||
except (OverflowError, struct.error): return 0x7c00 if f > 0 else 0xfc00
|
||||
def _f64(i): return _struct_d.unpack(_struct_Q.pack(i & MASK64))[0]
|
||||
def _i64(f):
|
||||
if math.isnan(f): return 0x7ff8000000000000
|
||||
if math.isinf(f): return 0x7ff0000000000000 if f > 0 else 0xfff0000000000000
|
||||
try: return _struct_Q.unpack(_struct_d.pack(f))[0]
|
||||
except (OverflowError, struct.error): return 0x7ff0000000000000 if f > 0 else 0xfff0000000000000
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# INTERNAL HELPERS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _div(a, b):
|
||||
try: return a / b
|
||||
except ZeroDivisionError:
|
||||
if a == 0.0 or math.isnan(a): return float("nan")
|
||||
return math.copysign(float("inf"), a * b) if b == 0.0 else float("inf") if a > 0 else float("-inf")
|
||||
def _check_nan_type(x, quiet_bit_expected, default):
|
||||
try:
|
||||
if not math.isnan(float(x)): return False
|
||||
if hasattr(x, '_reg') and hasattr(x, '_bits'):
|
||||
bits = x._reg._val & ((1 << x._bits) - 1)
|
||||
exp_bits, quiet_pos, mant_mask = {16: (0x1f, 9, 0x3ff), 32: (0xff, 22, 0x7fffff), 64: (0x7ff, 51, 0xfffffffffffff)}.get(x._bits, (0,0,0))
|
||||
exp_shift = {16: 10, 32: 23, 64: 52}.get(x._bits, 0)
|
||||
if exp_bits and ((bits >> exp_shift) & exp_bits) == exp_bits and (bits & mant_mask) != 0:
|
||||
return ((bits >> quiet_pos) & 1) == quiet_bit_expected
|
||||
return default
|
||||
except (TypeError, ValueError): return False
|
||||
def _gt_neg_zero(a, b): return (a > b) or (a == 0 and b == 0 and not math.copysign(1, a) < 0 and math.copysign(1, b) < 0)
|
||||
def _lt_neg_zero(a, b): return (a < b) or (a == 0 and b == 0 and math.copysign(1, a) < 0 and not math.copysign(1, b) < 0)
|
||||
def _fpop(fn):
|
||||
def wrapper(x):
|
||||
x = float(x)
|
||||
if math.isnan(x) or math.isinf(x): return x
|
||||
result = float(fn(x))
|
||||
return math.copysign(0.0, x) if result == 0.0 else result
|
||||
return wrapper
|
||||
def _f_to_int(f, lo, hi): f = float(f); return 0 if math.isnan(f) else (hi if f >= hi else lo if f <= lo else int(f))
|
||||
def _f16_to_f32_bits(bits): return struct.unpack("<e", struct.pack("<H", int(bits) & 0xffff))[0]
|
||||
def _brev(v, bits): return int(bin(v & ((1 << bits) - 1))[2:].zfill(bits)[::-1], 2)
|
||||
def _ctz(v, bits):
|
||||
v, n = int(v) & ((1 << bits) - 1), 0
|
||||
if v == 0: return bits
|
||||
while (v & 1) == 0: v >>= 1; n += 1
|
||||
return n
|
||||
|
||||
def _bf16(i):
|
||||
"""Convert bf16 bits to float. BF16 is just the top 16 bits of f32."""
|
||||
return struct.unpack("<f", struct.pack("<I", (i & 0xffff) << 16))[0]
|
||||
def _ibf16(f):
|
||||
"""Convert float to bf16 bits (truncate to top 16 bits of f32)."""
|
||||
if math.isnan(f): return 0x7fc0 # bf16 quiet NaN
|
||||
if math.isinf(f): return 0x7f80 if f > 0 else 0xff80 # bf16 ±infinity
|
||||
try: return (struct.unpack("<I", struct.pack("<f", float(f)))[0] >> 16) & 0xffff
|
||||
except (OverflowError, struct.error): return 0x7f80 if f > 0 else 0xff80
|
||||
def _trig(fn, x):
|
||||
# V_SIN/COS_F32: hardware does frac on input cycles before computing
|
||||
if math.isinf(x) or math.isnan(x): return float("nan")
|
||||
frac_cycles = fract(x / (2 * math.pi))
|
||||
result = fn(frac_cycles * 2 * math.pi)
|
||||
# Hardware returns exactly 0 for cos(π/2), sin(π), etc. due to lookup table
|
||||
# Round very small results (below f32 precision) to exactly 0
|
||||
if abs(result) < 1e-7: return 0.0
|
||||
return result
|
||||
|
||||
class _SafeFloat(float):
|
||||
"""Float subclass that uses _div for division to handle 0/inf correctly."""
|
||||
def __truediv__(self, o): return _div(float(self), float(o))
|
||||
def __rtruediv__(self, o): return _div(float(o), float(self))
|
||||
|
||||
class _Inf:
|
||||
f16 = f32 = f64 = float('inf')
|
||||
def __neg__(self): return _NegInf()
|
||||
def __pos__(self): return self
|
||||
def __float__(self): return float('inf')
|
||||
def __eq__(self, other): return float(other) == float('inf') if not isinstance(other, _NegInf) else False
|
||||
def __req__(self, other): return self.__eq__(other)
|
||||
class _NegInf:
|
||||
f16 = f32 = f64 = float('-inf')
|
||||
def __neg__(self): return _Inf()
|
||||
def __pos__(self): return self
|
||||
def __float__(self): return float('-inf')
|
||||
def __eq__(self, other): return float(other) == float('-inf') if not isinstance(other, _Inf) else False
|
||||
def __req__(self, other): return self.__eq__(other)
|
||||
|
||||
class _RoundMode:
|
||||
NEAREST_EVEN = 0
|
||||
|
||||
class _WaveMode:
|
||||
IEEE = False
|
||||
|
||||
class _DenormChecker:
|
||||
"""Comparator for denormalized floats. x == DENORM.f32 checks if x is denormalized."""
|
||||
def __init__(self, bits): self._bits = bits
|
||||
def _check(self, other):
|
||||
f = float(other)
|
||||
if math.isinf(f) or math.isnan(f) or f == 0.0: return False
|
||||
if self._bits == 64:
|
||||
bits = struct.unpack("<Q", struct.pack("<d", f))[0]
|
||||
return (bits >> 52) & 0x7ff == 0
|
||||
bits = struct.unpack("<I", struct.pack("<f", f))[0]
|
||||
return (bits >> 23) & 0xff == 0
|
||||
def __eq__(self, other): return self._check(other)
|
||||
def __req__(self, other): return self._check(other)
|
||||
def __ne__(self, other): return not self._check(other)
|
||||
|
||||
class _Denorm:
|
||||
f32 = _DenormChecker(32)
|
||||
f64 = _DenormChecker(64)
|
||||
|
||||
_pack = lambda hi, lo: ((int(hi) & 0xffff) << 16) | (int(lo) & 0xffff)
|
||||
_pack32 = lambda hi, lo: ((int(hi) & 0xffffffff) << 32) | (int(lo) & 0xffffffff)
|
||||
|
||||
class TypedView:
|
||||
"""View into a Reg with typed access. Used for both full-width (Reg.u32) and slices (Reg[31:16])."""
|
||||
__slots__ = ('_reg', '_high', '_low', '_signed', '_float', '_bf16', '_reversed')
|
||||
def __init__(self, reg, high, low=0, signed=False, is_float=False, is_bf16=False):
|
||||
# Handle reversed slices like [0:31] which means bit-reverse
|
||||
if high < low: high, low, reversed = low, high, True
|
||||
else: reversed = False
|
||||
self._reg, self._high, self._low, self._reversed = reg, high, low, reversed
|
||||
self._signed, self._float, self._bf16 = signed, is_float, is_bf16
|
||||
|
||||
def _nbits(self): return self._high - self._low + 1
|
||||
def _mask(self): return (1 << self._nbits()) - 1
|
||||
def _get(self):
|
||||
v = (self._reg._val >> self._low) & self._mask()
|
||||
return _brev(v, self._nbits()) if self._reversed else v
|
||||
def _set(self, v):
|
||||
v = int(v)
|
||||
if self._reversed: v = _brev(v, self._nbits())
|
||||
self._reg._val = (self._reg._val & ~(self._mask() << self._low)) | ((v & self._mask()) << self._low)
|
||||
|
||||
@property
|
||||
def _val(self): return self._get()
|
||||
@property
|
||||
def _bits(self): return self._nbits()
|
||||
|
||||
# Type accessors for slices (e.g., D0[31:16].f16)
|
||||
u8 = property(lambda s: s._get() & 0xff)
|
||||
u16 = property(lambda s: s._get() & 0xffff, lambda s, v: s._set(v))
|
||||
u32 = property(lambda s: s._get() & MASK32, lambda s, v: s._set(v))
|
||||
i16 = property(lambda s: _sext(s._get() & 0xffff, 16), lambda s, v: s._set(v))
|
||||
i32 = property(lambda s: _sext(s._get() & MASK32, 32), lambda s, v: s._set(v))
|
||||
f16 = property(lambda s: _f16(s._get()), lambda s, v: s._set(v if isinstance(v, int) else _i16(float(v))))
|
||||
f32 = property(lambda s: _f32(s._get()), lambda s, v: s._set(_i32(float(v))))
|
||||
bf16 = property(lambda s: _bf16(s._get()), lambda s, v: s._set(v if isinstance(v, int) else _ibf16(float(v))))
|
||||
b16, b32 = u16, u32
|
||||
|
||||
# Chained type access (e.g., jump_addr.i64 when jump_addr is already TypedView)
|
||||
@property
|
||||
def i64(s): return s if s._nbits() == 64 and s._signed else int(s)
|
||||
@property
|
||||
def u64(s): return s if s._nbits() == 64 and not s._signed else int(s) & MASK64
|
||||
|
||||
def __getitem__(self, key):
|
||||
if isinstance(key, slice):
|
||||
high, low = int(key.start), int(key.stop)
|
||||
return TypedView(self._reg, high, low)
|
||||
return (self._get() >> int(key)) & 1
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
if isinstance(key, slice):
|
||||
high, low = int(key.start), int(key.stop)
|
||||
if high < low: high, low, value = low, high, _brev(int(value), low - high + 1)
|
||||
mask = (1 << (high - low + 1)) - 1
|
||||
self._reg._val = (self._reg._val & ~(mask << low)) | ((int(value) & mask) << low)
|
||||
elif value: self._reg._val |= (1 << int(key))
|
||||
else: self._reg._val &= ~(1 << int(key))
|
||||
|
||||
def __int__(self): return _sext(self._get(), self._nbits()) if self._signed else self._get()
|
||||
def __index__(self): return int(self)
|
||||
def __trunc__(self): return int(float(self)) if self._float else int(self)
|
||||
def __float__(self):
|
||||
if self._float:
|
||||
if self._bf16: return _bf16(self._get())
|
||||
bits = self._nbits()
|
||||
return _f16(self._get()) if bits == 16 else _f32(self._get()) if bits == 32 else _f64(self._get())
|
||||
return float(int(self))
|
||||
def __bool__(s): return bool(int(s))
|
||||
|
||||
# Arithmetic - floats use float(), ints use int()
|
||||
def __add__(s, o): return float(s) + float(o) if s._float else int(s) + int(o)
|
||||
def __radd__(s, o): return float(o) + float(s) if s._float else int(o) + int(s)
|
||||
def __sub__(s, o): return float(s) - float(o) if s._float else int(s) - int(o)
|
||||
def __rsub__(s, o): return float(o) - float(s) if s._float else int(o) - int(s)
|
||||
def __mul__(s, o): return float(s) * float(o) if s._float else int(s) * int(o)
|
||||
def __rmul__(s, o): return float(o) * float(s) if s._float else int(o) * int(s)
|
||||
def __truediv__(s, o): return _div(float(s), float(o)) if s._float else _div(int(s), int(o))
|
||||
def __rtruediv__(s, o): return _div(float(o), float(s)) if s._float else _div(int(o), int(s))
|
||||
def __pow__(s, o): return float(s) ** float(o) if s._float else int(s) ** int(o)
|
||||
def __rpow__(s, o): return float(o) ** float(s) if s._float else int(o) ** int(s)
|
||||
def __neg__(s): return -float(s) if s._float else -int(s)
|
||||
def __abs__(s): return abs(float(s)) if s._float else abs(int(s))
|
||||
|
||||
# Bitwise - GPU shifts mask the shift amount to valid range
|
||||
def __and__(s, o): return int(s) & int(o)
|
||||
def __or__(s, o): return int(s) | int(o)
|
||||
def __xor__(s, o): return int(s) ^ int(o)
|
||||
def __invert__(s): return ~int(s)
|
||||
def __lshift__(s, o): n = int(o); return int(s) << n if 0 <= n < 64 or s._nbits() > 64 else 0
|
||||
def __rshift__(s, o): n = int(o); return int(s) >> n if 0 <= n < 64 or s._nbits() > 64 else 0
|
||||
def __rand__(s, o): return int(o) & int(s)
|
||||
def __ror__(s, o): return int(o) | int(s)
|
||||
def __rxor__(s, o): return int(o) ^ int(s)
|
||||
def __rlshift__(s, o): n = int(s); return int(o) << n if 0 <= n < 64 else 0
|
||||
def __rrshift__(s, o): n = int(s); return int(o) >> n if 0 <= n < 64 else 0
|
||||
|
||||
# Comparison - handle _DenormChecker specially
|
||||
def __eq__(s, o):
|
||||
if isinstance(o, _DenormChecker): return o._check(s)
|
||||
return float(s) == float(o) if s._float else int(s) == int(o)
|
||||
def __ne__(s, o):
|
||||
if isinstance(o, _DenormChecker): return not o._check(s)
|
||||
return float(s) != float(o) if s._float else int(s) != int(o)
|
||||
def __lt__(s, o): return float(s) < float(o) if s._float else int(s) < int(o)
|
||||
def __le__(s, o): return float(s) <= float(o) if s._float else int(s) <= int(o)
|
||||
def __gt__(s, o): return float(s) > float(o) if s._float else int(s) > int(o)
|
||||
def __ge__(s, o): return float(s) >= float(o) if s._float else int(s) >= int(o)
|
||||
|
||||
class Reg:
|
||||
"""GPU register: D0.f32 = S0.f32 + S1.f32 just works. Supports up to 128 bits for DS_LOAD_B128."""
|
||||
__slots__ = ('_val',)
|
||||
def __init__(self, val=0): self._val = int(val)
|
||||
|
||||
# Typed views - TypedView(reg, high, signed, is_float, is_bf16)
|
||||
u64 = property(lambda s: TypedView(s, 63), lambda s, v: setattr(s, '_val', int(v) & MASK64))
|
||||
i64 = property(lambda s: TypedView(s, 63, signed=True), lambda s, v: setattr(s, '_val', int(v) & MASK64))
|
||||
b64 = property(lambda s: TypedView(s, 63), lambda s, v: setattr(s, '_val', int(v) & MASK64))
|
||||
f64 = property(lambda s: TypedView(s, 63, is_float=True), lambda s, v: setattr(s, '_val', v if isinstance(v, int) else _i64(float(v))))
|
||||
u32 = property(lambda s: TypedView(s, 31), lambda s, v: setattr(s, '_val', int(v) & MASK32))
|
||||
i32 = property(lambda s: TypedView(s, 31, signed=True), lambda s, v: setattr(s, '_val', int(v) & MASK32))
|
||||
b32 = property(lambda s: TypedView(s, 31), lambda s, v: setattr(s, '_val', int(v) & MASK32))
|
||||
f32 = property(lambda s: TypedView(s, 31, is_float=True), lambda s, v: setattr(s, '_val', _i32(float(v))))
|
||||
u24 = property(lambda s: TypedView(s, 23))
|
||||
i24 = property(lambda s: TypedView(s, 23, signed=True))
|
||||
u16 = property(lambda s: TypedView(s, 15), lambda s, v: setattr(s, '_val', (s._val & 0xffff0000) | (int(v) & 0xffff)))
|
||||
i16 = property(lambda s: TypedView(s, 15, signed=True), lambda s, v: setattr(s, '_val', (s._val & 0xffff0000) | (int(v) & 0xffff)))
|
||||
b16 = property(lambda s: TypedView(s, 15), lambda s, v: setattr(s, '_val', (s._val & 0xffff0000) | (int(v) & 0xffff)))
|
||||
f16 = property(lambda s: TypedView(s, 15, is_float=True), lambda s, v: setattr(s, '_val', (s._val & 0xffff0000) | ((v if isinstance(v, int) else _i16(float(v))) & 0xffff)))
|
||||
bf16 = property(lambda s: TypedView(s, 15, is_float=True, is_bf16=True), lambda s, v: setattr(s, '_val', (s._val & 0xffff0000) | ((v if isinstance(v, int) else _ibf16(float(v))) & 0xffff)))
|
||||
u8 = property(lambda s: TypedView(s, 7))
|
||||
i8 = property(lambda s: TypedView(s, 7, signed=True))
|
||||
u3 = property(lambda s: TypedView(s, 2)) # 3-bit for opsel fields
|
||||
u1 = property(lambda s: TypedView(s, 0)) # single bit
|
||||
|
||||
def __getitem__(s, key):
|
||||
if isinstance(key, slice): return TypedView(s, int(key.start), int(key.stop))
|
||||
return (s._val >> int(key)) & 1
|
||||
|
||||
def __setitem__(s, key, value):
|
||||
if isinstance(key, slice):
|
||||
high, low = int(key.start), int(key.stop)
|
||||
if high < low: high, low = low, high
|
||||
mask = (1 << (high - low + 1)) - 1
|
||||
s._val = (s._val & ~(mask << low)) | ((int(value) & mask) << low)
|
||||
elif value: s._val |= (1 << int(key))
|
||||
else: s._val &= ~(1 << int(key))
|
||||
|
||||
def __int__(s): return s._val
|
||||
def __index__(s): return s._val
|
||||
def __bool__(s): return bool(s._val)
|
||||
|
||||
# Arithmetic (for tmp = tmp + 1 patterns). Float operands trigger f32 interpretation.
|
||||
def __add__(s, o): return (_f32(s._val) + float(o)) if isinstance(o, float) else s._val + int(o)
|
||||
def __radd__(s, o): return (float(o) + _f32(s._val)) if isinstance(o, float) else int(o) + s._val
|
||||
def __sub__(s, o): return (_f32(s._val) - float(o)) if isinstance(o, float) else s._val - int(o)
|
||||
def __rsub__(s, o): return (float(o) - _f32(s._val)) if isinstance(o, float) else int(o) - s._val
|
||||
def __mul__(s, o): return (_f32(s._val) * float(o)) if isinstance(o, float) else s._val * int(o)
|
||||
def __rmul__(s, o): return (float(o) * _f32(s._val)) if isinstance(o, float) else int(o) * s._val
|
||||
def __and__(s, o): return s._val & int(o)
|
||||
def __rand__(s, o): return int(o) & s._val
|
||||
def __or__(s, o): return s._val | int(o)
|
||||
def __ror__(s, o): return int(o) | s._val
|
||||
def __xor__(s, o): return s._val ^ int(o)
|
||||
def __rxor__(s, o): return int(o) ^ s._val
|
||||
def __lshift__(s, o): n = int(o); return s._val << n if 0 <= n < 64 else 0
|
||||
def __rshift__(s, o): n = int(o); return s._val >> n if 0 <= n < 64 else 0
|
||||
def __invert__(s): return ~s._val
|
||||
|
||||
# Comparison (for tmp >= 0x100000000 patterns)
|
||||
def __lt__(s, o): return s._val < int(o)
|
||||
def __le__(s, o): return s._val <= int(o)
|
||||
def __gt__(s, o): return s._val > int(o)
|
||||
def __ge__(s, o): return s._val >= int(o)
|
||||
def __eq__(s, o): return s._val == int(o)
|
||||
def __ne__(s, o): return s._val != int(o)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PSEUDOCODE API - Functions and constants from AMD ISA pseudocode
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
# Rounding and float operations
|
||||
trunc, floor, ceil = _fpop(math.trunc), _fpop(math.floor), _fpop(math.ceil)
|
||||
def sqrt(x): return _SafeFloat(math.sqrt(x)) if x >= 0 else _SafeFloat(float("nan"))
|
||||
def log2(x): return math.log2(x) if x > 0 else (float("-inf") if x == 0 else float("nan"))
|
||||
def fract(x): return x - math.floor(x)
|
||||
def sin(x): return _trig(math.sin, x)
|
||||
def cos(x): return _trig(math.cos, x)
|
||||
def pow(a, b):
|
||||
try: return a ** b
|
||||
except OverflowError: return float("inf") if b > 0 else 0.0
|
||||
def isEven(x):
|
||||
x = float(x)
|
||||
if math.isinf(x) or math.isnan(x): return False
|
||||
return int(x) % 2 == 0
|
||||
def mantissa(f):
|
||||
if f == 0.0 or math.isinf(f) or math.isnan(f): return f
|
||||
m, _ = math.frexp(f)
|
||||
return m # AMD V_FREXP_MANT returns mantissa in [0.5, 1.0) range
|
||||
def signext_from_bit(val, bit):
|
||||
bit = int(bit)
|
||||
if bit == 0: return 0
|
||||
mask = (1 << bit) - 1
|
||||
val = int(val) & mask
|
||||
if val & (1 << (bit - 1)): return val - (1 << bit)
|
||||
return val
|
||||
|
||||
# Type conversions
|
||||
i32_to_f32 = u32_to_f32 = i32_to_f64 = u32_to_f64 = f32_to_f64 = f64_to_f32 = float
|
||||
def f32_to_i32(f): return _f_to_int(f, -2147483648, 2147483647)
|
||||
def f32_to_u32(f): return _f_to_int(f, 0, 4294967295)
|
||||
f64_to_i32, f64_to_u32 = f32_to_i32, f32_to_u32
|
||||
def f32_to_f16(f):
|
||||
f = float(f)
|
||||
if math.isnan(f): return 0x7e00 # f16 NaN
|
||||
if math.isinf(f): return 0x7c00 if f > 0 else 0xfc00 # f16 ±infinity
|
||||
try: return struct.unpack("<H", struct.pack("<e", f))[0]
|
||||
except OverflowError: return 0x7c00 if f > 0 else 0xfc00 # overflow -> ±infinity
|
||||
def f16_to_f32(v): return v if isinstance(v, float) else _f16_to_f32_bits(v)
|
||||
def i16_to_f16(v): return f32_to_f16(float(_sext(int(v) & 0xffff, 16)))
|
||||
def u16_to_f16(v): return f32_to_f16(float(int(v) & 0xffff))
|
||||
def f16_to_i16(bits): f = _f16_to_f32_bits(bits); return max(-32768, min(32767, int(f))) if not math.isnan(f) else 0
|
||||
def f16_to_u16(bits): f = _f16_to_f32_bits(bits); return max(0, min(65535, int(f))) if not math.isnan(f) else 0
|
||||
def bf16_to_f32(v): return _bf16(v) if isinstance(v, int) else float(v)
|
||||
def f32_to_bf16(f): return _ibf16(f)
|
||||
def u8_to_u32(v): return int(v) & 0xff
|
||||
def u4_to_u32(v): return int(v) & 0xf
|
||||
def u32_to_u16(u): return int(u) & 0xffff
|
||||
def i32_to_i16(i): return ((int(i) + 32768) & 0xffff) - 32768
|
||||
def f16_to_snorm(f): return max(-32768, min(32767, int(round(max(-1.0, min(1.0, f)) * 32767))))
|
||||
def f16_to_unorm(f): return max(0, min(65535, int(round(max(0.0, min(1.0, f)) * 65535))))
|
||||
def f32_to_snorm(f): return max(-32768, min(32767, int(round(max(-1.0, min(1.0, f)) * 32767))))
|
||||
def f32_to_unorm(f): return max(0, min(65535, int(round(max(0.0, min(1.0, f)) * 65535))))
|
||||
def v_cvt_i16_f32(f): return max(-32768, min(32767, int(f))) if not math.isnan(f) else 0
|
||||
def v_cvt_u16_f32(f): return max(0, min(65535, int(f))) if not math.isnan(f) else 0
|
||||
def SAT8(v): return max(0, min(255, int(v)))
|
||||
def f32_to_u8(f): return max(0, min(255, int(f))) if not math.isnan(f) else 0
|
||||
|
||||
# Min/max operations
|
||||
def v_min_f32(a, b): return a if math.isnan(b) else b if math.isnan(a) else (a if _lt_neg_zero(a, b) else b)
|
||||
def v_max_f32(a, b): return a if math.isnan(b) else b if math.isnan(a) else (a if _gt_neg_zero(a, b) else b)
|
||||
v_min_f16, v_max_f16 = v_min_f32, v_max_f32
|
||||
v_min_i32, v_max_i32 = min, max
|
||||
v_min_i16, v_max_i16 = min, max
|
||||
def v_min_u32(a, b): return min(a & MASK32, b & MASK32)
|
||||
def v_max_u32(a, b): return max(a & MASK32, b & MASK32)
|
||||
def v_min_u16(a, b): return min(a & 0xffff, b & 0xffff)
|
||||
def v_max_u16(a, b): return max(a & 0xffff, b & 0xffff)
|
||||
def v_min3_f32(a, b, c): return v_min_f32(v_min_f32(a, b), c)
|
||||
def v_max3_f32(a, b, c): return v_max_f32(v_max_f32(a, b), c)
|
||||
v_min3_f16, v_max3_f16 = v_min3_f32, v_max3_f32
|
||||
v_min3_i32, v_max3_i32, v_min3_i16, v_max3_i16 = min, max, min, max
|
||||
def v_min3_u32(a, b, c): return min(a & MASK32, b & MASK32, c & MASK32)
|
||||
def v_max3_u32(a, b, c): return max(a & MASK32, b & MASK32, c & MASK32)
|
||||
def v_min3_u16(a, b, c): return min(a & 0xffff, b & 0xffff, c & 0xffff)
|
||||
def v_max3_u16(a, b, c): return max(a & 0xffff, b & 0xffff, c & 0xffff)
|
||||
|
||||
# SAD/MSAD operations
|
||||
def ABSDIFF(a, b): return abs(int(a) - int(b))
|
||||
def v_sad_u8(s0, s1, s2):
|
||||
"""V_SAD_U8: Sum of absolute differences of 4 byte pairs plus accumulator."""
|
||||
s0, s1, s2 = int(s0), int(s1), int(s2)
|
||||
result = s2
|
||||
for i in range(4):
|
||||
a = (s0 >> (i * 8)) & 0xff
|
||||
b = (s1 >> (i * 8)) & 0xff
|
||||
result += abs(a - b)
|
||||
return result & 0xffffffff
|
||||
def v_msad_u8(s0, s1, s2):
|
||||
"""V_MSAD_U8: Masked sum of absolute differences (skip if reference byte is 0)."""
|
||||
s0, s1, s2 = int(s0), int(s1), int(s2)
|
||||
result = s2
|
||||
for i in range(4):
|
||||
a = (s0 >> (i * 8)) & 0xff
|
||||
b = (s1 >> (i * 8)) & 0xff
|
||||
if b != 0: # Only add diff if reference (s1) byte is non-zero
|
||||
result += abs(a - b)
|
||||
return result & 0xffffffff
|
||||
|
||||
def BYTE_PERMUTE(data, sel):
|
||||
"""Select a byte from 64-bit data based on selector value."""
|
||||
sel = int(sel) & 0xff
|
||||
if sel <= 7: return (int(data) >> (sel * 8)) & 0xff
|
||||
if sel == 8: return 0xff if ((int(data) >> 15) & 1) else 0x00
|
||||
if sel == 9: return 0xff if ((int(data) >> 31) & 1) else 0x00
|
||||
if sel == 10: return 0xff if ((int(data) >> 47) & 1) else 0x00
|
||||
if sel == 11: return 0xff if ((int(data) >> 63) & 1) else 0x00
|
||||
if sel == 12: return 0x00
|
||||
return 0xff
|
||||
|
||||
# Pseudocode functions
|
||||
def s_ff1_i32_b32(v): return _ctz(v, 32)
|
||||
def s_ff1_i32_b64(v): return _ctz(v, 64)
|
||||
GT_NEG_ZERO, LT_NEG_ZERO = _gt_neg_zero, _lt_neg_zero
|
||||
def isNAN(x):
|
||||
try: return math.isnan(float(x))
|
||||
except (TypeError, ValueError): return False
|
||||
def isQuietNAN(x): return _check_nan_type(x, 1, True)
|
||||
def isSignalNAN(x): return _check_nan_type(x, 0, False)
|
||||
def fma(a, b, c):
|
||||
try: return math.fma(a, b, c)
|
||||
except ValueError: return float('nan')
|
||||
def ldexp(m, e): return math.ldexp(m, e)
|
||||
def sign(f): return 1 if math.copysign(1.0, f) < 0 else 0
|
||||
def exponent(f):
|
||||
if hasattr(f, '_bits') and hasattr(f, '_float') and f._float:
|
||||
raw = f._val
|
||||
if f._bits == 16: return (raw >> 10) & 0x1f
|
||||
if f._bits == 32: return (raw >> 23) & 0xff
|
||||
if f._bits == 64: return (raw >> 52) & 0x7ff
|
||||
f = float(f)
|
||||
if math.isinf(f) or math.isnan(f): return 255
|
||||
if f == 0.0: return 0
|
||||
try: bits = struct.unpack("<I", struct.pack("<f", f))[0]; return (bits >> 23) & 0xff
|
||||
except: return 0
|
||||
def signext(x): return int(x)
|
||||
def cvtToQuietNAN(x): return float('nan')
|
||||
|
||||
def F(x):
|
||||
"""32'F(x) or 64'F(x) - interpret x as float. If x is int, treat as bit pattern."""
|
||||
if isinstance(x, int): return _f32(x)
|
||||
if isinstance(x, TypedView): return x
|
||||
return float(x)
|
||||
|
||||
# Constants
|
||||
PI = math.pi
|
||||
WAVE32, WAVE64 = True, False
|
||||
OVERFLOW_F32, UNDERFLOW_F32 = float('inf'), 0.0
|
||||
OVERFLOW_F64, UNDERFLOW_F64 = float('inf'), 0.0
|
||||
MAX_FLOAT_F32 = 3.4028235e+38
|
||||
INF = _Inf()
|
||||
ROUND_MODE = _RoundMode()
|
||||
WAVE_MODE = _WaveMode()
|
||||
DENORM = _Denorm()
|
||||
|
||||
# 2/PI with 1201 bits of precision for V_TRIG_PREOP_F64
|
||||
TWO_OVER_PI_1201 = Reg(0x0145f306dc9c882a53f84eafa3ea69bb81b6c52b3278872083fca2c757bd778ac36e48dc74849ba5c00c925dd413a32439fc3bd63962534e7dd1046bea5d768909d338e04d68befc827323ac7306a673e93908bf177bf250763ff12fffbc0b301fde5e2316b414da3eda6cfd9e4f96136e9e8c7ecd3cbfd45aea4f758fd7cbe2f67a0e73ef14a525d4d7f6bf623f1aba10ac06608df8f6)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# COMPILER: pseudocode -> Python (minimal transforms)
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _filter_pseudocode(pseudocode: str) -> str:
|
||||
"""Filter raw PDF pseudocode to only include actual code lines."""
|
||||
pcode_lines, in_lambda, depth = [], 0, 0
|
||||
for line in pseudocode.split('\n'):
|
||||
s = line.strip()
|
||||
if not s: continue
|
||||
if '=>' in s or re.match(r'^[A-Z_]+\(', s): continue # Skip example lines
|
||||
if '= lambda(' in s: in_lambda += 1; continue # Skip lambda definitions
|
||||
if in_lambda > 0:
|
||||
if s.endswith(');'): in_lambda -= 1
|
||||
continue
|
||||
# Only include lines that look like pseudocode
|
||||
is_code = (any(p in s for p in ['D0.', 'D1.', 'S0.', 'S1.', 'S2.', 'SCC =', 'SCC ?', 'VCC', 'EXEC', 'tmp =', 'tmp[', 'lane =', 'PC =',
|
||||
'D0[', 'D1[', 'S0[', 'S1[', 'S2[', 'MEM[', 'RETURN_DATA', 'VADDR', 'VDATA', 'VDST', 'SADDR', 'OFFSET']) or
|
||||
s.startswith(('if ', 'else', 'elsif', 'endif', 'declare ', 'for ', 'endfor', '//')) or
|
||||
re.match(r'^[a-z_]+\s*=', s) or re.match(r'^[a-z_]+\[', s) or (depth > 0 and '=' in s))
|
||||
if s.startswith('if '): depth += 1
|
||||
elif s.startswith('endif'): depth = max(0, depth - 1)
|
||||
if is_code: pcode_lines.append(s)
|
||||
return '\n'.join(pcode_lines)
|
||||
|
||||
def _compile_pseudocode(pseudocode: str) -> str:
|
||||
"""Compile pseudocode to Python. Transforms are minimal - most syntax just works."""
|
||||
pseudocode = re.sub(r'\bpass\b', 'pass_', pseudocode) # 'pass' is Python keyword
|
||||
raw_lines = pseudocode.strip().split('\n')
|
||||
joined_lines: list[str] = []
|
||||
for line in raw_lines:
|
||||
line = line.strip()
|
||||
if joined_lines and (joined_lines[-1].rstrip().endswith(('||', '&&', '(', ',')) or
|
||||
(joined_lines[-1].count('(') > joined_lines[-1].count(')'))):
|
||||
joined_lines[-1] = joined_lines[-1].rstrip() + ' ' + line
|
||||
else:
|
||||
joined_lines.append(line)
|
||||
|
||||
lines = []
|
||||
indent, need_pass, in_first_match_loop = 0, False, False
|
||||
for line in joined_lines:
|
||||
line = line.split('//')[0].strip() # Strip C-style comments
|
||||
if not line: continue
|
||||
if line.startswith('if '):
|
||||
lines.append(' ' * indent + f"if {_expr(line[3:].rstrip(' then'))}:")
|
||||
indent += 1
|
||||
need_pass = True
|
||||
elif line.startswith('elsif '):
|
||||
if need_pass: lines.append(' ' * indent + "pass")
|
||||
indent -= 1
|
||||
lines.append(' ' * indent + f"elif {_expr(line[6:].rstrip(' then'))}:")
|
||||
indent += 1
|
||||
need_pass = True
|
||||
elif line == 'else':
|
||||
if need_pass: lines.append(' ' * indent + "pass")
|
||||
indent -= 1
|
||||
lines.append(' ' * indent + "else:")
|
||||
indent += 1
|
||||
need_pass = True
|
||||
elif line.startswith('endif'):
|
||||
if need_pass: lines.append(' ' * indent + "pass")
|
||||
indent -= 1
|
||||
need_pass = False
|
||||
elif line.startswith('endfor'):
|
||||
if need_pass: lines.append(' ' * indent + "pass")
|
||||
indent -= 1
|
||||
need_pass, in_first_match_loop = False, False
|
||||
elif line.startswith('declare '):
|
||||
pass
|
||||
elif m := re.match(r'for (\w+) in (.+?)\s*:\s*(.+?) do', line):
|
||||
start, end = _expr(m[2].strip()), _expr(m[3].strip())
|
||||
lines.append(' ' * indent + f"for {m[1]} in range({start}, int({end})+1):")
|
||||
indent += 1
|
||||
need_pass, in_first_match_loop = True, True
|
||||
elif '=' in line and not line.startswith('=='):
|
||||
need_pass = False
|
||||
line = line.rstrip(';')
|
||||
if m := re.match(r'\{\s*D1\.[ui]1\s*,\s*D0\.[ui]64\s*\}\s*=\s*(.+)', line):
|
||||
rhs = _expr(m[1])
|
||||
lines.append(' ' * indent + f"_full = {rhs}")
|
||||
lines.append(' ' * indent + f"D0.u64 = int(_full) & 0xffffffffffffffff")
|
||||
lines.append(' ' * indent + f"D1 = Reg((int(_full) >> 64) & 1)")
|
||||
elif any(op in line for op in ('+=', '-=', '*=', '/=', '|=', '&=', '^=')):
|
||||
for op in ('+=', '-=', '*=', '/=', '|=', '&=', '^='):
|
||||
if op in line:
|
||||
lhs, rhs = line.split(op, 1)
|
||||
lines.append(' ' * indent + f"{lhs.strip()} {op} {_expr(rhs.strip())}")
|
||||
break
|
||||
else:
|
||||
lhs, rhs = line.split('=', 1)
|
||||
lhs_s, rhs_s = _expr(lhs.strip()), rhs.strip()
|
||||
stmt = _assign(lhs_s, _expr(rhs_s))
|
||||
if in_first_match_loop and rhs_s == 'i' and (lhs_s == 'tmp' or lhs_s == 'D0.i32'):
|
||||
stmt += "; break"
|
||||
lines.append(' ' * indent + stmt)
|
||||
if need_pass: lines.append(' ' * indent + "pass")
|
||||
return '\n'.join(lines)
|
||||
|
||||
def _assign(lhs: str, rhs: str) -> str:
|
||||
if lhs in ('tmp', 'SCC', 'VCC', 'EXEC', 'D0', 'D1', 'saveexec', 'PC'):
|
||||
return f"{lhs} = Reg({rhs})"
|
||||
return f"{lhs} = {rhs}"
|
||||
|
||||
def _expr(e: str) -> str:
|
||||
e = e.strip()
|
||||
e = e.replace('&&', ' and ').replace('||', ' or ').replace('<>', ' != ')
|
||||
e = re.sub(r'!([^=])', r' not \1', e)
|
||||
e = re.sub(r'\{\s*(\w+\.u32)\s*,\s*(\w+\.u32)\s*\}', r'_pack32(\1, \2)', e)
|
||||
def pack(m):
|
||||
hi, lo = _expr(m[1].strip()), _expr(m[2].strip())
|
||||
return f'_pack({hi}, {lo})'
|
||||
e = re.sub(r'\{\s*([^,{}]+)\s*,\s*([^,{}]+)\s*\}', pack, e)
|
||||
e = re.sub(r"1201'B\(2\.0\s*/\s*PI\)", "TWO_OVER_PI_1201", e)
|
||||
e = re.sub(r"\d+'([0-9a-fA-Fx]+)[UuFf]*", r'\1', e)
|
||||
e = re.sub(r"\d+'[FIBU]\(", "(", e)
|
||||
e = re.sub(r'\bB\(', '(', e)
|
||||
e = re.sub(r'([0-9a-fA-Fx])ULL\b', r'\1', e)
|
||||
e = re.sub(r'([0-9a-fA-Fx])LL\b', r'\1', e)
|
||||
e = re.sub(r'([0-9a-fA-Fx])U\b', r'\1', e)
|
||||
e = re.sub(r'(\d\.?\d*)F\b', r'\1', e)
|
||||
e = re.sub(r'(\[laneId\])\.[uib]\d+', r'\1', e)
|
||||
e = e.replace('+INF', 'INF').replace('-INF', '(-INF)')
|
||||
e = re.sub(r'NAN\.f\d+', 'float("nan")', e)
|
||||
def convert_verilog_slice(m):
|
||||
start, width = m.group(1).strip(), m.group(2).strip()
|
||||
return f'[({start}) + ({width}) - 1 : ({start})]'
|
||||
e = re.sub(r'\[([^:\[\]]+)\s*\+:\s*([^:\[\]]+)\]', convert_verilog_slice, e)
|
||||
def process_brackets(s):
|
||||
result, i = [], 0
|
||||
while i < len(s):
|
||||
if s[i] == '[':
|
||||
depth, start = 1, i + 1
|
||||
j = start
|
||||
while j < len(s) and depth > 0:
|
||||
if s[j] == '[': depth += 1
|
||||
elif s[j] == ']': depth -= 1
|
||||
j += 1
|
||||
inner = _expr(s[start:j-1])
|
||||
result.append('[' + inner + ']')
|
||||
i = j
|
||||
else:
|
||||
result.append(s[i])
|
||||
i += 1
|
||||
return ''.join(result)
|
||||
e = process_brackets(e)
|
||||
while '?' in e:
|
||||
depth, bracket, q = 0, 0, -1
|
||||
for i, c in enumerate(e):
|
||||
if c == '(': depth += 1
|
||||
elif c == ')': depth -= 1
|
||||
elif c == '[': bracket += 1
|
||||
elif c == ']': bracket -= 1
|
||||
elif c == '?' and depth == 0 and bracket == 0: q = i; break
|
||||
if q < 0: break
|
||||
depth, bracket, col = 0, 0, -1
|
||||
for i in range(q + 1, len(e)):
|
||||
if e[i] == '(': depth += 1
|
||||
elif e[i] == ')': depth -= 1
|
||||
elif e[i] == '[': bracket += 1
|
||||
elif e[i] == ']': bracket -= 1
|
||||
elif e[i] == ':' and depth == 0 and bracket == 0: col = i; break
|
||||
if col < 0: break
|
||||
cond, t, f = e[:q].strip(), e[q+1:col].strip(), e[col+1:].strip()
|
||||
e = f'(({t}) if ({cond}) else ({f}))'
|
||||
return e
|
||||
|
||||
def _apply_pseudocode_fixes(op_name: str, code: str) -> str:
|
||||
"""Apply known fixes for PDF pseudocode bugs."""
|
||||
if op_name == 'V_DIV_FMAS_F32':
|
||||
code = code.replace('D0.f32 = 2.0 ** 32 * fma(S0.f32, S1.f32, S2.f32)',
|
||||
'D0.f32 = (2.0 ** 64 if exponent(S2.f32) > 127 else 2.0 ** -64) * fma(S0.f32, S1.f32, S2.f32)')
|
||||
if op_name == 'V_DIV_FMAS_F64':
|
||||
code = code.replace('D0.f64 = 2.0 ** 64 * fma(S0.f64, S1.f64, S2.f64)',
|
||||
'D0.f64 = (2.0 ** 128 if exponent(S2.f64) > 1023 else 2.0 ** -128) * fma(S0.f64, S1.f64, S2.f64)')
|
||||
if op_name == 'V_DIV_SCALE_F32':
|
||||
code = code.replace('D0.f32 = float("nan")', 'VCC = Reg(0x1); D0.f32 = float("nan")')
|
||||
code = code.replace('elif S1.f32 == DENORM.f32:\n D0.f32 = ldexp(S0.f32, 64)', 'elif False:\n pass')
|
||||
code += '\nif S1.f32 == DENORM.f32:\n D0.f32 = float("nan")'
|
||||
code = code.replace('elif exponent(S2.f32) <= 23:\n D0.f32 = ldexp(S0.f32, 64)', 'elif exponent(S2.f32) <= 23:\n VCC = Reg(0x1); D0.f32 = ldexp(S0.f32, 64)')
|
||||
code = code.replace('elif S2.f32 / S1.f32 == DENORM.f32:\n VCC = Reg(0x1)\n if S0.f32 == S2.f32:\n D0.f32 = ldexp(S0.f32, 64)', 'elif S2.f32 / S1.f32 == DENORM.f32:\n VCC = Reg(0x1)')
|
||||
if op_name == 'V_DIV_SCALE_F64':
|
||||
code = code.replace('D0.f64 = float("nan")', 'VCC = Reg(0x1); D0.f64 = float("nan")')
|
||||
code = code.replace('elif S1.f64 == DENORM.f64:\n D0.f64 = ldexp(S0.f64, 128)', 'elif False:\n pass')
|
||||
code += '\nif S1.f64 == DENORM.f64:\n D0.f64 = float("nan")'
|
||||
code = code.replace('elif exponent(S2.f64) <= 52:\n D0.f64 = ldexp(S0.f64, 128)', 'elif exponent(S2.f64) <= 52:\n VCC = Reg(0x1); D0.f64 = ldexp(S0.f64, 128)')
|
||||
code = code.replace('elif S2.f64 / S1.f64 == DENORM.f64:\n VCC = Reg(0x1)\n if S0.f64 == S2.f64:\n D0.f64 = ldexp(S0.f64, 128)', 'elif S2.f64 / S1.f64 == DENORM.f64:\n VCC = Reg(0x1)')
|
||||
if op_name == 'V_DIV_FIXUP_F32':
|
||||
code = code.replace('D0.f32 = ((-abs(S0.f32)) if (sign_out) else (abs(S0.f32)))',
|
||||
'D0.f32 = ((-OVERFLOW_F32) if (sign_out) else (OVERFLOW_F32)) if isNAN(S0.f32) else ((-abs(S0.f32)) if (sign_out) else (abs(S0.f32)))')
|
||||
if op_name == 'V_DIV_FIXUP_F64':
|
||||
code = code.replace('D0.f64 = ((-abs(S0.f64)) if (sign_out) else (abs(S0.f64)))',
|
||||
'D0.f64 = ((-OVERFLOW_F64) if (sign_out) else (OVERFLOW_F64)) if isNAN(S0.f64) else ((-abs(S0.f64)) if (sign_out) else (abs(S0.f64)))')
|
||||
if op_name == 'V_TRIG_PREOP_F64':
|
||||
code = code.replace('result = F((TWO_OVER_PI_1201[1200 : 0] << shift.u32) & 0x1fffffffffffff)',
|
||||
'result = float(((TWO_OVER_PI_1201[1200 : 0] << int(shift)) >> (1201 - 53)) & 0x1fffffffffffff)')
|
||||
return code
|
||||
|
||||
def _generate_function(cls_name: str, op_name: str, pc: str, code: str) -> str:
|
||||
"""Generate a single compiled pseudocode function.
|
||||
Functions take int parameters and return dict of int values.
|
||||
Reg wrapping happens inside the function, only for registers actually used."""
|
||||
has_d1 = '{ D1' in pc
|
||||
is_cmpx = (cls_name in ('VOPCOp', 'VOP3Op')) and 'EXEC.u64[laneId]' in pc
|
||||
is_div_scale = 'DIV_SCALE' in op_name
|
||||
has_sdst = cls_name == 'VOP3SDOp' and ('VCC.u64[laneId]' in pc or is_div_scale)
|
||||
is_ds = cls_name == 'DSOp'
|
||||
is_flat = cls_name in ('FLATOp', 'GLOBALOp', 'SCRATCHOp')
|
||||
is_smem = cls_name == 'SMEMOp'
|
||||
has_s_array = 'S[i]' in pc # FMA_MIX style: S[0], S[1], S[2] array access
|
||||
combined = code + pc
|
||||
|
||||
fn_name = f"_{cls_name}_{op_name}"
|
||||
|
||||
# Detect which registers are used/modified
|
||||
def needs_init(name): return name in combined and not re.search(rf'^\s*{name}\s*=\s*Reg\(', code, re.MULTILINE)
|
||||
modifies_d0 = is_div_scale or bool(re.search(r'\bD0\b[.\[]', combined))
|
||||
modifies_exec = is_cmpx or bool(re.search(r'EXEC\.(u32|u64|b32|b64)\s*=', combined))
|
||||
modifies_vcc = has_sdst or bool(re.search(r'VCC\.(u32|u64|b32|b64)\s*=|VCC\.u64\[laneId\]\s*=', combined))
|
||||
modifies_scc = bool(re.search(r'\bSCC\s*=', combined))
|
||||
modifies_pc = bool(re.search(r'\bPC\s*=', combined))
|
||||
|
||||
# Build function signature and Reg init lines
|
||||
if is_smem:
|
||||
lines = [f"def {fn_name}(MEM, addr):"]
|
||||
reg_inits = ["ADDR=Reg(addr)", "SDATA=Reg(0)"]
|
||||
special_regs = []
|
||||
elif is_ds:
|
||||
lines = [f"def {fn_name}(MEM, addr, data0, data1, offset0, offset1):"]
|
||||
reg_inits = ["ADDR=Reg(addr)", "DATA0=Reg(data0)", "DATA1=Reg(data1)", "OFFSET0=Reg(offset0)", "OFFSET1=Reg(offset1)", "RETURN_DATA=Reg(0)"]
|
||||
special_regs = [('DATA', 'DATA0'), ('DATA2', 'DATA1'), ('OFFSET', 'OFFSET0'), ('ADDR_BASE', 'ADDR')]
|
||||
elif is_flat:
|
||||
lines = [f"def {fn_name}(MEM, addr, vdata, vdst):"]
|
||||
reg_inits = ["ADDR=addr", "VDATA=Reg(vdata)", "VDST=Reg(vdst)", "RETURN_DATA=Reg(0)"]
|
||||
special_regs = [('DATA', 'VDATA')]
|
||||
elif has_s_array:
|
||||
# FMA_MIX style: needs S[i] array, opsel, opsel_hi for source selection (neg/neg_hi applied in emu.py before call)
|
||||
lines = [f"def {fn_name}(s0, s1, s2, d0, scc, vcc, laneId, exec_mask, literal, VGPR, src0_idx=0, vdst_idx=0, pc=None, opsel=0, opsel_hi=0):"]
|
||||
reg_inits = ["S0=Reg(s0)", "S1=Reg(s1)", "S2=Reg(s2)", "S=[S0,S1,S2]", "D0=Reg(d0)", "OPSEL=Reg(opsel)", "OPSEL_HI=Reg(opsel_hi)"]
|
||||
special_regs = []
|
||||
# Detect array declarations like "declare in : 32'F[3]" and create them (rename 'in' to 'ins' since 'in' is a keyword)
|
||||
if "in[" in combined:
|
||||
reg_inits.append("ins=[Reg(0),Reg(0),Reg(0)]")
|
||||
code = code.replace("in[", "ins[")
|
||||
else:
|
||||
lines = [f"def {fn_name}(s0, s1, s2, d0, scc, vcc, laneId, exec_mask, literal, VGPR, src0_idx=0, vdst_idx=0, pc=None):"]
|
||||
# Only create Regs for registers actually used in the pseudocode
|
||||
reg_inits = []
|
||||
if 'S0' in combined: reg_inits.append("S0=Reg(s0)")
|
||||
if 'S1' in combined: reg_inits.append("S1=Reg(s1)")
|
||||
if 'S2' in combined: reg_inits.append("S2=Reg(s2)")
|
||||
if modifies_d0 or 'D0' in combined: reg_inits.append("D0=Reg(s0)" if is_div_scale else "D0=Reg(d0)")
|
||||
if modifies_scc or 'SCC' in combined: reg_inits.append("SCC=Reg(scc)")
|
||||
if modifies_vcc or 'VCC' in combined: reg_inits.append("VCC=Reg(vcc)")
|
||||
if modifies_exec or 'EXEC' in combined: reg_inits.append("EXEC=Reg(exec_mask)")
|
||||
if modifies_pc or 'PC' in combined: reg_inits.append("PC=Reg(pc) if pc is not None else None")
|
||||
special_regs = [('D1', 'Reg(0)'), ('SIMM16', 'Reg(literal)'), ('SIMM32', 'Reg(literal)'),
|
||||
('SRC0', 'Reg(src0_idx)'), ('VDST', 'Reg(vdst_idx)')]
|
||||
if needs_init('tmp'): special_regs.insert(0, ('tmp', 'Reg(0)'))
|
||||
if needs_init('saveexec'): special_regs.insert(0, ('saveexec', 'Reg(EXEC._val)'))
|
||||
|
||||
# Build init code
|
||||
init_parts = reg_inits.copy()
|
||||
for name, init in special_regs:
|
||||
if name in combined: init_parts.append(f"{name}={init}")
|
||||
if 'EXEC_LO' in code: init_parts.append("EXEC_LO=TypedView(EXEC, 31, 0)")
|
||||
if 'EXEC_HI' in code: init_parts.append("EXEC_HI=TypedView(EXEC, 63, 32)")
|
||||
if 'VCCZ' in code and not re.search(r'^\s*VCCZ\s*=', code, re.MULTILINE): init_parts.append("VCCZ=Reg(1 if VCC._val == 0 else 0)")
|
||||
if 'EXECZ' in code and not re.search(r'^\s*EXECZ\s*=', code, re.MULTILINE): init_parts.append("EXECZ=Reg(1 if EXEC._val == 0 else 0)")
|
||||
|
||||
# Add init line and separator
|
||||
if init_parts: lines.append(f" {'; '.join(init_parts)}")
|
||||
|
||||
# Add compiled pseudocode
|
||||
for line in code.split('\n'):
|
||||
if line.strip(): lines.append(f" {line}")
|
||||
|
||||
# Build result dict
|
||||
result_items = []
|
||||
if modifies_d0: result_items.append("'D0': D0._val")
|
||||
if modifies_scc: result_items.append("'SCC': SCC._val")
|
||||
if modifies_vcc: result_items.append("'VCC': VCC._val")
|
||||
if modifies_exec: result_items.append("'EXEC': EXEC._val")
|
||||
if has_d1: result_items.append("'D1': D1._val")
|
||||
if modifies_pc: result_items.append("'PC': PC._val")
|
||||
if is_smem and 'SDATA' in combined and re.search(r'^\s*SDATA[\.\[].*=', code, re.MULTILINE):
|
||||
result_items.append("'SDATA': SDATA._val")
|
||||
if is_ds and 'RETURN_DATA' in combined and re.search(r'^\s*RETURN_DATA[\.\[].*=', code, re.MULTILINE):
|
||||
result_items.append("'RETURN_DATA': RETURN_DATA._val")
|
||||
if is_flat:
|
||||
if 'RETURN_DATA' in combined and re.search(r'^\s*RETURN_DATA[\.\[].*=', code, re.MULTILINE):
|
||||
result_items.append("'RETURN_DATA': RETURN_DATA._val")
|
||||
if re.search(r'^\s*VDATA[\.\[].*=', code, re.MULTILINE):
|
||||
result_items.append("'VDATA': VDATA._val")
|
||||
lines.append(f" return {{{', '.join(result_items)}}}")
|
||||
return '\n'.join(lines)
|
||||
|
||||
# Build the globals dict for exec() - includes all pcode symbols
|
||||
_PCODE_GLOBALS = {
|
||||
'Reg': Reg, 'TypedView': TypedView, '_pack': _pack, '_pack32': _pack32,
|
||||
'ABSDIFF': ABSDIFF, 'BYTE_PERMUTE': BYTE_PERMUTE, 'DENORM': DENORM, 'F': F,
|
||||
'GT_NEG_ZERO': GT_NEG_ZERO, 'LT_NEG_ZERO': LT_NEG_ZERO, 'INF': INF,
|
||||
'MAX_FLOAT_F32': MAX_FLOAT_F32, 'OVERFLOW_F32': OVERFLOW_F32, 'OVERFLOW_F64': OVERFLOW_F64,
|
||||
'UNDERFLOW_F32': UNDERFLOW_F32, 'UNDERFLOW_F64': UNDERFLOW_F64,
|
||||
'PI': PI, 'ROUND_MODE': ROUND_MODE, 'WAVE_MODE': WAVE_MODE,
|
||||
'WAVE32': WAVE32, 'WAVE64': WAVE64, 'TWO_OVER_PI_1201': TWO_OVER_PI_1201,
|
||||
'SAT8': SAT8, 'trunc': trunc, 'floor': floor, 'ceil': ceil, 'sqrt': sqrt,
|
||||
'log2': log2, 'fract': fract, 'sin': sin, 'cos': cos, 'pow': pow,
|
||||
'isEven': isEven, 'mantissa': mantissa, 'signext_from_bit': signext_from_bit,
|
||||
'i32_to_f32': i32_to_f32, 'u32_to_f32': u32_to_f32, 'i32_to_f64': i32_to_f64,
|
||||
'u32_to_f64': u32_to_f64, 'f32_to_f64': f32_to_f64, 'f64_to_f32': f64_to_f32,
|
||||
'f32_to_i32': f32_to_i32, 'f32_to_u32': f32_to_u32, 'f64_to_i32': f64_to_i32,
|
||||
'f64_to_u32': f64_to_u32, 'f32_to_f16': f32_to_f16, 'f16_to_f32': f16_to_f32,
|
||||
'i16_to_f16': i16_to_f16, 'u16_to_f16': u16_to_f16, 'f16_to_i16': f16_to_i16,
|
||||
'f16_to_u16': f16_to_u16, 'bf16_to_f32': bf16_to_f32, 'f32_to_bf16': f32_to_bf16,
|
||||
'u8_to_u32': u8_to_u32, 'u4_to_u32': u4_to_u32, 'u32_to_u16': u32_to_u16,
|
||||
'i32_to_i16': i32_to_i16, 'f16_to_snorm': f16_to_snorm, 'f16_to_unorm': f16_to_unorm,
|
||||
'f32_to_snorm': f32_to_snorm, 'f32_to_unorm': f32_to_unorm,
|
||||
'v_cvt_i16_f32': v_cvt_i16_f32, 'v_cvt_u16_f32': v_cvt_u16_f32, 'f32_to_u8': f32_to_u8,
|
||||
'v_min_f32': v_min_f32, 'v_max_f32': v_max_f32, 'v_min_f16': v_min_f16, 'v_max_f16': v_max_f16,
|
||||
'v_min_i32': v_min_i32, 'v_max_i32': v_max_i32, 'v_min_i16': v_min_i16, 'v_max_i16': v_max_i16,
|
||||
'v_min_u32': v_min_u32, 'v_max_u32': v_max_u32, 'v_min_u16': v_min_u16, 'v_max_u16': v_max_u16,
|
||||
'v_min3_f32': v_min3_f32, 'v_max3_f32': v_max3_f32, 'v_min3_f16': v_min3_f16, 'v_max3_f16': v_max3_f16,
|
||||
'v_min3_i32': v_min3_i32, 'v_max3_i32': v_max3_i32, 'v_min3_i16': v_min3_i16, 'v_max3_i16': v_max3_i16,
|
||||
'v_min3_u32': v_min3_u32, 'v_max3_u32': v_max3_u32, 'v_min3_u16': v_min3_u16, 'v_max3_u16': v_max3_u16,
|
||||
'v_sad_u8': v_sad_u8, 'v_msad_u8': v_msad_u8,
|
||||
's_ff1_i32_b32': s_ff1_i32_b32, 's_ff1_i32_b64': s_ff1_i32_b64,
|
||||
'isNAN': isNAN, 'isQuietNAN': isQuietNAN, 'isSignalNAN': isSignalNAN,
|
||||
'fma': fma, 'ldexp': ldexp, 'sign': sign, 'exponent': exponent,
|
||||
'signext': signext, 'cvtToQuietNAN': cvtToQuietNAN,
|
||||
}
|
||||
|
||||
@functools.cache
|
||||
def compile_pseudocode(cls_name: str, op_name: str, pseudocode: str):
|
||||
"""Compile pseudocode string to executable function. Cached for performance."""
|
||||
filtered = _filter_pseudocode(pseudocode)
|
||||
code = _compile_pseudocode(filtered)
|
||||
code = _apply_pseudocode_fixes(op_name, code)
|
||||
fn_code = _generate_function(cls_name, op_name, filtered, code)
|
||||
fn_name = f"_{cls_name}_{op_name}"
|
||||
local_ns = {}
|
||||
exec(fn_code, _PCODE_GLOBALS, local_ns)
|
||||
return local_ns[fn_name]
|
||||
@@ -1,386 +0,0 @@
|
||||
"""SQTT (SQ Thread Trace) packet encoder and decoder for AMD GPUs.
|
||||
|
||||
This module provides encoding and decoding of raw SQTT byte streams.
|
||||
The format is nibble-based with variable-width packets determined by a state machine.
|
||||
Uses BitField infrastructure from dsl.py, similar to GPU instruction encoding.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
from typing import Iterator
|
||||
from enum import Enum
|
||||
from extra.assembly.amd.dsl import BitField, FixedBitField, bits
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# FIELD ENUMS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class MemSrc(Enum):
|
||||
LDS = 0
|
||||
LDS_ALT = 1
|
||||
VMEM = 2
|
||||
VMEM_ALT = 3
|
||||
|
||||
class AluSrc(Enum):
|
||||
NONE = 0
|
||||
SALU = 1
|
||||
VALU = 2
|
||||
VALU_SALU = 3
|
||||
|
||||
class InstOp(Enum):
|
||||
"""SQTT instruction operation types.
|
||||
|
||||
Memory ops appear in two ranges depending on which SIMD executes them:
|
||||
- 0x1x-0x2x range: ops on traced SIMD
|
||||
- 0x5x range: ops on other SIMD (OTHER_ prefix)
|
||||
|
||||
GLOBAL memory ops encoding depends on addressing mode AND size:
|
||||
- Loads: 0x21 (saddr=SGPR) or 0x22 (saddr=NULL), all sizes same
|
||||
- Stores: base + size_offset, where VADDR is shifted +1 from SADDR
|
||||
SADDR: 0x24(32) 0x25(64) 0x26(96) 0x27(128)
|
||||
VADDR: 0x25(32) 0x26(64) 0x27(96) 0x28(128)
|
||||
|
||||
OTHER_ range follows same pattern but values overlap differently.
|
||||
"""
|
||||
SALU = 0x0
|
||||
SMEM = 0x1
|
||||
JUMP = 0x3 # branch taken
|
||||
JUMP_NO = 0x4 # branch not taken
|
||||
MESSAGE = 0x9
|
||||
VALU_TRANS = 0xb # transcendental: exp, log, rcp, sqrt, sin, cos
|
||||
VALU_64_SHIFT = 0xd # 64-bit shifts: lshl, lshr, ashr
|
||||
VALU_MAD64 = 0xe # 64-bit multiply-add
|
||||
VALU_64 = 0xf # 64-bit: add, mul, fma, rcp, sqrt, rounding, frexp, div helpers
|
||||
VINTERP = 0x12 # interpolation: v_interp_p10_f32, v_interp_p2_f32
|
||||
BARRIER = 0x13
|
||||
|
||||
# FLAT memory ops on traced SIMD (0x1x range)
|
||||
FLAT_LOAD = 0x1c
|
||||
FLAT_STORE = 0x1d
|
||||
FLAT_STORE_64 = 0x1e
|
||||
FLAT_STORE_96 = 0x1f
|
||||
FLAT_STORE_128 = 0x20
|
||||
|
||||
# GLOBAL memory ops on traced SIMD (0x2x range)
|
||||
GLOBAL_LOAD = 0x21 # saddr=SGPR, all sizes
|
||||
GLOBAL_LOAD_VADDR = 0x22 # saddr=NULL, all sizes
|
||||
GLOBAL_STORE = 0x24 # saddr=SGPR, 32-bit
|
||||
GLOBAL_STORE_64 = 0x25 # saddr=SGPR 64 or saddr=NULL 32
|
||||
GLOBAL_STORE_96 = 0x26 # saddr=SGPR 96 or saddr=NULL 64
|
||||
GLOBAL_STORE_128 = 0x27 # saddr=SGPR 128 or saddr=NULL 96
|
||||
GLOBAL_STORE_VADDR_128 = 0x28 # saddr=NULL, 128-bit
|
||||
|
||||
# LDS ops on traced SIMD
|
||||
LDS_LOAD = 0x29
|
||||
LDS_STORE = 0x2b
|
||||
LDS_STORE_64 = 0x2c
|
||||
LDS_STORE_128 = 0x2e
|
||||
|
||||
# Memory ops on other SIMD (0x5x range)
|
||||
OTHER_LDS_LOAD = 0x50
|
||||
OTHER_LDS_STORE = 0x51
|
||||
OTHER_LDS_STORE_64 = 0x52
|
||||
OTHER_LDS_STORE_128 = 0x54
|
||||
OTHER_FLAT_LOAD = 0x55
|
||||
OTHER_FLAT_STORE = 0x56
|
||||
OTHER_FLAT_STORE_64 = 0x57
|
||||
OTHER_FLAT_STORE_96 = 0x58
|
||||
OTHER_FLAT_STORE_128 = 0x59
|
||||
OTHER_GLOBAL_LOAD = 0x5a # saddr=SGPR, all sizes
|
||||
OTHER_GLOBAL_LOAD_VADDR = 0x5b # saddr=NULL or saddr=SGPR store 32
|
||||
OTHER_GLOBAL_STORE_64 = 0x5c # saddr=SGPR 64 or saddr=NULL 32
|
||||
OTHER_GLOBAL_STORE_96 = 0x5d # saddr=SGPR 96 or saddr=NULL 64
|
||||
OTHER_GLOBAL_STORE_128 = 0x5e # saddr=SGPR 128 or saddr=NULL 96
|
||||
OTHER_GLOBAL_STORE_VADDR_128 = 0x5f # saddr=NULL, 128-bit
|
||||
|
||||
# EXEC-modifying ops (0x7x range)
|
||||
SALU_SAVEEXEC = 0x72 # s_*_saveexec_b32/b64
|
||||
VALU_CMPX = 0x73 # v_cmpx_*
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PACKET TYPE BASE CLASS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class PacketType:
|
||||
"""Base class for SQTT packet types."""
|
||||
encoding: FixedBitField
|
||||
_raw: int
|
||||
_time: int
|
||||
|
||||
def __init_subclass__(cls, **kwargs):
|
||||
super().__init_subclass__(**kwargs)
|
||||
cls._fields = {k: v for k, v in cls.__dict__.items() if isinstance(v, BitField)}
|
||||
cls._size_nibbles = ((max((f.hi for f in cls._fields.values()), default=0) + 4) // 4)
|
||||
|
||||
@classmethod
|
||||
def from_raw(cls, raw: int, time: int = 0):
|
||||
inst = object.__new__(cls)
|
||||
inst._raw, inst._time = raw, time
|
||||
return inst
|
||||
|
||||
def __repr__(self) -> str:
|
||||
fields_str = ", ".join(f"{k}={getattr(self, k)}" for k in self._fields if not k.startswith('_'))
|
||||
return f"{self.__class__.__name__}({fields_str})"
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PACKET TYPE DEFINITIONS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class VALUINST(PacketType): # exclude: 1 << 2
|
||||
encoding = bits[2:0] == 0b011
|
||||
delta = bits[5:3]
|
||||
flag = bits[6:6]
|
||||
wave = bits[11:7]
|
||||
|
||||
class VMEMEXEC(PacketType): # exclude: 1 << 0
|
||||
encoding = bits[3:0] == 0b1111
|
||||
delta = bits[5:4]
|
||||
src = bits[7:6].enum(MemSrc)
|
||||
|
||||
class ALUEXEC(PacketType): # exclude: 1 << 1
|
||||
encoding = bits[3:0] == 0b1110
|
||||
delta = bits[5:4]
|
||||
src = bits[7:6].enum(AluSrc)
|
||||
|
||||
class IMMEDIATE(PacketType): # exclude: 1 << 5
|
||||
encoding = bits[3:0] == 0b1101
|
||||
delta = bits[6:4]
|
||||
wave = bits[11:7]
|
||||
|
||||
class IMMEDIATE_MASK(PacketType): # exclude: 1 << 5
|
||||
encoding = bits[4:0] == 0b00100
|
||||
delta = bits[7:5]
|
||||
mask = bits[23:8]
|
||||
|
||||
class WAVERDY(PacketType): # exclude: 1 << 3
|
||||
encoding = bits[4:0] == 0b10100
|
||||
delta = bits[7:5]
|
||||
mask = bits[23:8]
|
||||
|
||||
class TS_DELTA_S8_W3(PacketType):
|
||||
encoding = bits[6:0] == 0b0100001
|
||||
delta = bits[10:8]
|
||||
_padding = bits[63:11]
|
||||
|
||||
class WAVEEND(PacketType): # exclude: 1 << 4
|
||||
encoding = bits[4:0] == 0b10101
|
||||
delta = bits[7:5]
|
||||
flag7 = bits[8:8]
|
||||
simd = bits[10:9]
|
||||
cu_lo = bits[13:11]
|
||||
wave = bits[19:15]
|
||||
@property
|
||||
def cu(self) -> int: return self.cu_lo | (self.flag7 << 3)
|
||||
|
||||
class WAVESTART(PacketType): # exclude: 1 << 4
|
||||
encoding = bits[4:0] == 0b01100
|
||||
delta = bits[6:5]
|
||||
flag7 = bits[7:7]
|
||||
simd = bits[9:8]
|
||||
cu_lo = bits[12:10]
|
||||
wave = bits[17:13]
|
||||
id7 = bits[31:18]
|
||||
@property
|
||||
def cu(self) -> int: return self.cu_lo | (self.flag7 << 3)
|
||||
|
||||
class TS_DELTA_S5_W2(PacketType):
|
||||
encoding = bits[4:0] == 0b11100
|
||||
delta = bits[6:5]
|
||||
_padding = bits[47:7]
|
||||
|
||||
class WAVEALLOC(PacketType): # exclude: 1 << 10
|
||||
encoding = bits[4:0] == 0b00101
|
||||
delta = bits[7:5]
|
||||
_padding = bits[19:8]
|
||||
|
||||
class TS_DELTA_S5_W3(PacketType):
|
||||
encoding = bits[4:0] == 0b00110
|
||||
delta = bits[7:5]
|
||||
_padding = bits[51:8]
|
||||
|
||||
class PERF(PacketType): # exclude: 1 << 11
|
||||
encoding = bits[4:0] == 0b10110
|
||||
delta = bits[7:5]
|
||||
arg = bits[27:8]
|
||||
|
||||
class TS_DELTA_SHORT(PacketType):
|
||||
encoding = bits[3:0] == 0b1000
|
||||
delta = bits[7:4]
|
||||
|
||||
class NOP(PacketType):
|
||||
encoding = bits[3:0] == 0b0000
|
||||
delta = None # type: ignore
|
||||
_padding = bits[3:0]
|
||||
|
||||
class TS_WAVE_STATE(PacketType):
|
||||
encoding = bits[6:0] == 0b1010001
|
||||
delta = bits[15:7]
|
||||
coarse = bits[23:16]
|
||||
@property
|
||||
def wave_interest(self) -> bool: return bool(self.coarse & 1)
|
||||
@property
|
||||
def terminate_all(self) -> bool: return bool(self.coarse & 8)
|
||||
|
||||
class EVENT(PacketType): # exclude: 1 << 7
|
||||
encoding = bits[7:0] == 0b01100001
|
||||
delta = bits[10:8]
|
||||
event = bits[23:11]
|
||||
|
||||
class EVENT_BIG(PacketType):
|
||||
encoding = bits[7:0] == 0b11100001
|
||||
delta = bits[10:8]
|
||||
event = bits[31:11]
|
||||
|
||||
class REG(PacketType):
|
||||
encoding = bits[3:0] == 0b1001
|
||||
delta = bits[6:4]
|
||||
slot = bits[9:7]
|
||||
hi_byte = bits[15:8]
|
||||
subop = bits[31:16]
|
||||
val32 = bits[63:32]
|
||||
@property
|
||||
def is_config(self) -> bool: return bool(self.hi_byte & 0x80)
|
||||
|
||||
class SNAPSHOT(PacketType):
|
||||
encoding = bits[6:0] == 0b1110001
|
||||
delta = bits[9:7]
|
||||
snap = bits[63:10]
|
||||
|
||||
class TS_DELTA_OR_MARK(PacketType):
|
||||
encoding = bits[6:0] == 0b0000001
|
||||
delta = bits[47:12]
|
||||
bit8 = bits[8:8]
|
||||
bit9 = bits[9:9]
|
||||
@property
|
||||
def is_marker(self) -> bool: return bool(self.bit9 and not self.bit8)
|
||||
|
||||
class LAYOUT_HEADER(PacketType):
|
||||
encoding = bits[6:0] == 0b0010001
|
||||
delta = None # type: ignore
|
||||
layout = bits[12:7]
|
||||
simd = bits[14:13]
|
||||
group = bits[17:15]
|
||||
sel_a = bits[31:28]
|
||||
sel_b = bits[36:33]
|
||||
flag4 = bits[59:59]
|
||||
_padding = bits[63:60]
|
||||
|
||||
class INST(PacketType):
|
||||
encoding = bits[2:0] == 0b010
|
||||
delta = bits[6:4]
|
||||
flag1 = bits[3:3]
|
||||
flag2 = bits[7:7]
|
||||
wave = bits[12:8]
|
||||
op = bits[19:13].enum(InstOp)
|
||||
|
||||
class UTILCTR(PacketType):
|
||||
encoding = bits[6:0] == 0b0110001
|
||||
delta = bits[8:7]
|
||||
ctr = bits[47:9]
|
||||
|
||||
# All packet types in encoding priority order (more specific masks first, NOP last as fallback)
|
||||
PACKET_TYPES: list[type[PacketType]] = [
|
||||
EVENT, EVENT_BIG,
|
||||
TS_DELTA_S8_W3, TS_WAVE_STATE, SNAPSHOT, TS_DELTA_OR_MARK, LAYOUT_HEADER, UTILCTR,
|
||||
IMMEDIATE_MASK, WAVERDY, WAVEEND, WAVESTART, TS_DELTA_S5_W2, WAVEALLOC, TS_DELTA_S5_W3, PERF,
|
||||
VMEMEXEC, ALUEXEC, IMMEDIATE, TS_DELTA_SHORT, REG,
|
||||
VALUINST, INST,
|
||||
NOP,
|
||||
]
|
||||
|
||||
def _build_state_table() -> tuple[bytes, dict[int, type[PacketType]]]:
|
||||
table = [len(PACKET_TYPES) - 1] * 256 # default to NOP
|
||||
opcode_to_class: dict[int, type[PacketType]] = {i: cls for i, cls in enumerate(PACKET_TYPES)}
|
||||
|
||||
for byte_val in range(256):
|
||||
for opcode, pkt_cls in enumerate(PACKET_TYPES):
|
||||
if (byte_val & pkt_cls.encoding.mask) == pkt_cls.encoding.default:
|
||||
table[byte_val] = opcode
|
||||
break
|
||||
|
||||
return bytes(table), opcode_to_class
|
||||
|
||||
STATE_TO_OPCODE, OPCODE_TO_CLASS = _build_state_table()
|
||||
|
||||
# Precompute special case opcodes
|
||||
_TS_DELTA_OR_MARK_OPCODE = next(op for op, cls in OPCODE_TO_CLASS.items() if cls is TS_DELTA_OR_MARK)
|
||||
_TS_DELTA_SHORT_OPCODE = next(op for op, cls in OPCODE_TO_CLASS.items() if cls is TS_DELTA_SHORT)
|
||||
|
||||
# Combined lookup: opcode -> (pkt_cls, nib_count, delta_lo, delta_mask, special_case)
|
||||
# special_case: 0=none, 1=TS_DELTA_OR_MARK, 2=TS_DELTA_SHORT
|
||||
_DECODE_INFO: dict[int, tuple] = {}
|
||||
for _opcode, _pkt_cls in OPCODE_TO_CLASS.items():
|
||||
_delta_field = getattr(_pkt_cls, 'delta', None)
|
||||
_delta_lo = _delta_field.lo if _delta_field else 0
|
||||
_delta_mask = _delta_field.mask if _delta_field else 0
|
||||
_special = 1 if _opcode == _TS_DELTA_OR_MARK_OPCODE else (2 if _opcode == _TS_DELTA_SHORT_OPCODE else 0)
|
||||
_DECODE_INFO[_opcode] = (_pkt_cls, _pkt_cls._size_nibbles, _delta_lo, _delta_mask, _special)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# DECODER
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
def decode(data: bytes) -> Iterator[PacketType]:
|
||||
"""Decode raw SQTT blob, yielding packet instances."""
|
||||
n, reg, pos, nib_off, nib_count, time = len(data), 0, 0, 0, 16, 0
|
||||
|
||||
while pos + ((nib_count + nib_off + 1) >> 1) <= n:
|
||||
need = nib_count - nib_off
|
||||
# 1. if unaligned, read high nibble to align
|
||||
if nib_off: reg, pos = (reg >> 4) | ((data[pos] >> 4) << 60), pos + 1
|
||||
# 2. read all full bytes at once
|
||||
if (byte_count := need >> 1):
|
||||
chunk = int.from_bytes(data[pos:pos + byte_count], 'little')
|
||||
reg, pos = (reg >> (byte_count * 8)) | (chunk << (64 - byte_count * 8)), pos + byte_count
|
||||
# 3. if odd, read low nibble
|
||||
if (nib_off := need & 1): reg = (reg >> 4) | ((data[pos] & 0xF) << 60)
|
||||
|
||||
opcode = STATE_TO_OPCODE[reg & 0xFF]
|
||||
pkt_cls, nib_count, delta_lo, delta_mask, special = _DECODE_INFO[opcode]
|
||||
delta = (reg >> delta_lo) & delta_mask
|
||||
if special == 1 and (reg >> 9) & 1 and not (reg >> 8) & 1: delta = 0 # TS_DELTA_OR_MARK marker
|
||||
elif special == 2: delta += 8 # TS_DELTA_SHORT
|
||||
time += delta
|
||||
yield pkt_cls.from_raw(reg, time)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PRINTER
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
PACKET_COLORS = {
|
||||
"INST": "WHITE", "VALUINST": "BLACK", "VMEMEXEC": "yellow", "ALUEXEC": "yellow",
|
||||
"IMMEDIATE": "YELLOW", "IMMEDIATE_MASK": "YELLOW", "WAVERDY": "cyan", "WAVEALLOC": "cyan",
|
||||
"WAVEEND": "blue", "WAVESTART": "blue", "PERF": "magenta", "EVENT": "red", "EVENT_BIG": "red",
|
||||
"REG": "green", "LAYOUT_HEADER": "white", "SNAPSHOT": "white", "UTILCTR": "green",
|
||||
}
|
||||
|
||||
def format_packet(p) -> str:
|
||||
from tinygrad.helpers import colored
|
||||
name = type(p).__name__
|
||||
if isinstance(p, INST):
|
||||
op_name = p.op.name if isinstance(p.op, InstOp) else f"0x{p.op:02x}"
|
||||
fields = f"wave={p.wave} op={op_name}" + (" flag1" if p.flag1 else "") + (" flag2" if p.flag2 else "")
|
||||
elif isinstance(p, VALUINST): fields = f"wave={p.wave}" + (" flag" if p.flag else "")
|
||||
elif isinstance(p, ALUEXEC): fields = f"src={p.src.name if isinstance(p.src, AluSrc) else p.src}"
|
||||
elif isinstance(p, VMEMEXEC): fields = f"src={p.src.name if isinstance(p.src, MemSrc) else p.src}"
|
||||
elif isinstance(p, (WAVESTART, WAVEEND)): fields = f"wave={p.wave} simd={p.simd} cu={p.cu}"
|
||||
elif hasattr(p, '_fields'):
|
||||
fields = " ".join(f"{k}=0x{getattr(p, k):x}" if k in {'snap', 'val32'} else f"{k}={getattr(p, k)}"
|
||||
for k in p._fields if not k.startswith('_') and k not in {'delta', 'encoding'})
|
||||
else: fields = ""
|
||||
return f"{p._time:8}: {colored(f'{name:18}', PACKET_COLORS.get(name, 'white'))} {fields}"
|
||||
|
||||
def print_packets(packets) -> None:
|
||||
skip = {"NOP", "TS_DELTA_SHORT", "TS_WAVE_STATE", "TS_DELTA_OR_MARK", "TS_DELTA_S5_W2", "TS_DELTA_S5_W3", "TS_DELTA_S8_W3", "REG", "EVENT"}
|
||||
for p in packets:
|
||||
if type(p).__name__ not in skip: print(format_packet(p))
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys, pickle
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: python sqtt.py <pkl_file>")
|
||||
sys.exit(1)
|
||||
with open(sys.argv[1], "rb") as f:
|
||||
data = pickle.load(f)
|
||||
sqtt_events = [e for e in data if type(e).__name__ == "ProfileSQTTEvent"]
|
||||
for i, event in enumerate(sqtt_events):
|
||||
print(f"\n=== event {i} ===")
|
||||
print_packets(decode(event.blob))
|
||||
@@ -1,192 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Benchmark comparing Python vs Rust RDNA3 emulators on real tinygrad kernels."""
|
||||
import ctypes, time, os
|
||||
from pathlib import Path
|
||||
|
||||
# Set AMD=1 before importing tinygrad
|
||||
os.environ["AMD"] = "1"
|
||||
|
||||
from extra.assembly.amd.emu import run_asm as python_run_asm, set_valid_mem_ranges, decode_program
|
||||
|
||||
REMU_PATH = Path(__file__).parents[3] / "remu/target/release/libremu.so"
|
||||
if not REMU_PATH.exists():
|
||||
REMU_PATH = Path(__file__).parents[3] / "remu/target/release/libremu.dylib"
|
||||
|
||||
def get_rust_remu():
|
||||
"""Load the Rust libremu shared library."""
|
||||
if not REMU_PATH.exists(): return None
|
||||
remu = ctypes.CDLL(str(REMU_PATH))
|
||||
remu.run_asm.restype = ctypes.c_int32
|
||||
remu.run_asm.argtypes = [ctypes.c_void_p, ctypes.c_uint32, ctypes.c_uint32, ctypes.c_uint32, ctypes.c_uint32,
|
||||
ctypes.c_uint32, ctypes.c_uint32, ctypes.c_uint32, ctypes.c_void_p]
|
||||
return remu
|
||||
|
||||
def count_instructions(kernel: bytes) -> int:
|
||||
"""Count instructions in a kernel."""
|
||||
return len(decode_program(kernel))
|
||||
|
||||
def setup_buffers(buf_sizes: list[int], init_data: dict[int, bytes] | None = None):
|
||||
"""Allocate buffers and return args pointer + valid ranges."""
|
||||
if init_data is None: init_data = {}
|
||||
buffers = []
|
||||
for i, size in enumerate(buf_sizes):
|
||||
padded = ((size + 15) // 16) * 16 + 16
|
||||
data = init_data.get(i, b'\x00' * padded)
|
||||
data_list = list(data) + [0] * (padded - len(data))
|
||||
buf = (ctypes.c_uint8 * padded)(*data_list[:padded])
|
||||
buffers.append(buf)
|
||||
args = (ctypes.c_uint64 * len(buffers))(*[ctypes.addressof(b) for b in buffers])
|
||||
args_ptr = ctypes.addressof(args)
|
||||
ranges = {(ctypes.addressof(b), len(b)) for b in buffers}
|
||||
ranges.add((args_ptr, ctypes.sizeof(args)))
|
||||
return buffers, args, args_ptr, ranges
|
||||
|
||||
def benchmark_emulator(name: str, run_fn, kernel: bytes, global_size, local_size, args_ptr, rsrc2: int, iterations: int = 5):
|
||||
"""Benchmark an emulator and return average time."""
|
||||
gx, gy, gz = global_size
|
||||
lx, ly, lz = local_size
|
||||
kernel_buf = (ctypes.c_char * len(kernel)).from_buffer_copy(kernel)
|
||||
lib_ptr = ctypes.addressof(kernel_buf)
|
||||
|
||||
# Warmup
|
||||
run_fn(lib_ptr, len(kernel), gx, gy, gz, lx, ly, lz, args_ptr, rsrc2)
|
||||
|
||||
# Timed runs
|
||||
times = []
|
||||
for _ in range(iterations):
|
||||
start = time.perf_counter()
|
||||
result = run_fn(lib_ptr, len(kernel), gx, gy, gz, lx, ly, lz, args_ptr, rsrc2)
|
||||
end = time.perf_counter()
|
||||
if result != 0:
|
||||
print(f" {name} returned error: {result}")
|
||||
return None
|
||||
times.append(end - start)
|
||||
|
||||
return sum(times) / len(times)
|
||||
|
||||
def get_tinygrad_kernel(op_name: str) -> tuple[bytes, tuple, tuple, list[int], dict[int, bytes], int] | None:
|
||||
"""Get a real tinygrad kernel by operation name. Returns (code, global_size, local_size, buf_sizes, buf_data, rsrc2)."""
|
||||
try:
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.runtime.support.elf import elf_loader
|
||||
from tinygrad.runtime.autogen import hsa
|
||||
import numpy as np
|
||||
np.random.seed(42)
|
||||
|
||||
ops = {
|
||||
"add": lambda: Tensor.empty(1024) + Tensor.empty(1024),
|
||||
"mul": lambda: Tensor.empty(1024) * Tensor.empty(1024),
|
||||
"matmul_small": lambda: Tensor.empty(16, 16) @ Tensor.empty(16, 16),
|
||||
"matmul_medium": lambda: Tensor.empty(64, 64) @ Tensor.empty(64, 64),
|
||||
"reduce_sum": lambda: Tensor.empty(4096).sum(),
|
||||
"reduce_max": lambda: Tensor.empty(4096).max(),
|
||||
"softmax": lambda: Tensor.empty(256).softmax(),
|
||||
"layernorm": lambda: Tensor.empty(32, 64).layernorm(),
|
||||
"conv2d": lambda: Tensor.empty(1, 4, 16, 16).conv2d(Tensor.empty(4, 4, 3, 3)),
|
||||
"gelu": lambda: Tensor.empty(1024).gelu(),
|
||||
"exp": lambda: Tensor.empty(1024).exp(),
|
||||
"sin": lambda: Tensor.empty(1024).sin(),
|
||||
}
|
||||
|
||||
if op_name not in ops: return None
|
||||
out = ops[op_name]()
|
||||
sched = out.schedule()
|
||||
|
||||
for ei in sched:
|
||||
lowered = ei.lower()
|
||||
if ei.ast.op.name == 'SINK' and lowered.prg and lowered.prg.p.lib:
|
||||
lib = bytes(lowered.prg.p.lib)
|
||||
image = memoryview(bytearray(lib))
|
||||
_, sections, _ = elf_loader(lib)
|
||||
rodata_entry = next((sh.header.sh_addr for sh in sections if sh.name == ".rodata"), -1)
|
||||
for sec in sections:
|
||||
if sec.name == '.text':
|
||||
buf_sizes = [b.nbytes for b in lowered.bufs]
|
||||
# Get initial data from numpy arrays if available
|
||||
buf_data = {}
|
||||
for i, buf in enumerate(lowered.bufs):
|
||||
if hasattr(buf, 'base') and buf.base is not None and hasattr(buf.base, '_buf'):
|
||||
try: buf_data[i] = bytes(buf.base._buf)
|
||||
except: pass
|
||||
# Extract rsrc2 from ELF (same as ops_amd.py)
|
||||
group_segment_size = image[rodata_entry:rodata_entry+4].cast("I")[0]
|
||||
lds_size = ((group_segment_size + 511) // 512) & 0x1FF
|
||||
code = hsa.amd_kernel_code_t.from_buffer_copy(bytes(image[rodata_entry:rodata_entry+256]) + b'\x00'*256)
|
||||
rsrc2 = code.compute_pgm_rsrc2 | (lds_size << 15)
|
||||
return (bytes(sec.content), tuple(lowered.prg.p.global_size), tuple(lowered.prg.p.local_size), buf_sizes, buf_data, rsrc2)
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f" Error getting kernel: {e}")
|
||||
return None
|
||||
|
||||
TINYGRAD_TESTS = ["add", "mul", "reduce_sum", "softmax", "exp", "gelu", "matmul_small"]
|
||||
|
||||
def main():
|
||||
import argparse
|
||||
parser = argparse.ArgumentParser(description="Benchmark RDNA3 emulators")
|
||||
parser.add_argument("--iterations", type=int, default=3, help="Number of iterations per benchmark")
|
||||
args = parser.parse_args()
|
||||
|
||||
rust_remu = get_rust_remu()
|
||||
if rust_remu is None:
|
||||
print("Rust libremu not found. Build with: cargo build --release --manifest-path extra/remu/Cargo.toml")
|
||||
print("Running Python-only benchmarks...\n")
|
||||
|
||||
print("=" * 90)
|
||||
print("RDNA3 Emulator Benchmark: Python vs Rust")
|
||||
print("=" * 90)
|
||||
|
||||
results = []
|
||||
|
||||
print("\n[TINYGRAD KERNELS]")
|
||||
print("-" * 90)
|
||||
|
||||
for op_name in TINYGRAD_TESTS:
|
||||
print(f"\n{op_name}:", end=" ", flush=True)
|
||||
kernel_info = get_tinygrad_kernel(op_name)
|
||||
if kernel_info is None:
|
||||
print("failed to compile")
|
||||
continue
|
||||
|
||||
kernel, global_size, local_size, buf_sizes, buf_data, rsrc2 = kernel_info
|
||||
n_insts = count_instructions(kernel)
|
||||
n_workgroups = global_size[0] * global_size[1] * global_size[2]
|
||||
n_threads = local_size[0] * local_size[1] * local_size[2]
|
||||
total_work = n_insts * n_workgroups * n_threads
|
||||
|
||||
print(f"{n_insts} insts × {n_workgroups} WGs × {n_threads} threads = {total_work:,} ops")
|
||||
|
||||
buffers, args_arr, args_ptr, ranges = setup_buffers(buf_sizes, buf_data)
|
||||
set_valid_mem_ranges(ranges)
|
||||
|
||||
py_time = benchmark_emulator("Python", python_run_asm, kernel, global_size, local_size, args_ptr, rsrc2, args.iterations)
|
||||
rust_time = benchmark_emulator("Rust", rust_remu.run_asm, kernel, global_size, local_size, args_ptr, rsrc2, args.iterations) if rust_remu else None
|
||||
|
||||
if py_time:
|
||||
py_rate = total_work / py_time / 1e6
|
||||
print(f" Python: {py_time*1000:8.3f} ms ({py_rate:7.2f} M ops/s)")
|
||||
if rust_time:
|
||||
rust_rate = total_work / rust_time / 1e6
|
||||
speedup = py_time / rust_time if py_time else 0
|
||||
print(f" Rust: {rust_time*1000:8.3f} ms ({rust_rate:7.2f} M ops/s) [{speedup:.1f}x faster]")
|
||||
|
||||
results.append((op_name, n_insts, n_workgroups, py_time, rust_time))
|
||||
|
||||
# Summary table
|
||||
print("\n" + "=" * 90)
|
||||
print("SUMMARY")
|
||||
print("=" * 90)
|
||||
print(f"{'Name':<25} {'Insts':<8} {'WGs':<6} {'Python (ms)':<14} {'Rust (ms)':<14} {'Speedup':<10}")
|
||||
print("-" * 90)
|
||||
|
||||
for name, n_insts, n_wgs, py_time, rust_time in results:
|
||||
py_ms = f"{py_time*1000:.3f}" if py_time else "error"
|
||||
if rust_time:
|
||||
rust_ms = f"{rust_time*1000:.3f}"
|
||||
speedup = f"{py_time/rust_time:.1f}x" if py_time else "N/A"
|
||||
else:
|
||||
rust_ms, speedup = "N/A", "N/A"
|
||||
print(f"{name:<25} {n_insts:<8} {n_wgs:<6} {py_ms:<14} {rust_ms:<14} {speedup:<10}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1,196 +0,0 @@
|
||||
# Usability tests for the RDNA3 ASM DSL
|
||||
# These tests demonstrate how the DSL *should* work for a good user experience
|
||||
# Currently many of these tests fail - they document desired behavior
|
||||
|
||||
import unittest
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
from extra.assembly.amd.dsl import Inst, RawImm, SGPR, VGPR
|
||||
|
||||
class TestRegisterSliceSyntax(unittest.TestCase):
|
||||
"""
|
||||
Issue: Register slice syntax should use AMD assembly convention (inclusive end).
|
||||
|
||||
In AMD assembly, s[4:7] means registers s4, s5, s6, s7 (4 registers, inclusive).
|
||||
The DSL should match this convention so that:
|
||||
- s[4:7] gives 4 registers
|
||||
- Disassembler output can be copied directly back into DSL code
|
||||
|
||||
Fix: Change _RegFactory.__getitem__ to use inclusive end:
|
||||
key.stop - key.start + 1 (instead of key.stop - key.start)
|
||||
"""
|
||||
def test_register_slice_count(self):
|
||||
# s[4:7] should give 4 registers: s4, s5, s6, s7 (AMD convention, inclusive)
|
||||
reg = s[4:7]
|
||||
self.assertEqual(reg.count, 4, "s[4:7] should give 4 registers (s4, s5, s6, s7)")
|
||||
|
||||
def test_register_slice_roundtrip(self):
|
||||
# Round-trip: DSL -> disasm -> DSL should preserve register count
|
||||
reg = s[4:7] # 4 registers in AMD convention
|
||||
inst = s_load_b128(reg, s[0:1], NULL, 0)
|
||||
disasm = inst.disasm()
|
||||
# Disasm shows s[4:7] - user should be able to copy this back
|
||||
self.assertIn("s[4:7]", disasm)
|
||||
# And s[4:7] in DSL should give the same 4 registers
|
||||
reg_from_disasm = s[4:7]
|
||||
self.assertEqual(reg_from_disasm.count, 4, "s[4:7] from disasm should give 4 registers")
|
||||
|
||||
|
||||
class TestReprReadability(unittest.TestCase):
|
||||
"""
|
||||
Issue: repr() leaks internal RawImm type and omits zero-valued fields.
|
||||
|
||||
When you create v_mov_b32_e32(v[0], v[1]), the repr shows:
|
||||
VOP1(op=1, src0=RawImm(257))
|
||||
|
||||
Problems:
|
||||
1. vdst=v[0] is omitted because 0 is treated as "default"
|
||||
2. src0 shows RawImm(257) instead of v[1]
|
||||
3. User sees encoded values (257 = 256 + 1) instead of register names
|
||||
|
||||
Expected repr: VOP1(op=1, vdst=v[0], src0=v[1])
|
||||
"""
|
||||
def test_repr_shows_registers_not_raw_imm(self):
|
||||
inst = v_mov_b32_e32(v[0], v[1])
|
||||
# Should show v[1], not RawImm(257)
|
||||
self.assertNotIn("RawImm", repr(inst), "repr should not expose RawImm internal type")
|
||||
self.assertIn("v[1]", repr(inst), "repr should show register name")
|
||||
|
||||
def test_repr_includes_zero_dst(self):
|
||||
inst = v_mov_b32_e32(v[0], v[1])
|
||||
# v[0] is a valid destination register, should be shown
|
||||
self.assertIn("vdst", repr(inst), "repr should include vdst even when 0")
|
||||
|
||||
def test_repr_roundtrip(self):
|
||||
# repr should produce something that can be eval'd back
|
||||
inst = v_mov_b32_e32(v[0], v[1])
|
||||
# This would require repr to output valid Python, e.g.:
|
||||
# "VOP1(op=VOP1Op.V_MOV_B32, vdst=v[0], src0=v[1])"
|
||||
r = repr(inst)
|
||||
# At minimum, it should be human-readable
|
||||
self.assertIn("v[", r, "repr should show register syntax")
|
||||
|
||||
|
||||
class TestInstructionEquality(unittest.TestCase):
|
||||
"""
|
||||
Issue: No __eq__ method - instruction comparison requires repr() workaround.
|
||||
|
||||
Two identical instructions should compare equal with ==, but currently:
|
||||
inst1 == inst2 returns False
|
||||
|
||||
The test_handwritten.py works around this with:
|
||||
self.assertEqual(repr(self.inst), repr(reasm))
|
||||
"""
|
||||
def test_identical_instructions_equal(self):
|
||||
inst1 = v_mov_b32_e32(v[0], v[1])
|
||||
inst2 = v_mov_b32_e32(v[0], v[1])
|
||||
self.assertEqual(inst1, inst2, "identical instructions should be equal")
|
||||
|
||||
def test_different_instructions_not_equal(self):
|
||||
inst1 = v_mov_b32_e32(v[0], v[1])
|
||||
inst2 = v_mov_b32_e32(v[0], v[2])
|
||||
self.assertNotEqual(inst1, inst2, "different instructions should not be equal")
|
||||
|
||||
|
||||
class TestVOPDHelperSignature(unittest.TestCase):
|
||||
"""
|
||||
Issue: VOPD helper functions have confusing semantics.
|
||||
|
||||
v_dual_mul_f32 is defined as:
|
||||
v_dual_mul_f32 = functools.partial(VOPD, VOPDOp.V_DUAL_MUL_F32)
|
||||
|
||||
This binds VOPDOp.V_DUAL_MUL_F32 to the FIRST positional arg of VOPD.__init__,
|
||||
which is 'opx'. So v_dual_mul_f32 sets the X operation.
|
||||
|
||||
But then test_dual_mul in test_handwritten.py does:
|
||||
v_dual_mul_f32(VOPDOp.V_DUAL_MUL_F32, vdstx=v[0], ...)
|
||||
|
||||
This passes V_DUAL_MUL_F32 as the SECOND positional arg (opy), making both
|
||||
X and Y operations the same. This is confusing because:
|
||||
1. The function name suggests it handles the X operation
|
||||
2. But you still pass an opcode as the first arg (which becomes opy)
|
||||
|
||||
Expected: Either make the helper fully specify both ops, or make the
|
||||
signature clearer about what the positional arg means.
|
||||
"""
|
||||
def test_vopd_helper_opy_should_be_required(self):
|
||||
# Using only keyword args "works" but opy silently defaults to 0
|
||||
inst = v_dual_mul_f32(vdstx=v[0], vdsty=v[1], srcx0=v[2], vsrcx1=v[3], srcy0=v[4], vsrcy1=v[5])
|
||||
self.assertEqual(inst.opx, VOPDOp.V_DUAL_MUL_F32)
|
||||
# Bug: opy defaults to 0 (V_DUAL_FMAC_F32) silently - should require explicit opy
|
||||
# This test documents the bug - it should fail once fixed
|
||||
self.assertNotEqual(inst.opy, VOPDOp.V_DUAL_FMAC_F32, "opy should not silently default to FMAC")
|
||||
|
||||
def test_vopd_helper_positional_arg_is_opy(self):
|
||||
# The first positional arg after the partial becomes opy, not a second opx
|
||||
inst = v_dual_mul_f32(VOPDOp.V_DUAL_MOV_B32, vdstx=v[0], vdsty=v[1], srcx0=v[2], vsrcx1=v[3], srcy0=v[4], vsrcy1=v[5])
|
||||
self.assertEqual(inst.opx, VOPDOp.V_DUAL_MUL_F32) # From partial
|
||||
self.assertEqual(inst.opy, VOPDOp.V_DUAL_MOV_B32) # From first positional arg
|
||||
|
||||
|
||||
class TestFieldAccessPreservesType(unittest.TestCase):
|
||||
"""
|
||||
Issue: Field access loses type information.
|
||||
|
||||
After creating an instruction, accessing fields returns encoded int values:
|
||||
inst = v_mov_b32_e32(v[0], v[1])
|
||||
inst.vdst # returns 0, not VGPR(0)
|
||||
|
||||
This makes it impossible to round-trip register types through field access.
|
||||
"""
|
||||
def test_vdst_returns_register(self):
|
||||
inst = v_mov_b32_e32(v[5], v[1])
|
||||
vdst = inst.vdst
|
||||
# Should return a VGPR, not an int
|
||||
self.assertIsInstance(vdst, (VGPR, int), "vdst should return VGPR or at least be usable")
|
||||
# Ideally: self.assertIsInstance(vdst, VGPR)
|
||||
|
||||
def test_src_returns_register_for_vgpr_source(self):
|
||||
inst = v_mov_b32_e32(v[0], v[1])
|
||||
# src0 is encoded as 257 (256 + 1 for v1)
|
||||
# Ideally it should decode back to v[1]
|
||||
src0_raw = inst._values.get('src0')
|
||||
# Currently returns RawImm(257), should return VGPR(1) or similar
|
||||
self.assertNotIsInstance(src0_raw, RawImm, "source should not be RawImm internally")
|
||||
|
||||
|
||||
class TestArgumentDiscoverability(unittest.TestCase):
|
||||
"""
|
||||
Issue: No clear signature for positional arguments.
|
||||
|
||||
inspect.signature(s_load_b128) shows: (*args, literal=None, **kwargs)
|
||||
|
||||
Users have no way to know the argument order without reading source code.
|
||||
The order is implicitly defined by the class field definition order.
|
||||
|
||||
Possible fixes:
|
||||
1. Add explicit parameter names to functools.partial
|
||||
2. Generate type stubs with proper signatures
|
||||
3. Add docstrings listing the expected arguments
|
||||
"""
|
||||
def test_signature_has_named_params(self):
|
||||
import inspect
|
||||
sig = inspect.signature(s_load_b128)
|
||||
params = list(sig.parameters.keys())
|
||||
# Currently: ['args', 'literal', 'kwargs'] (from *args, literal=None, **kwargs)
|
||||
# Expected: something like ['sdata', 'sbase', 'soffset', 'offset', 'literal']
|
||||
self.assertIn('sdata', params, "signature should show field names")
|
||||
|
||||
|
||||
class TestSpecialConstants(unittest.TestCase):
|
||||
"""
|
||||
Issue: NULL and other constants are IntEnum values that might be confusing.
|
||||
|
||||
NULL = SrcEnum.NULL = 124, but users might expect NULL to be a special object
|
||||
that clearly represents "no register" rather than a magic number.
|
||||
"""
|
||||
def test_null_has_clear_repr(self):
|
||||
# NULL should have a clear string representation
|
||||
self.assertIn("NULL", str(NULL) or repr(NULL), "NULL should be clearly identifiable")
|
||||
|
||||
def test_null_is_distinguishable_from_int(self):
|
||||
# NULL should be distinguishable from the raw integer 124
|
||||
self.assertNotEqual(type(NULL), int, "NULL should not be plain int")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -1,66 +0,0 @@
|
||||
"""Shared test helpers for RDNA3 tests."""
|
||||
import shutil
|
||||
from dataclasses import dataclass
|
||||
|
||||
@dataclass
|
||||
class KernelInfo:
|
||||
code: bytes
|
||||
global_size: tuple[int, int, int]
|
||||
local_size: tuple[int, int, int]
|
||||
buf_idxs: list[int] # indices into shared buffer pool
|
||||
buf_sizes: list[int] # sizes for each buffer index
|
||||
|
||||
# LLVM tool detection (shared across test files)
|
||||
def get_llvm_mc():
|
||||
"""Find llvm-mc executable, preferring newer versions."""
|
||||
for p in ['llvm-mc', 'llvm-mc-21', 'llvm-mc-20']:
|
||||
if shutil.which(p): return p
|
||||
raise FileNotFoundError("llvm-mc not found")
|
||||
|
||||
def get_llvm_objdump():
|
||||
"""Find llvm-objdump executable, preferring newer versions."""
|
||||
for p in ['llvm-objdump', 'llvm-objdump-21', 'llvm-objdump-20']:
|
||||
if shutil.which(p): return p
|
||||
raise FileNotFoundError("llvm-objdump not found")
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# EXECUTION CONTEXT (for testing compiled pseudocode)
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class ExecContext:
|
||||
"""Context for running compiled pseudocode in tests."""
|
||||
def __init__(self, s0=0, s1=0, s2=0, d0=0, scc=0, vcc=0, lane=0, exec_mask=0xffffffff, literal=0, vgprs=None, src0_idx=0, vdst_idx=0):
|
||||
from extra.assembly.amd.pcode import Reg, MASK32, MASK64, TypedView
|
||||
self._Reg, self._MASK64, self._TypedView = Reg, MASK64, TypedView
|
||||
self.S0, self.S1, self.S2 = Reg(s0), Reg(s1), Reg(s2)
|
||||
self.D0, self.D1 = Reg(d0), Reg(0)
|
||||
self.SCC, self.VCC, self.EXEC = Reg(scc), Reg(vcc), Reg(exec_mask)
|
||||
self.tmp, self.saveexec = Reg(0), Reg(exec_mask)
|
||||
self.lane, self.laneId, self.literal = lane, lane, literal
|
||||
self.SIMM16, self.SIMM32 = Reg(literal), Reg(literal)
|
||||
self.VGPR = vgprs if vgprs is not None else {}
|
||||
self.SRC0, self.VDST = Reg(src0_idx), Reg(vdst_idx)
|
||||
|
||||
def run(self, code: str):
|
||||
"""Execute compiled code."""
|
||||
import extra.assembly.amd.pcode as pcode
|
||||
ns = {k: getattr(pcode, k) for k in dir(pcode) if not k.startswith('_')}
|
||||
# Also include underscore-prefixed helpers that compiled pseudocode uses
|
||||
for k in ['_pack', '_pack32']:
|
||||
if hasattr(pcode, k): ns[k] = getattr(pcode, k)
|
||||
ns.update({
|
||||
'S0': self.S0, 'S1': self.S1, 'S2': self.S2, 'D0': self.D0, 'D1': self.D1,
|
||||
'SCC': self.SCC, 'VCC': self.VCC, 'EXEC': self.EXEC,
|
||||
'EXEC_LO': self._TypedView(self.EXEC, 31, 0), 'EXEC_HI': self._TypedView(self.EXEC, 63, 32),
|
||||
'tmp': self.tmp, 'saveexec': self.saveexec,
|
||||
'lane': self.lane, 'laneId': self.laneId, 'literal': self.literal,
|
||||
'SIMM16': self.SIMM16, 'SIMM32': self.SIMM32, 'VGPR': self.VGPR, 'SRC0': self.SRC0, 'VDST': self.VDST,
|
||||
})
|
||||
exec(code, ns)
|
||||
def _sync(ctx_reg, ns_val):
|
||||
if isinstance(ns_val, self._Reg): ctx_reg._val = ns_val._val
|
||||
else: ctx_reg._val = int(ns_val) & self._MASK64
|
||||
for name in ('SCC', 'VCC', 'EXEC', 'D0', 'D1', 'tmp', 'saveexec'):
|
||||
if ns.get(name) is not getattr(self, name): _sync(getattr(self, name), ns[name])
|
||||
|
||||
def result(self) -> dict: return {"d0": self.D0._val, "scc": self.SCC._val & 1}
|
||||
@@ -1,381 +0,0 @@
|
||||
"""Tests for SOP instructions - scalar operations.
|
||||
|
||||
Includes: s_add_u32, s_mov_b32, s_and_b32, s_or_b32, s_quadmask_b32, s_wqm_b32,
|
||||
s_cbranch_vccnz, s_cbranch_vccz
|
||||
"""
|
||||
import unittest
|
||||
from extra.assembly.amd.test.hw.helpers import *
|
||||
|
||||
class TestBasicScalar(unittest.TestCase):
|
||||
"""Tests for basic scalar operations."""
|
||||
|
||||
def test_s_add_u32(self):
|
||||
"""S_ADD_U32 adds two scalar values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 100),
|
||||
s_mov_b32(s[1], 200),
|
||||
s_add_u32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 300)
|
||||
|
||||
def test_s_add_u32_carry(self):
|
||||
"""S_ADD_U32 sets SCC on overflow."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 64),
|
||||
s_not_b32(s[0], s[0]), # ~64 = 0xffffffbf
|
||||
s_mov_b32(s[1], 64),
|
||||
s_add_u32(s[2], s[0], s[1]), # 0xffffffbf + 64 = 0xffffffff
|
||||
s_mov_b32(s[3], 1),
|
||||
s_add_u32(s[4], s[2], s[3]), # 0xffffffff + 1 = overflow
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[4], 0)
|
||||
self.assertEqual(st.scc, 1)
|
||||
|
||||
def test_s_brev_b32(self):
|
||||
"""S_BREV_B32 reverses bits of a 32-bit value."""
|
||||
# 10 = 0b00000000000000000000000000001010
|
||||
# reversed = 0b01010000000000000000000000000000 = 0x50000000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 10),
|
||||
s_brev_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0x50000000)
|
||||
|
||||
def test_s_brev_b32_all_ones(self):
|
||||
"""S_BREV_B32 with all ones stays all ones."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFFFFFFFF),
|
||||
s_brev_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0xFFFFFFFF)
|
||||
|
||||
def test_s_brev_b32_single_bit(self):
|
||||
"""S_BREV_B32 with bit 0 set becomes bit 31."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 1),
|
||||
s_brev_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0x80000000)
|
||||
|
||||
|
||||
class TestQuadmaskWqm(unittest.TestCase):
|
||||
"""Tests for S_QUADMASK_B32 and S_WQM_B32."""
|
||||
|
||||
def test_s_quadmask_b32_all_quads_active(self):
|
||||
"""S_QUADMASK_B32 with all quads active."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFFFFFFFF), # All lanes active
|
||||
s_quadmask_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# Each quad (4 lanes) with any bit set -> 1 bit in result
|
||||
# 32 lanes = 8 quads, all active -> 0xFF
|
||||
self.assertEqual(st.sgpr[1], 0xFF)
|
||||
|
||||
def test_s_quadmask_b32_alternating_quads(self):
|
||||
"""S_QUADMASK_B32 with alternating quads active."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x0F0F0F0F), # Quads 0,2,4,6 active
|
||||
s_quadmask_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# Quads 0,2,4,6 have at least one bit -> 0b01010101 = 0x55
|
||||
self.assertEqual(st.sgpr[1], 0x55)
|
||||
|
||||
def test_s_quadmask_b32_no_quads_active(self):
|
||||
"""S_QUADMASK_B32 with no quads active."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0),
|
||||
s_quadmask_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0)
|
||||
|
||||
def test_s_quadmask_b32_single_lane_per_quad(self):
|
||||
"""S_QUADMASK_B32 with single lane active in each quad."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x11111111), # Bit 0 of each nibble
|
||||
s_quadmask_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# All 8 quads have at least one lane -> 0xFF
|
||||
self.assertEqual(st.sgpr[1], 0xFF)
|
||||
|
||||
def test_s_wqm_b32_all_active(self):
|
||||
"""S_WQM_B32 with all lanes active returns all 1s."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFFFFFFFF),
|
||||
s_wqm_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0xFFFFFFFF)
|
||||
|
||||
def test_s_wqm_b32_alternating_quads(self):
|
||||
"""S_WQM_B32 with single lane per quad expands to full quads."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x11111111), # One lane per quad
|
||||
s_wqm_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# Each quad with any bit expands to all 4 bits
|
||||
self.assertEqual(st.sgpr[1], 0xFFFFFFFF)
|
||||
|
||||
def test_s_wqm_b32_zero(self):
|
||||
"""S_WQM_B32 with zero input returns zero."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0),
|
||||
s_wqm_b32(s[1], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0)
|
||||
|
||||
|
||||
class TestBranch(unittest.TestCase):
|
||||
"""Tests for branch instructions."""
|
||||
|
||||
def test_cbranch_vccnz_ignores_vcc_hi(self):
|
||||
"""S_CBRANCH_VCCNZ should only check VCC_LO in wave32."""
|
||||
instructions = [
|
||||
# Set VCC_LO = 0, VCC_HI = 1
|
||||
s_mov_b32(VCC_LO, 0),
|
||||
s_mov_b32(VCC_HI, 1),
|
||||
v_mov_b32_e32(v[0], 0),
|
||||
# If VCC_HI is incorrectly used, branch will be taken
|
||||
s_cbranch_vccnz(1), # Skip next instruction if VCC != 0
|
||||
v_mov_b32_e32(v[0], 42), # This should execute
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][0], 42, "Branch should NOT be taken (VCC_LO is 0)")
|
||||
|
||||
def test_cbranch_vccz_ignores_vcc_hi(self):
|
||||
"""S_CBRANCH_VCCZ should only check VCC_LO in wave32."""
|
||||
instructions = [
|
||||
# Set VCC_LO = 1, VCC_HI = 0
|
||||
s_mov_b32(VCC_LO, 1),
|
||||
s_mov_b32(VCC_HI, 0),
|
||||
v_mov_b32_e32(v[0], 0),
|
||||
# If VCC_HI is incorrectly used, branch will be taken
|
||||
s_cbranch_vccz(1), # Skip next instruction if VCC == 0
|
||||
v_mov_b32_e32(v[0], 42), # This should execute
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][0], 42, "Branch should NOT be taken (VCC_LO is 1)")
|
||||
|
||||
def test_cbranch_vccnz_branches_on_vcc_lo(self):
|
||||
"""S_CBRANCH_VCCNZ branches when VCC_LO is non-zero."""
|
||||
instructions = [
|
||||
s_mov_b32(VCC_LO, 1),
|
||||
v_mov_b32_e32(v[0], 0),
|
||||
s_cbranch_vccnz(1), # Skip next instruction if VCC != 0
|
||||
v_mov_b32_e32(v[0], 42), # This should be skipped
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][0], 0, "Branch should be taken (VCC_LO is 1)")
|
||||
|
||||
|
||||
class Test64BitLiterals(unittest.TestCase):
|
||||
"""Tests for 64-bit literal encoding in instructions."""
|
||||
|
||||
def test_64bit_literal_negative_encoding(self):
|
||||
"""64-bit literal -2^32 encodes correctly."""
|
||||
lit = -4294967296.0 # -2^32
|
||||
lit_bits = f2i64(lit)
|
||||
instructions = [
|
||||
s_mov_b32(s[0], lit_bits & 0xffffffff),
|
||||
s_mov_b32(s[1], lit_bits >> 32),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = i642f(st.vgpr[0][0] | (st.vgpr[0][1] << 32))
|
||||
self.assertAlmostEqual(result, -4294967296.0, places=5)
|
||||
|
||||
class TestSCCBehavior(unittest.TestCase):
|
||||
"""Tests for SCC condition code behavior."""
|
||||
|
||||
def test_scc_from_s_cmp(self):
|
||||
"""SCC should be set by scalar compare."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 10),
|
||||
s_cmp_eq_u32(s[0], 10),
|
||||
s_cselect_b32(s[1], 1, 0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 1, "SCC should be true")
|
||||
self.assertEqual(st.scc, 1)
|
||||
|
||||
def test_scc_clear(self):
|
||||
"""SCC should be cleared by failing compare."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 10),
|
||||
s_cmp_eq_u32(s[0], 20),
|
||||
s_cselect_b32(s[1], 1, 0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0, "SCC should be false")
|
||||
self.assertEqual(st.scc, 0)
|
||||
|
||||
|
||||
class TestSignedArithmetic(unittest.TestCase):
|
||||
"""Tests for S_ADD_I32, S_SUB_I32 and their SCC overflow behavior."""
|
||||
|
||||
def test_s_add_i32_no_overflow(self):
|
||||
"""S_ADD_I32: 1 + 1 = 2, no overflow, SCC=0."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 1),
|
||||
s_add_i32(s[1], s[0], 1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 2)
|
||||
self.assertEqual(st.scc, 0, "No overflow, SCC should be 0")
|
||||
|
||||
def test_s_add_i32_positive_overflow(self):
|
||||
"""S_ADD_I32: MAX_INT + 1 overflows, SCC=1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7FFFFFFF), # MAX_INT
|
||||
s_add_i32(s[1], s[0], 1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[1], 0x80000000) # Wraps to MIN_INT
|
||||
self.assertEqual(st.scc, 1, "Overflow, SCC should be 1")
|
||||
|
||||
def test_s_add_i32_negative_no_overflow(self):
|
||||
"""S_ADD_I32: -10 + 20 = 10, no overflow."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFFFFFFF6), # -10 in two's complement
|
||||
s_mov_b32(s[1], 20),
|
||||
s_add_i32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 10)
|
||||
self.assertEqual(st.scc, 0)
|
||||
|
||||
def test_s_add_i32_negative_overflow(self):
|
||||
"""S_ADD_I32: MIN_INT + (-1) underflows, SCC=1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x80000000), # MIN_INT
|
||||
s_mov_b32(s[1], 0xFFFFFFFF), # -1
|
||||
s_add_i32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 0x7FFFFFFF) # Wraps to MAX_INT
|
||||
self.assertEqual(st.scc, 1, "Underflow, SCC should be 1")
|
||||
|
||||
def test_s_sub_i32_no_overflow(self):
|
||||
"""S_SUB_I32: 10 - 5 = 5, no overflow."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 10),
|
||||
s_mov_b32(s[1], 5),
|
||||
s_sub_i32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 5)
|
||||
self.assertEqual(st.scc, 0)
|
||||
|
||||
def test_s_sub_i32_overflow(self):
|
||||
"""S_SUB_I32: MAX_INT - (-1) overflows, SCC=1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7FFFFFFF), # MAX_INT
|
||||
s_mov_b32(s[1], 0xFFFFFFFF), # -1
|
||||
s_sub_i32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 0x80000000) # Wraps to MIN_INT
|
||||
self.assertEqual(st.scc, 1, "Overflow, SCC should be 1")
|
||||
|
||||
def test_s_mul_hi_u32(self):
|
||||
"""S_MUL_HI_U32: high 32 bits of u32 * u32."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x80000000), # 2^31
|
||||
s_mov_b32(s[1], 4),
|
||||
s_mul_hi_u32(s[2], s[0], s[1]), # (2^31 * 4) >> 32 = 2
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 2)
|
||||
|
||||
def test_s_mul_i32(self):
|
||||
"""S_MUL_I32: signed multiply low 32 bits."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFFFFFFFF), # -1
|
||||
s_mov_b32(s[1], 10),
|
||||
s_mul_i32(s[2], s[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[2], 0xFFFFFFF6) # -10
|
||||
|
||||
def test_division_sequence_from_llvm(self):
|
||||
"""Test the division sequence pattern from LLVM-generated code."""
|
||||
# This sequence is from the sin kernel and computes integer division
|
||||
# s10 = dividend, s18 = divisor, result in s6/s14
|
||||
dividend = 0x28BE60DB # Some value from the sin kernel
|
||||
divisor = 3 # Simplified divisor
|
||||
instructions = [
|
||||
s_mov_b32(s[10], dividend),
|
||||
s_mov_b32(s[18], divisor),
|
||||
# Compute reciprocal approximation: s6 = ~0 / divisor (approx)
|
||||
s_mov_b32(s[11], 0),
|
||||
s_sub_i32(s[11], s[11], s[18]), # s11 = -divisor
|
||||
# For testing, just verify basic arithmetic works
|
||||
s_mul_i32(s[6], s[10], 2),
|
||||
s_add_i32(s[7], s[6], 1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[6], (dividend * 2) & 0xFFFFFFFF)
|
||||
self.assertEqual(st.sgpr[7], ((dividend * 2) + 1) & 0xFFFFFFFF)
|
||||
|
||||
|
||||
class Test64BitCompare(unittest.TestCase):
|
||||
"""Tests for 64-bit scalar compare instructions."""
|
||||
|
||||
def test_s_cmp_eq_u64_equal(self):
|
||||
"""S_CMP_EQ_U64: comparing equal 64-bit values sets SCC=1."""
|
||||
val = 0x123456789ABCDEF0
|
||||
instructions = [
|
||||
s_mov_b32(s[0], val & 0xFFFFFFFF),
|
||||
s_mov_b32(s[1], val >> 32),
|
||||
s_mov_b32(s[2], val & 0xFFFFFFFF),
|
||||
s_mov_b32(s[3], val >> 32),
|
||||
s_cmp_eq_u64(s[0:1], s[2:3]),
|
||||
s_cselect_b32(s[4], 1, 0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.scc, 1)
|
||||
self.assertEqual(st.sgpr[4], 1)
|
||||
|
||||
def test_s_cmp_eq_u64_different_upper_bits(self):
|
||||
"""S_CMP_EQ_U64: values differing only in upper 32 bits are not equal."""
|
||||
# This is the bug case - if only lower 32 bits are compared, these would be equal
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0), # lower 32 bits of value 0
|
||||
s_mov_b32(s[1], 0), # upper 32 bits of value 0
|
||||
s_mov_b32(s[2], 0), # lower 32 bits of 0x100000000
|
||||
s_mov_b32(s[3], 1), # upper 32 bits of 0x100000000
|
||||
s_cmp_eq_u64(s[0:1], s[2:3]),
|
||||
s_cselect_b32(s[4], 1, 0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.scc, 0, "0 != 0x100000000, SCC should be 0")
|
||||
self.assertEqual(st.sgpr[4], 0)
|
||||
|
||||
def test_s_cmp_lg_u64_different(self):
|
||||
"""S_CMP_LG_U64: different 64-bit values sets SCC=1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0),
|
||||
s_mov_b32(s[1], 0), # s[0:1] = 0
|
||||
s_mov_b32(s[2], 0),
|
||||
s_mov_b32(s[3], 1), # s[2:3] = 0x100000000
|
||||
s_cmp_lg_u64(s[0:1], s[2:3]),
|
||||
s_cselect_b32(s[4], 1, 0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.scc, 1, "0 != 0x100000000, SCC should be 1")
|
||||
self.assertEqual(st.sgpr[4], 1)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,451 +0,0 @@
|
||||
"""Tests for VOP2 instructions - two operand vector operations.
|
||||
|
||||
Includes: v_add_f32, v_mul_f32, v_and_b32, v_or_b32, v_xor_b32,
|
||||
v_lshrrev_b32, v_lshlrev_b32, v_fmac_f32, v_fmaak_f32, v_fmamk_f32,
|
||||
v_add_nc_u32, v_cndmask_b32, v_add_f16, v_mul_f16
|
||||
"""
|
||||
import unittest
|
||||
from extra.assembly.amd.test.hw.helpers import *
|
||||
|
||||
class TestBasicArithmetic(unittest.TestCase):
|
||||
"""Tests for basic arithmetic VOP2 instructions."""
|
||||
|
||||
def test_v_add_f32(self):
|
||||
"""V_ADD_F32 adds two floats."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 1.0),
|
||||
v_mov_b32_e32(v[1], 2.0),
|
||||
v_add_f32_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 3.0, places=5)
|
||||
|
||||
def test_v_mul_f32(self):
|
||||
"""V_MUL_F32 multiplies two floats."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 2.0),
|
||||
v_mov_b32_e32(v[1], 4.0),
|
||||
v_mul_f32_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 8.0, places=5)
|
||||
|
||||
def test_v_fmac_f32(self):
|
||||
"""V_FMAC_F32: d = d + a*b using inline constants."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 2.0),
|
||||
v_mov_b32_e32(v[1], 4.0),
|
||||
v_mov_b32_e32(v[2], 1.0),
|
||||
v_fmac_f32_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 9.0, places=5)
|
||||
|
||||
def test_v_fmaak_f32(self):
|
||||
"""V_FMAAK_F32: d = a * b + K using inline constants."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 2.0),
|
||||
v_mov_b32_e32(v[1], 4.0),
|
||||
v_fmaak_f32_e32(v[2], v[0], v[1], literal=0x3f800000),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 9.0, places=5)
|
||||
|
||||
def test_v_fmamk_f32_basic(self):
|
||||
"""V_FMAMK_F32: d = a * K + b."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 2.0),
|
||||
v_mov_b32_e32(v[1], 1.0),
|
||||
v_fmamk_f32_e32(v[2], v[0], v[1], literal=0x40800000),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 9.0, places=5)
|
||||
|
||||
def test_v_fmamk_f32_small_constant(self):
|
||||
"""V_FMAMK_F32 with small constant."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 4.0),
|
||||
v_mov_b32_e32(v[1], 1.0),
|
||||
v_fmamk_f32_e32(v[2], v[0], v[1], literal=f2i(0.5)),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][2]), 3.0, places=5)
|
||||
|
||||
|
||||
class TestBitManipulation(unittest.TestCase):
|
||||
"""Tests for bit manipulation VOP2 instructions."""
|
||||
|
||||
def test_v_and_b32(self):
|
||||
"""V_AND_B32 bitwise and."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xff),
|
||||
s_mov_b32(s[1], 0x0f),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_and_b32_e32(v[1], s[1], v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0x0f)
|
||||
|
||||
def test_v_and_b32_quadrant(self):
|
||||
"""V_AND_B32 for quadrant extraction (n & 3)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 15915),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_and_b32_e32(v[1], 3, v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 15915 & 3)
|
||||
|
||||
def test_v_lshrrev_b32(self):
|
||||
"""V_LSHRREV_B32 logical shift right."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xff00),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_lshrrev_b32_e32(v[1], 8, v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0xff)
|
||||
|
||||
def test_v_lshlrev_b32(self):
|
||||
"""V_LSHLREV_B32 logical shift left."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xff),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_lshlrev_b32_e32(v[1], 8, v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0xff00)
|
||||
|
||||
def test_v_xor_b32(self):
|
||||
"""V_XOR_B32 bitwise xor (used in sin for sign)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x80000000),
|
||||
s_mov_b32(s[1], f2i(1.0)),
|
||||
v_mov_b32_e32(v[0], s[1]),
|
||||
v_xor_b32_e32(v[1], s[0], v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][1]), -1.0, places=5)
|
||||
|
||||
def test_v_xor_b32_sign_flip(self):
|
||||
"""V_XOR_B32 for sign flip pattern."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x80000000),
|
||||
v_mov_b32_e32(v[0], -2.0),
|
||||
v_xor_b32_e32(v[1], s[0], v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertAlmostEqual(i2f(st.vgpr[0][1]), 2.0, places=5)
|
||||
|
||||
|
||||
class TestSpecialValues(unittest.TestCase):
|
||||
"""Tests for special float values - inf, nan, zero handling."""
|
||||
|
||||
def test_v_mul_f32_zero_times_inf(self):
|
||||
"""V_MUL_F32: 0 * inf = NaN."""
|
||||
import math
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0),
|
||||
s_mov_b32(s[0], 0x7f800000),
|
||||
v_mov_b32_e32(v[1], s[0]),
|
||||
v_mul_f32_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertTrue(math.isnan(i2f(st.vgpr[0][2])))
|
||||
|
||||
def test_v_add_f32_inf_minus_inf(self):
|
||||
"""V_ADD_F32: inf + (-inf) = NaN."""
|
||||
import math
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7f800000),
|
||||
s_mov_b32(s[1], 0xff800000),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_add_f32_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertTrue(math.isnan(i2f(st.vgpr[0][2])))
|
||||
|
||||
|
||||
class TestF16Ops(unittest.TestCase):
|
||||
"""Tests for 16-bit VOP2 operations."""
|
||||
|
||||
def test_v_add_f16_basic(self):
|
||||
"""V_ADD_F16 adds two f16 values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_add_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x4200, f"Expected 0x4200 (f16 3.0), got 0x{result:04x}")
|
||||
|
||||
def test_v_add_f16_negative(self):
|
||||
"""V_ADD_F16 with negative values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0xc000), # f16 -2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_add_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0xbc00, f"Expected 0xbc00 (f16 -1.0), got 0x{result:04x}")
|
||||
|
||||
def test_v_mul_f16_basic(self):
|
||||
"""V_MUL_F16 multiplies two f16 values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x4000), # f16 2.0
|
||||
s_mov_b32(s[1], 0x4200), # f16 3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mul_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x4600, f"Expected 0x4600 (f16 6.0), got 0x{result:04x}")
|
||||
|
||||
def test_v_mul_f16_by_zero(self):
|
||||
"""V_MUL_F16 by zero."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0),
|
||||
v_mul_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x0000, f"Expected 0x0000 (f16 0.0), got 0x{result:04x}")
|
||||
|
||||
def test_v_fmac_f16_basic(self):
|
||||
"""V_FMAC_F16: d = d + a*b."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x4000), # f16 2.0
|
||||
s_mov_b32(s[1], 0x4200), # f16 3.0
|
||||
s_mov_b32(s[2], 0x3c00), # f16 1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
v_fmac_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
# 2.0 * 3.0 + 1.0 = 7.0, f16 7.0 = 0x4700
|
||||
self.assertEqual(result, 0x4700, f"Expected 0x4700 (f16 7.0), got 0x{result:04x}")
|
||||
|
||||
def test_v_fmaak_f16_basic(self):
|
||||
"""V_FMAAK_F16: d = a * b + K."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x4000), # f16 2.0
|
||||
s_mov_b32(s[1], 0x4200), # f16 3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_fmaak_f16_e32(v[2], v[0], v[1], literal=0x3c00), # + f16 1.0
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
# 2.0 * 3.0 + 1.0 = 7.0, f16 7.0 = 0x4700
|
||||
self.assertEqual(result, 0x4700, f"Expected 0x4700 (f16 7.0), got 0x{result:04x}")
|
||||
|
||||
|
||||
class TestHiHalfOps(unittest.TestCase):
|
||||
"""Tests for VOP2 16-bit operations with hi-half operands."""
|
||||
|
||||
def test_v_add_f16_src0_hi_fold(self):
|
||||
"""V_ADD_F16 with src0 hi-half fold (same register, different halves)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # lo=f16(1.0), hi=f16(2.0)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
VOP3(VOP3Op.V_ADD_F16, vdst=v[1], src0=v[0], src1=v[0], opsel=0b0001),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][1] & 0xffff
|
||||
self.assertEqual(result, 0x4200, f"Expected f16(3.0)=0x4200, got 0x{result:04x}")
|
||||
|
||||
def test_v_add_f16_src0_hi_different_reg(self):
|
||||
"""V_ADD_F16 with src0 hi-half from different register."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40000000), # hi=f16(2.0), lo=0
|
||||
s_mov_b32(s[1], 0x00003c00), # hi=0, lo=f16(1.0)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
VOP3(VOP3Op.V_ADD_F16, vdst=v[2], src0=v[0], src1=v[1], opsel=0b0001),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x4200, f"Expected f16(3.0)=0x4200, got 0x{result:04x}")
|
||||
|
||||
def test_v_mul_f16_src0_hi(self):
|
||||
"""V_MUL_F16 with src0 from high half."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40000000), # hi=f16(2.0), lo=0
|
||||
s_mov_b32(s[1], 0x00004200), # hi=0, lo=f16(3.0)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
VOP3(VOP3Op.V_MUL_F16, vdst=v[2], src0=v[0], src1=v[1], opsel=0b0001),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x4600, f"Expected f16(6.0)=0x4600, got 0x{result:04x}")
|
||||
|
||||
def test_v_mul_f16_hi_half(self):
|
||||
"""V_MUL_F16 reading from high half."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # lo=1.0, hi=2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
VOP3(VOP3Op.V_MUL_F16, vdst=v[1], src0=v[0], src1=v[0], opsel=0b0011),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][1] & 0xffff
|
||||
self.assertEqual(result, 0x4400, f"Expected f16(4.0)=0x4400, got 0x{result:04x}")
|
||||
|
||||
def test_v_fma_f16_hi_dest(self):
|
||||
"""V_FMA_F16 writing to high half with opsel.
|
||||
|
||||
Uses V_FMA_F16 (not V_FMAC_F16) because it has explicit src2 operand
|
||||
which makes opsel handling clearer.
|
||||
"""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c000000), # hi=f16(1.0), lo=0
|
||||
s_mov_b32(s[1], 0x4000), # f16(2.0) in lo
|
||||
s_mov_b32(s[2], 0x4200), # f16(3.0) in lo
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
# V_FMA_F16: dst = src0 * src1 + src2
|
||||
# opsel=0b1100: bit2=src2 hi, bit3=dst hi
|
||||
# So: v[0].hi = v[1].lo * v[2].lo + v[0].hi = 2.0 * 3.0 + 1.0 = 7.0
|
||||
VOP3(VOP3Op.V_FMA_F16, vdst=v[0], src0=v[1], src1=v[2], src2=v[0], opsel=0b1100),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
hi = (st.vgpr[0][0] >> 16) & 0xffff
|
||||
# 2.0 * 3.0 + 1.0 = 7.0, f16 7.0 = 0x4700
|
||||
self.assertEqual(hi, 0x4700, f"Expected f16(7.0)=0x4700 in hi, got 0x{hi:04x}")
|
||||
|
||||
def test_v_add_f16_multilane(self):
|
||||
"""V_ADD_F16 with multiple lanes."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_add_f16_e32(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=4)
|
||||
for lane in range(4):
|
||||
result = st.vgpr[lane][2] & 0xffff
|
||||
self.assertEqual(result, 0x4200, f"Lane {lane}: expected 0x4200, got 0x{result:04x}")
|
||||
|
||||
|
||||
class TestCndmask(unittest.TestCase):
|
||||
"""Tests for V_CNDMASK_B32 and V_CNDMASK_B16."""
|
||||
|
||||
def test_v_cndmask_b16_select_src0(self):
|
||||
"""V_CNDMASK_B16 selects src0 when VCC bit is 0."""
|
||||
instructions = [
|
||||
s_mov_b32(VCC_LO, 0), # VCC = 0
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cndmask_b16(v[2], v[0], v[1], VCC),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x3c00, f"Expected src0=0x3c00, got 0x{result:04x}")
|
||||
|
||||
def test_v_cndmask_b16_select_src1(self):
|
||||
"""V_CNDMASK_B16 selects src1 when VCC bit is 1."""
|
||||
instructions = [
|
||||
s_mov_b32(VCC_LO, 1), # VCC = 1
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cndmask_b16(v[2], v[0], v[1], VCC),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2] & 0xffff
|
||||
self.assertEqual(result, 0x4000, f"Expected src1=0x4000, got 0x{result:04x}")
|
||||
|
||||
def test_v_cndmask_b16_write_hi(self):
|
||||
"""V_CNDMASK_B16 can write to high 16 bits with opsel."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c003800), # src0: hi=1.0, lo=0.5
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], 0x4000c000), # src1: hi=2.0, lo=-2.0
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], 0xDEAD0000), # v2 initial: hi=0xDEAD, lo=0
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
s_mov_b32(VCC_LO, 0), # vcc = 0, select src0
|
||||
# opsel=0b1011: bit0=src0 hi, bit1=src1 hi, bit3=dst hi
|
||||
VOP3(VOP3Op.V_CNDMASK_B16, vdst=v[2], src0=v[0], src1=v[1], src2=SrcEnum.VCC_LO, opsel=0b1011),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
hi = (st.vgpr[0][2] >> 16) & 0xffff
|
||||
lo = st.vgpr[0][2] & 0xffff
|
||||
# vcc=0 selects src0.h = 1.0 = 0x3c00, writes to hi
|
||||
self.assertEqual(hi, 0x3c00, f"Expected hi=0x3c00 (1.0), got 0x{hi:04x}")
|
||||
self.assertEqual(lo, 0x0000, f"Expected lo preserved as 0, got 0x{lo:04x}")
|
||||
|
||||
|
||||
class TestSpecialFloatValues(unittest.TestCase):
|
||||
"""Tests for special float value handling in VOP2 instructions."""
|
||||
|
||||
def test_neg_zero_add(self):
|
||||
"""-0.0 + 0.0 = +0.0 (IEEE 754)."""
|
||||
neg_zero = 0x80000000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], neg_zero),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_add_f32_e32(v[1], 0.0, v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0x00000000, "Should be +0.0")
|
||||
|
||||
def test_neg_zero_mul(self):
|
||||
"""-0.0 * -1.0 = +0.0."""
|
||||
neg_zero = 0x80000000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], neg_zero),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mul_f32_e32(v[1], -1.0, v[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0x00000000, "Should be +0.0")
|
||||
|
||||
def test_inf_minus_inf(self):
|
||||
"""+inf - inf = NaN."""
|
||||
import math
|
||||
pos_inf = 0x7f800000
|
||||
neg_inf = 0xff800000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], pos_inf),
|
||||
s_mov_b32(s[1], neg_inf),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_sub_f32_e32(v[2], v[0], v[1]), # inf - (-inf) = inf
|
||||
v_add_f32_e32(v[3], v[0], v[1]), # inf + (-inf) = NaN
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][2], pos_inf, "inf - (-inf) = inf")
|
||||
self.assertTrue(math.isnan(i2f(st.vgpr[0][3])), "inf + (-inf) = NaN")
|
||||
|
||||
def test_denormal_f32_mul_ftz(self):
|
||||
"""Denormal * normal - RDNA3 flushes denormals to zero (FTZ mode)."""
|
||||
smallest_denorm = 0x00000001 # Smallest positive denormal
|
||||
instructions = [
|
||||
s_mov_b32(s[0], smallest_denorm),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mul_f32_e32(v[1], 2.0, v[0]), # Denormal input gets flushed to 0
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][1], 0x00000000)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,532 +0,0 @@
|
||||
"""Tests for VOP3P instructions - packed 16-bit vector operations.
|
||||
|
||||
Includes: v_pk_add_f16, v_pk_mul_f16, v_pk_fma_f16, v_pack_b32_f16, v_wmma_*, v_dot2_*
|
||||
"""
|
||||
import unittest
|
||||
from extra.assembly.amd.test.hw.helpers import *
|
||||
|
||||
class TestPackInstructions(unittest.TestCase):
|
||||
"""Tests for pack instructions."""
|
||||
|
||||
def test_v_pack_b32_f16(self):
|
||||
"""V_PACK_B32_F16 packs two f16 values into one 32-bit register."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x40003c00, f"Expected 0x40003c00, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_opsel_hi_hi(self):
|
||||
"""V_PACK_B32_F16 with opsel to read high halves."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # hi=2.0, lo=1.0
|
||||
s_mov_b32(s[1], 0x44004200), # hi=4.0, lo=3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1], opsel=0b0011),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x44004000, f"Expected 0x44004000, got 0x{result:08x}")
|
||||
|
||||
|
||||
class TestPackMore(unittest.TestCase):
|
||||
"""Additional pack instruction tests."""
|
||||
|
||||
def test_v_pack_b32_f16_basic(self):
|
||||
"""V_PACK_B32_F16 packs two f16 values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 1.0
|
||||
s_mov_b32(s[1], 0x4000), # f16 2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x40003c00, f"Expected 0x40003c00, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_with_cvt(self):
|
||||
"""V_PACK_B32_F16 after V_CVT_F16_F32 conversions."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3f800000),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[0]),
|
||||
v_cvt_f16_f32_e32(v[2], v[0]),
|
||||
v_cvt_f16_f32_e32(v[3], v[1]),
|
||||
v_pack_b32_f16(v[4], v[2], v[3]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][4]
|
||||
self.assertEqual(result, 0x3c003c00, f"Expected 0x3c003c00, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_packed_sources(self):
|
||||
"""V_PACK_B32_F16 with packed f16 sources (reads lo halves)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # hi=2.0, lo=1.0
|
||||
s_mov_b32(s[1], 0x44004200), # hi=4.0, lo=3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
# Expected: hi=v1.lo=0x4200 (3.0), lo=v0.lo=0x3c00 (1.0) -> 0x42003c00
|
||||
self.assertEqual(result, 0x42003c00, f"Expected 0x42003c00, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_opsel_lo_hi(self):
|
||||
"""V_PACK_B32_F16 with opsel=0b0010 to read lo from src0, hi from src1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00),
|
||||
s_mov_b32(s[1], 0x44004200),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1], opsel=0b0010),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x44003c00, f"Expected 0x44003c00, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_opsel_hi_lo(self):
|
||||
"""V_PACK_B32_F16 with opsel=0b0001 to read hi from src0, lo from src1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00),
|
||||
s_mov_b32(s[1], 0x44004200),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1], opsel=0b0001),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x42004000, f"Expected 0x42004000, got 0x{result:08x}")
|
||||
|
||||
def test_v_pack_b32_f16_zeros(self):
|
||||
"""V_PACK_B32_F16 with zero values."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0),
|
||||
v_mov_b32_e32(v[1], 0),
|
||||
v_pack_b32_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][2], 0)
|
||||
|
||||
def test_v_pack_b32_f16_both_positive(self):
|
||||
"""V_PACK_B32_F16 with positive f16 values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x4200), # f16 3.0
|
||||
s_mov_b32(s[1], 0x4400), # f16 4.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pack_b32_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x44004200, f"Expected 0x44004200, got 0x{result:08x}")
|
||||
|
||||
|
||||
class TestFmaMix(unittest.TestCase):
|
||||
"""Tests for V_FMA_MIX_F32 and V_FMA_MIXLO_F16."""
|
||||
|
||||
def test_v_fma_mix_f32_all_f32_sources(self):
|
||||
"""V_FMA_MIX_F32 with all f32 sources."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(2.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(3.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], f2i(1.0)),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
VOP3P(VOP3POp.V_FMA_MIX_F32, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=0, opsel_hi=0, opsel_hi2=0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = i2f(st.vgpr[0][3])
|
||||
self.assertAlmostEqual(result, 7.0, places=5)
|
||||
|
||||
def test_v_fma_mix_f32_src2_f16_lo(self):
|
||||
"""V_FMA_MIX_F32 with src2 as f16 from lo bits."""
|
||||
from extra.assembly.amd.pcode import f32_to_f16
|
||||
f16_2 = f32_to_f16(2.0)
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(1.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(3.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], f16_2),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
VOP3P(VOP3POp.V_FMA_MIX_F32, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=0, opsel_hi=0, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = i2f(st.vgpr[0][3])
|
||||
self.assertAlmostEqual(result, 5.0, places=5)
|
||||
|
||||
def test_v_fma_mix_f32_src2_f16_hi(self):
|
||||
"""V_FMA_MIX_F32 with src2 as f16 from hi bits."""
|
||||
from extra.assembly.amd.pcode import f32_to_f16
|
||||
f16_2 = f32_to_f16(2.0)
|
||||
val = (f16_2 << 16) | 0
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(1.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(3.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], val),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
VOP3P(VOP3POp.V_FMA_MIX_F32, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=4, opsel_hi=0, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = i2f(st.vgpr[0][3])
|
||||
self.assertAlmostEqual(result, 5.0, places=5)
|
||||
|
||||
def test_v_fma_mix_f32_with_abs(self):
|
||||
"""V_FMA_MIX_F32 with abs modifier on src2."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(2.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(3.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], f2i(-1.0)),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
VOP3P(VOP3POp.V_FMA_MIX_F32, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=0, opsel_hi=0, opsel_hi2=0, neg_hi=4),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = i2f(st.vgpr[0][3])
|
||||
self.assertAlmostEqual(result, 7.0, places=5)
|
||||
|
||||
def test_v_fma_mixlo_f16(self):
|
||||
"""V_FMA_MIXLO_F16 writes to low 16 bits of destination."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(2.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(3.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], f2i(1.0)),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
s_mov_b32(s[3], 0xdead0000),
|
||||
v_mov_b32_e32(v[3], s[3]),
|
||||
VOP3P(VOP3POp.V_FMA_MIXLO_F16, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=0, opsel_hi=0, opsel_hi2=0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
lo = _f16(st.vgpr[0][3] & 0xffff)
|
||||
hi = (st.vgpr[0][3] >> 16) & 0xffff
|
||||
self.assertAlmostEqual(lo, 7.0, places=1)
|
||||
self.assertEqual(hi, 0xdead, f"hi should be preserved, got 0x{hi:04x}")
|
||||
|
||||
def test_v_fma_mixlo_f16_all_f32_sources(self):
|
||||
"""V_FMA_MIXLO_F16 with all f32 sources."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], f2i(1.0)),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], f2i(2.0)),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
s_mov_b32(s[2], f2i(3.0)),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
v_mov_b32_e32(v[3], 0),
|
||||
VOP3P(VOP3POp.V_FMA_MIXLO_F16, vdst=v[3], src0=v[0], src1=v[1], src2=v[2], opsel=0, opsel_hi=0, opsel_hi2=0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
lo = _f16(st.vgpr[0][3] & 0xffff)
|
||||
# 1*2+3 = 5
|
||||
self.assertAlmostEqual(lo, 5.0, places=1)
|
||||
|
||||
def test_v_fma_mixlo_f16_sin_case(self):
|
||||
"""V_FMA_MIXLO_F16 case from sin kernel."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3f800000), # f32 1.0
|
||||
v_mov_b32_e32(v[3], s[0]),
|
||||
s_mov_b32(s[1], 0xaf05a309), # f32 tiny negative
|
||||
s_mov_b32(s[6], s[1]),
|
||||
s_mov_b32(s[2], 0xc0490fdb), # f32 -π
|
||||
v_mov_b32_e32(v[5], s[2]),
|
||||
s_mov_b32(s[3], 0x3f800000),
|
||||
v_mov_b32_e32(v[3], s[3]),
|
||||
VOP3P(VOP3POp.V_FMA_MIXLO_F16, vdst=v[3], src0=v[3], src1=s[6], src2=v[5], opsel=0, opsel_hi=0, opsel_hi2=0),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
lo = _f16(st.vgpr[0][3] & 0xffff)
|
||||
self.assertAlmostEqual(lo, -3.14159, delta=0.01)
|
||||
|
||||
|
||||
class TestVOP3P(unittest.TestCase):
|
||||
"""Tests for VOP3P packed 16-bit operations."""
|
||||
|
||||
def test_v_pk_add_f16_basic(self):
|
||||
"""V_PK_ADD_F16 adds two packed f16 values."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # hi=2.0, lo=1.0
|
||||
s_mov_b32(s[1], 0x44004200), # hi=4.0, lo=3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pk_add_f16(v[2], v[0], v[1], opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
self.assertAlmostEqual(lo, 4.0, places=2)
|
||||
self.assertAlmostEqual(hi, 6.0, places=2)
|
||||
|
||||
def test_v_pk_mul_f16_basic(self):
|
||||
"""V_PK_MUL_F16 multiplies two packed f16 values."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x42004000), # hi=3.0, lo=2.0
|
||||
s_mov_b32(s[1], 0x45004400), # hi=5.0, lo=4.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pk_mul_f16(v[2], v[0], v[1], opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
self.assertAlmostEqual(lo, 8.0, places=1)
|
||||
self.assertAlmostEqual(hi, 15.0, places=1)
|
||||
|
||||
def test_v_pk_fma_f16_basic(self):
|
||||
"""V_PK_FMA_F16: D = A * B + C for packed f16."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x42004000), # A: hi=3.0, lo=2.0
|
||||
s_mov_b32(s[1], 0x45004400), # B: hi=5.0, lo=4.0
|
||||
s_mov_b32(s[2], 0x3c003c00), # C: hi=1.0, lo=1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], s[2]),
|
||||
v_pk_fma_f16(v[3], v[0], v[1], v[2], opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][3]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
self.assertAlmostEqual(lo, 9.0, places=1) # 2*4+1
|
||||
self.assertAlmostEqual(hi, 16.0, places=0) # 3*5+1
|
||||
|
||||
def test_v_pk_add_f16_with_inline_constant(self):
|
||||
"""V_PK_ADD_F16 with inline constant POS_ONE (1.0).
|
||||
Inline constants for VOP3P are f16 values in the low 16 bits only.
|
||||
hi half of inline constant is 0, so hi result = v0.hi + 0 = 1.0.
|
||||
"""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c003c00), # packed f16: hi=1.0, lo=1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_pk_add_f16(v[1], v[0], SrcEnum.POS_ONE, opsel_hi=3, opsel_hi2=1), # Add inline constant 1.0
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][1]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
# lo = 1.0 + 1.0 = 2.0, hi = 1.0 + 0.0 = 1.0 (inline const hi half is 0)
|
||||
self.assertAlmostEqual(lo, 2.0, places=2)
|
||||
self.assertAlmostEqual(hi, 1.0, places=2)
|
||||
|
||||
def test_v_pk_mul_f16_with_inline_constant(self):
|
||||
"""V_PK_MUL_F16 with inline constant POS_TWO (2.0).
|
||||
Inline constant has value only in low 16 bits, hi is 0.
|
||||
"""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
# v0 = packed (3.0, 4.0), multiply by POS_TWO
|
||||
# lo = 3.0 * 2.0 = 6.0, hi = 4.0 * 0.0 = 0.0 (inline const hi is 0)
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x44004200), # packed f16: hi=4.0, lo=3.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_pk_mul_f16(v[1], v[0], SrcEnum.POS_TWO, opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][1]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
self.assertAlmostEqual(lo, 6.0, places=1)
|
||||
self.assertAlmostEqual(hi, 0.0, places=1)
|
||||
|
||||
|
||||
class TestWMMA(unittest.TestCase):
|
||||
"""Tests for WMMA (Wave Matrix Multiply-Accumulate) instructions."""
|
||||
|
||||
def test_v_wmma_f32_16x16x16_f16_all_ones(self):
|
||||
"""V_WMMA_F32_16X16X16_F16 with all ones produces 16.0."""
|
||||
instructions = []
|
||||
instructions.append(s_mov_b32(s[0], 0x3c003c00)) # packed f16 1.0
|
||||
for i in range(16, 32):
|
||||
instructions.append(v_mov_b32_e32(v[i], s[0]))
|
||||
for i in range(8):
|
||||
instructions.append(v_mov_b32_e32(v[i], 0))
|
||||
instructions.append(v_wmma_f32_16x16x16_f16(v[0:7], v[16:23], v[24:31], v[0:7]))
|
||||
st = run_program(instructions, n_lanes=32)
|
||||
expected = f2i(16.0)
|
||||
for lane in range(32):
|
||||
for reg in range(8):
|
||||
result = st.vgpr[lane][reg]
|
||||
self.assertEqual(result, expected, f"v[{reg}] lane {lane}: expected 16.0, got {i2f(result)}")
|
||||
|
||||
def test_v_wmma_f32_16x16x16_f16_with_accumulator(self):
|
||||
"""V_WMMA_F32_16X16X16_F16 with non-zero accumulator."""
|
||||
instructions = []
|
||||
instructions.append(s_mov_b32(s[0], 0x3c003c00))
|
||||
instructions.append(s_mov_b32(s[1], f2i(5.0)))
|
||||
for i in range(16, 32):
|
||||
instructions.append(v_mov_b32_e32(v[i], s[0]))
|
||||
for i in range(8):
|
||||
instructions.append(v_mov_b32_e32(v[i], s[1]))
|
||||
instructions.append(v_wmma_f32_16x16x16_f16(v[0:7], v[16:23], v[24:31], v[0:7]))
|
||||
st = run_program(instructions, n_lanes=32)
|
||||
expected = f2i(21.0) # 16 + 5
|
||||
for lane in range(32):
|
||||
for reg in range(8):
|
||||
result = st.vgpr[lane][reg]
|
||||
self.assertEqual(result, expected, f"v[{reg}] lane {lane}: expected 21.0, got {i2f(result)}")
|
||||
|
||||
|
||||
class TestSpecialOps(unittest.TestCase):
|
||||
"""Tests for special operations (SAD, PERM, DOT2)."""
|
||||
|
||||
def test_v_sad_u8_basic(self):
|
||||
"""V_SAD_U8 computes sum of absolute differences."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x04030201), # bytes: 1, 2, 3, 4
|
||||
s_mov_b32(s[1], 0x05040302), # bytes: 2, 3, 4, 5
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], 0),
|
||||
v_sad_u8(v[3], v[0], v[1], v[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# |1-2| + |2-3| + |3-4| + |4-5| = 1 + 1 + 1 + 1 = 4
|
||||
self.assertEqual(st.vgpr[0][3], 4)
|
||||
|
||||
def test_v_sad_u8_identical_bytes(self):
|
||||
"""V_SAD_U8 with identical inputs returns accumulator."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x04030201),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], 10),
|
||||
v_mov_b32_e32(v[2], s[1]),
|
||||
v_sad_u8(v[3], v[0], v[0], v[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# Same inputs -> SAD = 0, result = accumulator = 10
|
||||
self.assertEqual(st.vgpr[0][3], 10)
|
||||
|
||||
def test_v_sad_u16_basic(self):
|
||||
"""V_SAD_U16 computes sum of absolute differences of u16 pairs."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x00030001), # hi=3, lo=1
|
||||
s_mov_b32(s[1], 0x00050002), # hi=5, lo=2
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], 0),
|
||||
v_sad_u16(v[3], v[0], v[1], v[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# |1-2| + |3-5| = 1 + 2 = 3
|
||||
self.assertEqual(st.vgpr[0][3], 3)
|
||||
|
||||
def test_v_sad_u32_basic(self):
|
||||
"""V_SAD_U32 computes absolute difference of u32 values."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 100),
|
||||
s_mov_b32(s[1], 70),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], 0),
|
||||
v_sad_u32(v[3], v[0], v[1], v[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# |100-70| = 30
|
||||
self.assertEqual(st.vgpr[0][3], 30)
|
||||
|
||||
def test_v_msad_u8_masked(self):
|
||||
"""V_MSAD_U8 masked SAD operation."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x04030201),
|
||||
s_mov_b32(s[1], 0x05040302),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], 0),
|
||||
v_msad_u8(v[3], v[0], v[1], v[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# V_MSAD_U8 skips bytes where src0 is 0
|
||||
# Since no bytes are 0, result same as V_SAD_U8 = 4
|
||||
self.assertEqual(st.vgpr[0][3], 4)
|
||||
|
||||
def test_v_perm_b32_select_bytes(self):
|
||||
"""V_PERM_B32 selects bytes from two sources.
|
||||
|
||||
V_PERM_B32 concatenates {S1, S0} as a 64-bit value with S1 in low 32 bits.
|
||||
Selector byte values 0-3 select from S1, values 4-7 select from S0.
|
||||
"""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x44332211), # src0: bytes 4-7 in 64-bit view
|
||||
s_mov_b32(s[1], 0x88776655), # src1: bytes 0-3 in 64-bit view
|
||||
s_mov_b32(s[2], 0x07060504), # select bytes 4,5,6,7 (from src0)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_perm_b32(v[2], v[0], v[1], s[2]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vgpr[0][2], 0x44332211)
|
||||
|
||||
def test_v_dot2_f32_bf16_basic(self):
|
||||
"""V_DOT2_F32_BF16 computes dot product of bf16 pairs."""
|
||||
# bf16 1.0 = 0x3f80, bf16 2.0 = 0x4000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3f803f80), # packed bf16: lo=1.0, hi=1.0
|
||||
s_mov_b32(s[1], 0x40003f80), # packed bf16: lo=1.0, hi=2.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_mov_b32_e32(v[2], 0),
|
||||
v_dot2_f32_bf16(v[3], v[0], v[1], v[2], opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
# 1.0*1.0 + 1.0*2.0 + 0 = 3.0
|
||||
result = i2f(st.vgpr[0][3])
|
||||
self.assertAlmostEqual(result, 3.0, places=4)
|
||||
|
||||
|
||||
class TestPackedMixedSigns(unittest.TestCase):
|
||||
"""Tests for packed operations with mixed sign values."""
|
||||
|
||||
def test_pk_add_f16_mixed_signs(self):
|
||||
"""V_PK_ADD_F16 with mixed positive/negative values."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xc0003c00), # packed: hi=-2.0, lo=1.0
|
||||
s_mov_b32(s[1], 0x3c003c00), # packed: hi=1.0, lo=1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pk_add_f16(v[2], v[0], v[1], opsel_hi=3, opsel_hi2=1),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
lo = _f16(result & 0xffff)
|
||||
hi = _f16((result >> 16) & 0xffff)
|
||||
self.assertAlmostEqual(lo, 2.0, places=2) # 1.0 + 1.0
|
||||
self.assertAlmostEqual(hi, -1.0, places=2) # -2.0 + 1.0
|
||||
|
||||
def test_pk_mul_f16_zero(self):
|
||||
"""V_PK_MUL_F16 with zero."""
|
||||
from extra.assembly.amd.pcode import _f16
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40004000), # packed: 2.0, 2.0
|
||||
s_mov_b32(s[1], 0x00000000), # packed: 0.0, 0.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_pk_mul_f16(v[2], v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
result = st.vgpr[0][2]
|
||||
self.assertEqual(result, 0x00000000, "2.0 * 0.0 should be 0.0")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,476 +0,0 @@
|
||||
"""Tests for VOPC instructions - vector compare operations.
|
||||
|
||||
Includes: v_cmp_class_f32, v_cmp_class_f16, v_cmp_eq_*, v_cmp_lt_*, v_cmp_gt_*
|
||||
"""
|
||||
import unittest
|
||||
from extra.assembly.amd.test.hw.helpers import *
|
||||
|
||||
VCC = 106 # SGPR index for VCC_LO
|
||||
|
||||
class TestCmpClass(unittest.TestCase):
|
||||
"""Tests for V_CMP_CLASS_F32 float classification."""
|
||||
|
||||
def test_cmp_class_quiet_nan(self):
|
||||
"""V_CMP_CLASS_F32 detects quiet NaN."""
|
||||
quiet_nan = 0x7fc00000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], quiet_nan),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0b0000000010), # bit 1 = quiet NaN
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect quiet NaN")
|
||||
|
||||
def test_cmp_class_signaling_nan(self):
|
||||
"""V_CMP_CLASS_F32 detects signaling NaN."""
|
||||
signal_nan = 0x7f800001
|
||||
instructions = [
|
||||
s_mov_b32(s[0], signal_nan),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0b0000000001), # bit 0 = signaling NaN
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect signaling NaN")
|
||||
|
||||
def test_cmp_class_positive_inf(self):
|
||||
"""V_CMP_CLASS_F32 detects +inf."""
|
||||
pos_inf = 0x7f800000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], pos_inf),
|
||||
s_mov_b32(s[1], 0b1000000000), # bit 9 = +inf
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect +inf")
|
||||
|
||||
def test_cmp_class_negative_inf(self):
|
||||
"""V_CMP_CLASS_F32 detects -inf."""
|
||||
neg_inf = 0xff800000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], neg_inf),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0b0000000100), # bit 2 = -inf
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect -inf")
|
||||
|
||||
def test_cmp_class_normal_positive(self):
|
||||
"""V_CMP_CLASS_F32 detects positive normal."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 1.0),
|
||||
s_mov_b32(s[1], 0b0100000000), # bit 8 = positive normal
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect positive normal")
|
||||
|
||||
def test_cmp_class_normal_negative(self):
|
||||
"""V_CMP_CLASS_F32 detects negative normal."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], -1.0),
|
||||
v_mov_b32_e32(v[1], 0b0000001000), # bit 3 = negative normal
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect negative normal")
|
||||
|
||||
def test_cmp_class_quiet_nan_not_signaling(self):
|
||||
"""Quiet NaN does not match signaling NaN mask."""
|
||||
quiet_nan = 0x7fc00000
|
||||
instructions = [
|
||||
s_mov_b32(s[0], quiet_nan),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0b0000000001), # bit 0 = signaling NaN only
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 0, "Quiet NaN should not match signaling mask")
|
||||
|
||||
def test_cmp_class_signaling_nan_not_quiet(self):
|
||||
"""Signaling NaN does not match quiet NaN mask."""
|
||||
signal_nan = 0x7f800001
|
||||
instructions = [
|
||||
s_mov_b32(s[0], signal_nan),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0b0000000010), # bit 1 = quiet NaN only
|
||||
v_cmp_class_f32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 0, "Signaling NaN should not match quiet mask")
|
||||
|
||||
def test_v_cmp_sets_vcc_bits(self):
|
||||
"""V_CMP_EQ sets VCC bits based on per-lane comparison."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 5),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[0]),
|
||||
v_cmp_eq_u32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=4)
|
||||
self.assertEqual(st.vcc & 0xf, 0xf, "All lanes should match")
|
||||
|
||||
|
||||
class TestCmpClassF16(unittest.TestCase):
|
||||
"""Tests for V_CMP_CLASS_F16 float classification.
|
||||
|
||||
Class bit mapping:
|
||||
bit 0 = signaling NaN
|
||||
bit 1 = quiet NaN
|
||||
bit 2 = -infinity
|
||||
bit 3 = -normal
|
||||
bit 4 = -denormal
|
||||
bit 5 = -zero
|
||||
bit 6 = +zero
|
||||
bit 7 = +denormal
|
||||
bit 8 = +normal
|
||||
bit 9 = +infinity
|
||||
"""
|
||||
|
||||
def test_cmp_class_f16_positive_zero(self):
|
||||
"""V_CMP_CLASS_F16: +zero matches bit 6."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0x0000), # f16 +0.0
|
||||
v_mov_b32_e32(v[1], 0x40), # bit 6 = +zero
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect positive zero")
|
||||
|
||||
def test_cmp_class_f16_negative_zero(self):
|
||||
"""V_CMP_CLASS_F16: -zero matches bit 5."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x8000), # f16 -0.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x20), # bit 5 = -zero
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect negative zero")
|
||||
|
||||
def test_cmp_class_f16_positive_normal(self):
|
||||
"""V_CMP_CLASS_F16: +1.0 (normal) matches bit 8."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 +1.0
|
||||
s_mov_b32(s[1], 0x100), # bit 8 = +normal
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect positive normal")
|
||||
|
||||
def test_cmp_class_f16_negative_normal(self):
|
||||
"""V_CMP_CLASS_F16: -1.0 (normal) matches bit 3."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xbc00), # f16 -1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x08), # bit 3 = -normal
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect negative normal")
|
||||
|
||||
def test_cmp_class_f16_positive_infinity(self):
|
||||
"""V_CMP_CLASS_F16: +inf matches bit 9."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7c00), # f16 +inf
|
||||
s_mov_b32(s[1], 0x200), # bit 9 = +inf
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect positive infinity")
|
||||
|
||||
def test_cmp_class_f16_negative_infinity(self):
|
||||
"""V_CMP_CLASS_F16: -inf matches bit 2."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xfc00), # f16 -inf
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x04), # bit 2 = -inf
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect negative infinity")
|
||||
|
||||
def test_cmp_class_f16_quiet_nan(self):
|
||||
"""V_CMP_CLASS_F16: quiet NaN matches bit 1."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7e00), # f16 quiet NaN
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x02), # bit 1 = quiet NaN
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect quiet NaN")
|
||||
|
||||
def test_cmp_class_f16_signaling_nan(self):
|
||||
"""V_CMP_CLASS_F16: signaling NaN matches bit 0."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7c01), # f16 signaling NaN
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x01), # bit 0 = signaling NaN
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect signaling NaN")
|
||||
|
||||
def test_cmp_class_f16_positive_denormal(self):
|
||||
"""V_CMP_CLASS_F16: positive denormal matches bit 7."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 1), # f16 +denormal (0x0001)
|
||||
v_mov_b32_e32(v[1], 0x80), # bit 7 = +denormal
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect positive denormal")
|
||||
|
||||
def test_cmp_class_f16_negative_denormal(self):
|
||||
"""V_CMP_CLASS_F16: negative denormal matches bit 4."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x8001), # f16 -denormal
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], 0x10), # bit 4 = -denormal
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Should detect negative denormal")
|
||||
|
||||
def test_cmp_class_f16_combined_mask_zeros(self):
|
||||
"""V_CMP_CLASS_F16: mask 0x60 covers both +zero and -zero."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0), # f16 +0.0
|
||||
v_mov_b32_e32(v[1], 0x60), # bits 5 and 6 (+-zero)
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "VCC should be 1 for +zero with mask 0x60")
|
||||
|
||||
def test_cmp_class_f16_combined_mask_1f8(self):
|
||||
"""V_CMP_CLASS_F16: mask 0x1f8 covers -normal,-denorm,-zero,+zero,+denorm,+normal.
|
||||
|
||||
This is the exact mask used in the f16 sin kernel at PC=46.
|
||||
"""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0), # f16 +0.0
|
||||
s_mov_b32(s[0], 0x1f8),
|
||||
v_mov_b32_e32(v[1], s[0]), # mask 0x1f8
|
||||
v_cmp_class_f16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "VCC should be 1 for +zero with mask 0x1f8")
|
||||
|
||||
def test_cmp_class_f16_vop3_encoding(self):
|
||||
"""V_CMP_CLASS_F16 in VOP3 encoding (v_cmp_class_f16_e64)."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 0), # f16 +0.0
|
||||
s_mov_b32(s[0], 0x1f8), # class mask
|
||||
v_cmp_class_f16_e64(VCC_LO, v[0], s[0]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "VCC should be 1 for +zero with VOP3 encoding")
|
||||
|
||||
def test_cmp_class_f16_vop3_normal_positive(self):
|
||||
"""V_CMP_CLASS_F16 VOP3 encoding with +1.0 (normal)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x3c00), # f16 +1.0
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], 0x1f8), # class mask
|
||||
v_cmp_class_f16_e64(VCC_LO, v[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "VCC should be 1 for +1.0 (normal) with mask 0x1f8")
|
||||
|
||||
def test_cmp_class_f16_vop3_nan_fails_mask(self):
|
||||
"""V_CMP_CLASS_F16 VOP3: NaN should NOT match mask 0x1f8 (no NaN bits set)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7e00), # f16 quiet NaN
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], 0x1f8), # class mask
|
||||
v_cmp_class_f16_e64(VCC_LO, v[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 0, "VCC should be 0 for NaN with mask 0x1f8 (no NaN bits)")
|
||||
|
||||
def test_cmp_class_f16_vop3_inf_fails_mask(self):
|
||||
"""V_CMP_CLASS_F16 VOP3: +inf should NOT match mask 0x1f8 (no inf bits set)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x7c00), # f16 +inf
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
s_mov_b32(s[1], 0x1f8), # class mask
|
||||
v_cmp_class_f16_e64(VCC_LO, v[0], s[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 0, "VCC should be 0 for +inf with mask 0x1f8 (no inf bits)")
|
||||
|
||||
|
||||
class TestCmpInt(unittest.TestCase):
|
||||
"""Tests for integer comparison operations."""
|
||||
|
||||
def test_v_cmp_eq_u32(self):
|
||||
"""V_CMP_EQ_U32 sets VCC bits based on per-lane comparison."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 5),
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[0]),
|
||||
v_cmp_eq_u32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=4)
|
||||
self.assertEqual(st.vcc & 0xf, 0xf, "All lanes should match")
|
||||
|
||||
def test_cmp_eq_u16_opsel_lo_lo(self):
|
||||
"""V_CMP_EQ_U16 comparing lo halves."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x12340005), # lo=5, hi=0x1234
|
||||
s_mov_b32(s[1], 0xABCD0005), # lo=5, hi=0xABCD
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_mov_b32_e32(v[1], s[1]),
|
||||
v_cmp_eq_u16_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Lo halves should be equal")
|
||||
|
||||
def test_cmp_eq_u16_opsel_hi_hi(self):
|
||||
"""V_CMP_EQ_U16 comparing hi halves with VOP3 opsel."""
|
||||
instructions = [
|
||||
s_mov_b32(s[2], 0x00051234), # hi=5, lo=0x1234
|
||||
v_mov_b32_e32(v[0], s[2]),
|
||||
s_mov_b32(s[2], 0x0005ABCD), # hi=5, lo=0xABCD
|
||||
v_mov_b32_e32(v[1], s[2]),
|
||||
v_cmp_eq_u16_e64(vdst=s[0], src0=v[0], src1=v[1], opsel=3),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[0] & 1, 1, "Hi halves should be equal: 5==5")
|
||||
|
||||
def test_cmp_eq_u16_opsel_hi_hi_equal(self):
|
||||
"""V_CMP_EQ_U16 VOP3 with opsel=3 compares hi halves (equal case)."""
|
||||
instructions = [
|
||||
s_mov_b32(s[2], 0x12340005), # lo=5, hi=0x1234
|
||||
v_mov_b32_e32(v[0], s[2]),
|
||||
s_mov_b32(s[2], 0x12340009), # lo=9, hi=0x1234
|
||||
v_mov_b32_e32(v[1], s[2]),
|
||||
v_cmp_eq_u16_e64(vdst=s[0], src0=v[0], src1=v[1], opsel=3),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[0] & 1, 1, "hi==hi should be true: 0x1234==0x1234")
|
||||
|
||||
def test_cmp_gt_u16_opsel_hi(self):
|
||||
"""V_CMP_GT_U16 VOP3 with opsel=3 compares hi halves."""
|
||||
instructions = [
|
||||
s_mov_b32(s[2], 0x99990005), # lo=5, hi=0x9999
|
||||
v_mov_b32_e32(v[0], s[2]),
|
||||
s_mov_b32(s[2], 0x12340005), # lo=5, hi=0x1234
|
||||
v_mov_b32_e32(v[1], s[2]),
|
||||
v_cmp_gt_u16_e64(vdst=s[0], src0=v[0], src1=v[1], opsel=3),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[0] & 1, 1, "hi>hi should be true: 0x9999>0x1234")
|
||||
|
||||
|
||||
class TestCmpFloat(unittest.TestCase):
|
||||
"""Tests for float comparison operations."""
|
||||
|
||||
def test_v_cmp_lt_f16_vsrc1_hi(self):
|
||||
"""V_CMP_LT_F16 with both operands from high half using VOP3 opsel."""
|
||||
instructions = [
|
||||
s_mov_b32(s[2], 0x3c000000), # hi=1.0 (f16), lo=0
|
||||
v_mov_b32_e32(v[0], s[2]),
|
||||
s_mov_b32(s[2], 0x40000000), # hi=2.0 (f16), lo=0
|
||||
v_mov_b32_e32(v[1], s[2]),
|
||||
v_cmp_lt_f16_e64(vdst=s[0], src0=v[0], src1=v[1], opsel=3),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[0] & 1, 1, "1.0 < 2.0 should be true")
|
||||
|
||||
def test_v_cmp_gt_f16_vsrc1_hi(self):
|
||||
"""V_CMP_GT_F16 with both operands from high half using VOP3 opsel."""
|
||||
instructions = [
|
||||
s_mov_b32(s[2], 0x40000000), # hi=2.0 (f16), lo=0
|
||||
v_mov_b32_e32(v[0], s[2]),
|
||||
s_mov_b32(s[2], 0x3c000000), # hi=1.0 (f16), lo=0
|
||||
v_mov_b32_e32(v[1], s[2]),
|
||||
v_cmp_gt_f16_e64(vdst=s[0], src0=v[0], src1=v[1], opsel=3),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.sgpr[0] & 1, 1, "2.0 > 1.0 should be true")
|
||||
|
||||
def test_v_cmp_eq_f16_vsrc1_hi_equal(self):
|
||||
"""v_cmp_eq_f16 with equal low and high halves."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x42004200), # hi=3.0 (0x4200), lo=3.0 (0x4200)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_cmp_eq_f16_e32(v[0], v[0].h),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Expected vcc=1 (3.0 == 3.0)")
|
||||
|
||||
def test_v_cmp_neq_f16_vsrc1_hi(self):
|
||||
"""v_cmp_neq_f16 with different low and high halves."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0x40003c00), # hi=2.0 (0x4000), lo=1.0 (0x3c00)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_cmp_lg_f16_e32(v[0], v[0].h),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 1, "Expected vcc=1 (1.0 != 2.0)")
|
||||
|
||||
def test_v_cmp_nge_f16_inf_self(self):
|
||||
"""v_cmp_nge_f16 comparing -inf with itself (unordered less than).
|
||||
|
||||
Regression test: -inf < -inf should be false (IEEE 754).
|
||||
"""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], 0xFC00FC00), # both halves = -inf (0xFC00)
|
||||
v_mov_b32_e32(v[0], s[0]),
|
||||
v_cmp_nge_f16_e32(v[0], v[0].h),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=1)
|
||||
self.assertEqual(st.vcc & 1, 0, "Expected vcc=0 (-inf >= -inf)")
|
||||
|
||||
def test_v_cmp_f16_multilane(self):
|
||||
"""v_cmp_lt_f16 with vsrc1=v128 across multiple lanes."""
|
||||
instructions = [
|
||||
# Lane 0: v0 = 0x40003c00 (hi=2.0, lo=1.0) -> 1.0 < 2.0 = true
|
||||
# Lane 1: v0 = 0x3c004000 (hi=1.0, lo=2.0) -> 2.0 < 1.0 = false
|
||||
v_mov_b32_e32(v[0], 0x40003c00), # default
|
||||
v_cmp_eq_u32_e32(1, v[255]), # vcc = (lane == 1)
|
||||
v_cndmask_b32_e64(v[0], v[0], 0x3c004000, SrcEnum.VCC_LO),
|
||||
v_cmp_lt_f16_e32(v[0], v[0].h),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=2)
|
||||
self.assertEqual(st.vcc & 1, 1, "Lane 0: expected vcc=1 (1.0 < 2.0)")
|
||||
self.assertEqual((st.vcc >> 1) & 1, 0, "Lane 1: expected vcc=0 (2.0 < 1.0)")
|
||||
|
||||
|
||||
class TestVCCBehavior(unittest.TestCase):
|
||||
"""Tests for VCC condition code behavior."""
|
||||
|
||||
def test_vcc_all_lanes_true(self):
|
||||
"""VCC should have all bits set when all lanes compare true."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 5),
|
||||
v_mov_b32_e32(v[1], 5),
|
||||
v_cmp_eq_u32_e32(v[0], v[1]),
|
||||
]
|
||||
st = run_program(instructions, n_lanes=32)
|
||||
self.assertEqual(st.vcc, 0xFFFFFFFF, "All 32 lanes should be true")
|
||||
|
||||
def test_vcc_lane_dependent(self):
|
||||
"""VCC should differ per lane based on lane_id comparison."""
|
||||
instructions = [
|
||||
v_mov_b32_e32(v[0], 16),
|
||||
v_cmp_lt_u32_e32(v[255], v[0]), # lanes 0-15 are < 16
|
||||
]
|
||||
st = run_program(instructions, n_lanes=32)
|
||||
self.assertEqual(st.vcc & 0xFFFF, 0xFFFF, "Lanes 0-15 should be true")
|
||||
self.assertEqual(st.vcc >> 16, 0x0000, "Lanes 16-31 should be false")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,48 +0,0 @@
|
||||
import unittest
|
||||
import functools
|
||||
from tinygrad import Tensor, Device, dtypes
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo
|
||||
from tinygrad.renderer import Estimates
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
from extra.assembly.amd.dsl import s, v, Inst
|
||||
|
||||
def assemble_insts(insts:list[Inst], name:str, arch:str, kernarg_size:int=8) -> tuple[UOp, UOp]:
|
||||
kd = {"kernarg_size":kernarg_size, "user_sgpr_kernarg_segment_ptr":1, "next_free_vgpr":8, "next_free_sgpr":8, "wavefront_size32":1}
|
||||
disasm = "\n".join([inst.disasm() for inst in insts])
|
||||
hsasrc = f".text\n.globl {name}\n.p2align 8\n.type fn_name,@function\n{name}:\n{disasm}\ns_code_end\n"
|
||||
hsasrc += f".rodata\n.p2align 6\n.amdhsa_kernel {name}\n"+"\n".join([f".amdhsa_{k} {v}" for k,v in kd.items()])+"\n.end_amdhsa_kernel"
|
||||
binary = HIPCompiler(arch).compile(hsasrc)
|
||||
return UOp(Ops.SOURCE, arg=disasm), UOp(Ops.BINARY, arg=binary)
|
||||
|
||||
def custom_add_one(A:UOp, arch:str) -> UOp:
|
||||
A = A.flatten()
|
||||
assert dtypes.is_float(A.dtype.base), f"buffer dtype must be float32, got {A.dtype}"
|
||||
threads = UOp.special(A.size, "lidx0")
|
||||
insts = [
|
||||
s_load_b64(s[0:1], s[0:1], soffset=NULL),
|
||||
s_waitcnt(lgkmcnt=0),
|
||||
v_lshlrev_b32_e32(v[0], 2, v[0]), # element offset
|
||||
global_load_b32(v[1], v[0], saddr=s[0:1]),
|
||||
s_waitcnt(vmcnt=0),
|
||||
v_mov_b32_e32(v[2], 1.0),
|
||||
v_add_f32_e32(v[1], v[1], v[2]),
|
||||
global_store_b32(addr=v[0], data=v[1], saddr=s[0:1]),
|
||||
s_endpgm(),
|
||||
]
|
||||
sink = UOp.sink(A.base, threads, arg=KernelInfo(name:=f"custom_add_one_{A.size}", estimates=Estimates(ops=A.size, mem=A.size*4*2)))
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=(*sink.src, sink)), *assemble_insts(insts, name, arch)))
|
||||
|
||||
class TestCustomKernel(unittest.TestCase):
|
||||
def test_simple(self):
|
||||
a = Tensor.full((16, 16), 1.).contiguous().realize()
|
||||
a = Tensor.custom_kernel(a, fxn=functools.partial(custom_add_one, arch=Device[Device.DEFAULT].arch))[0]
|
||||
ei = a.schedule()[-1].lower()
|
||||
self.assertEqual(ei.prg.estimates.ops, a.numel())
|
||||
self.assertEqual(ei.prg.estimates.mem, a.nbytes()*2)
|
||||
ei.run()
|
||||
self.assertTrue((a.numpy() == 2.).all())
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -1,258 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Integration test: round-trip RDNA3 assembly through AMD toolchain."""
|
||||
import unittest, io, sys
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
|
||||
def waitcnt(vmcnt: int = 0x3f, expcnt: int = 0x7, lgkmcnt: int = 0x3f) -> int:
|
||||
return (expcnt & 0x7) | ((lgkmcnt & 0x3f) << 4) | ((vmcnt & 0x3f) << 10)
|
||||
|
||||
def disassemble(lib: bytes, arch: str = "gfx1100") -> str:
|
||||
"""Disassemble ELF binary using tinygrad's compiler, return raw output."""
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
old_stdout = sys.stdout
|
||||
sys.stdout = io.StringIO()
|
||||
HIPCompiler(arch).disassemble(lib)
|
||||
output = sys.stdout.getvalue()
|
||||
sys.stdout = old_stdout
|
||||
return output
|
||||
|
||||
def parse_disassembly(raw: str) -> list[str]:
|
||||
"""Parse disassembly output to list of instruction mnemonics."""
|
||||
lines = []
|
||||
for line in raw.splitlines():
|
||||
if line.startswith('\t'):
|
||||
instr = line.split('//')[0].strip()
|
||||
if instr: lines.append(instr)
|
||||
return lines
|
||||
|
||||
def assemble_and_disassemble(instructions: list, arch: str = "gfx1100") -> list[str]:
|
||||
"""Assemble instructions with our DSL, then disassemble with AMD toolchain."""
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
|
||||
# Generate bytes from our DSL
|
||||
code_bytes = b''.join(inst.to_bytes() for inst in instructions)
|
||||
|
||||
# Wrap in minimal ELF-compatible assembly with .byte directives
|
||||
byte_str = ', '.join(f'0x{b:02x}' for b in code_bytes)
|
||||
asm_src = f".text\n.globl test\n.p2align 8\n.type test,@function\ntest:\n.byte {byte_str}\n"
|
||||
|
||||
# Assemble with AMD COMGR and disassemble
|
||||
lib = HIPCompiler(arch).compile(asm_src)
|
||||
return parse_disassembly(disassemble(lib, arch))
|
||||
|
||||
class TestIntegration(unittest.TestCase):
|
||||
"""Test our DSL output matches LLVM disassembly."""
|
||||
|
||||
def test_simple_sop1(self):
|
||||
"""Test SOP1 instructions round-trip."""
|
||||
instructions = [
|
||||
s_mov_b32(s[0], s[1]),
|
||||
s_mov_b32(s[2], 0),
|
||||
s_not_b32(s[3], s[4]),
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
self.assertIn('s_mov_b32', disasm[0])
|
||||
self.assertIn('s_mov_b32', disasm[1])
|
||||
self.assertIn('s_not_b32', disasm[2])
|
||||
|
||||
def test_simple_sop2(self):
|
||||
"""Test SOP2 instructions round-trip."""
|
||||
instructions = [
|
||||
s_add_u32(s[0], s[1], s[2]),
|
||||
s_sub_u32(s[3], s[4], 10),
|
||||
s_and_b32(s[5], s[6], s[7]),
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
self.assertIn('s_add_u32', disasm[0])
|
||||
self.assertIn('s_sub_u32', disasm[1])
|
||||
self.assertIn('s_and_b32', disasm[2])
|
||||
|
||||
def test_simple_vop2(self):
|
||||
"""Test VOP2 instructions round-trip."""
|
||||
instructions = [
|
||||
v_add_f32_e32(v[0], v[1], v[2]),
|
||||
v_mul_f32_e32(v[3], 1.0, v[4]), # 1.0 is inline constant
|
||||
v_and_b32_e32(v[5], 10, v[6]), # small inline constant
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
self.assertIn('v_add_f32', disasm[0])
|
||||
self.assertIn('v_mul_f32', disasm[1])
|
||||
|
||||
def test_control_flow(self):
|
||||
"""Test control flow instructions."""
|
||||
instructions = [
|
||||
s_waitcnt(simm16=waitcnt(lgkmcnt=0)),
|
||||
s_endpgm(),
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
self.assertIn('s_waitcnt', disasm[0])
|
||||
self.assertIn('s_endpgm', disasm[1])
|
||||
|
||||
def test_memory_ops(self):
|
||||
"""Test memory instructions."""
|
||||
instructions = [
|
||||
s_load_b32(s[0], s[0:1], NULL),
|
||||
s_waitcnt(simm16=waitcnt(lgkmcnt=0)),
|
||||
global_store_b32(addr=v[0:1], data=v[2], saddr=OFF),
|
||||
s_endpgm(),
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
self.assertIn('s_load_b32', disasm[0])
|
||||
self.assertIn('s_waitcnt', disasm[1])
|
||||
self.assertIn('global_store_b32', disasm[2])
|
||||
|
||||
def test_full_kernel(self):
|
||||
"""Test a complete kernel similar to tinygrad output."""
|
||||
# Simple kernel: load value, add 1, store back
|
||||
instructions = [
|
||||
# Get thread ID
|
||||
v_mov_b32_e32(v[0], s[0]), # base addr low
|
||||
v_mov_b32_e32(v[1], s[1]), # base addr high
|
||||
# Load value
|
||||
global_load_b32(vdst=v[2], addr=v[0:1], saddr=OFF),
|
||||
s_waitcnt(simm16=waitcnt(vmcnt=0)),
|
||||
# Add 1.0
|
||||
v_add_f32_e32(v[2], 1.0, v[2]),
|
||||
# Store result
|
||||
global_store_b32(addr=v[0:1], data=v[2], saddr=OFF),
|
||||
s_endpgm(),
|
||||
]
|
||||
disasm = assemble_and_disassemble(instructions)
|
||||
# Verify key instructions are present
|
||||
self.assertTrue(any('global_load' in d for d in disasm))
|
||||
self.assertTrue(any('v_add_f32' in d for d in disasm))
|
||||
self.assertTrue(any('global_store' in d for d in disasm))
|
||||
self.assertTrue(any('s_endpgm' in d for d in disasm))
|
||||
|
||||
def test_bytes_roundtrip(self):
|
||||
"""Test that our bytes match what AMD assembler produces."""
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
|
||||
# Simple instruction
|
||||
inst = s_mov_b32(s[0], s[1])
|
||||
our_bytes = inst.to_bytes()
|
||||
|
||||
# Assemble same instruction with AMD toolchain
|
||||
asm_src = ".text\n.globl test\n.p2align 8\n.type test,@function\ntest:\ns_mov_b32 s0, s1\n"
|
||||
compiler = HIPCompiler("gfx1100")
|
||||
lib = compiler.compile(asm_src)
|
||||
raw = disassemble(lib)
|
||||
|
||||
for line in raw.splitlines():
|
||||
if 's_mov_b32' in line and '//' in line:
|
||||
# Extract hex bytes from comment: "// 000000001300: BE800001"
|
||||
comment = line.split('//')[1].strip()
|
||||
hex_str = comment.split(':')[1].strip()
|
||||
# Convert big-endian hex string to little-endian bytes
|
||||
amd_bytes = bytes.fromhex(hex_str)[::-1] # reverse for little-endian
|
||||
self.assertEqual(our_bytes, amd_bytes, f"Bytes mismatch: ours={our_bytes.hex()} AMD={amd_bytes.hex()}")
|
||||
return
|
||||
self.fail("Could not find s_mov_b32 in disassembly")
|
||||
|
||||
class TestTinygradIntegration(unittest.TestCase):
|
||||
"""Test that we can parse disassembled tinygrad kernels."""
|
||||
|
||||
def test_simple_add_kernel(self):
|
||||
"""Generate a simple add kernel from tinygrad and verify disassembly."""
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.codegen import get_program
|
||||
from tinygrad.renderer.cstyle import AMDHIPRenderer
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
from tinygrad.uop.ops import Ops
|
||||
|
||||
# Create a computation that generates a real kernel
|
||||
a = Tensor([1.0, 2.0, 3.0, 4.0]).realize()
|
||||
b = Tensor([5.0, 6.0, 7.0, 8.0]).realize()
|
||||
c = a + b
|
||||
|
||||
# Get schedule and find SINK
|
||||
schedule = c.schedule()
|
||||
sink_items = [si for si in schedule if si.ast.op == Ops.SINK]
|
||||
self.assertTrue(len(sink_items) > 0, "No SINK in schedule")
|
||||
|
||||
# Generate program
|
||||
renderer = AMDHIPRenderer('gfx1100')
|
||||
prg = get_program(sink_items[0].ast, renderer)
|
||||
self.assertIsNotNone(prg.src)
|
||||
|
||||
# Compile and disassemble
|
||||
compiler = HIPCompiler('gfx1100')
|
||||
lib = compiler.compile(prg.src)
|
||||
raw_disasm = disassemble(lib)
|
||||
instrs = parse_disassembly(raw_disasm)
|
||||
|
||||
# Verify we got some instructions
|
||||
self.assertTrue(len(instrs) > 0, "No instructions in disassembly")
|
||||
# Should have an endpgm
|
||||
self.assertTrue(any('s_endpgm' in i for i in instrs), "Missing s_endpgm")
|
||||
|
||||
def test_matmul_kernel(self):
|
||||
"""Generate a matmul kernel and verify disassembly has expected patterns."""
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.codegen import get_program
|
||||
from tinygrad.renderer.cstyle import AMDHIPRenderer
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
from tinygrad.uop.ops import Ops
|
||||
|
||||
# Create a small matmul
|
||||
a = Tensor.rand(4, 4).realize()
|
||||
b = Tensor.rand(4, 4).realize()
|
||||
c = a @ b
|
||||
|
||||
# Get schedule
|
||||
schedule = c.schedule()
|
||||
sink_items = [si for si in schedule if si.ast.op == Ops.SINK]
|
||||
self.assertTrue(len(sink_items) > 0)
|
||||
|
||||
# Generate and compile
|
||||
renderer = AMDHIPRenderer('gfx1100')
|
||||
prg = get_program(sink_items[0].ast, renderer)
|
||||
compiler = HIPCompiler('gfx1100')
|
||||
lib = compiler.compile(prg.src)
|
||||
raw_disasm = disassemble(lib)
|
||||
instrs = parse_disassembly(raw_disasm)
|
||||
|
||||
# Matmul should have multiply and add instructions
|
||||
has_mul = any('mul' in i.lower() for i in instrs)
|
||||
has_add = any('add' in i.lower() for i in instrs)
|
||||
self.assertTrue(has_mul or has_add, "Matmul should have mul/add ops")
|
||||
|
||||
def test_disasm_to_bytes_roundtrip(self):
|
||||
"""Parse disassembled instructions and verify we can re-encode some of them."""
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.codegen import get_program
|
||||
from tinygrad.renderer.cstyle import AMDHIPRenderer
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
from tinygrad.uop.ops import Ops
|
||||
|
||||
# Simple kernel
|
||||
a = Tensor([1.0, 2.0, 3.0, 4.0]).realize()
|
||||
b = (a * 2.0)
|
||||
|
||||
schedule = b.schedule()
|
||||
sink_items = [si for si in schedule if si.ast.op == Ops.SINK]
|
||||
if not sink_items: return # skip if no kernel
|
||||
|
||||
renderer = AMDHIPRenderer('gfx1100')
|
||||
prg = get_program(sink_items[0].ast, renderer)
|
||||
compiler = HIPCompiler('gfx1100')
|
||||
lib = compiler.compile(prg.src)
|
||||
raw_disasm = disassemble(lib)
|
||||
|
||||
# Find s_endpgm and verify we can encode it
|
||||
for line in raw_disasm.splitlines():
|
||||
if 's_endpgm' in line and '//' in line:
|
||||
# Extract bytes from comment
|
||||
comment = line.split('//')[1].strip()
|
||||
hex_str = comment.split(':')[1].strip()
|
||||
amd_bytes = bytes.fromhex(hex_str)[::-1]
|
||||
|
||||
# Our encoding
|
||||
our_inst = s_endpgm()
|
||||
our_bytes = our_inst.to_bytes()
|
||||
|
||||
self.assertEqual(our_bytes, amd_bytes, f"s_endpgm mismatch: ours={our_bytes.hex()} AMD={amd_bytes.hex()}")
|
||||
return
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -1,403 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Tests for the RDNA3 pseudocode DSL."""
|
||||
import unittest
|
||||
from extra.assembly.amd.pcode import (Reg, TypedView, TypedView, MASK32, MASK64,
|
||||
_f32, _i32, _f16, _i16, f32_to_f16, isNAN, _bf16, _ibf16, bf16_to_f32, f32_to_bf16,
|
||||
BYTE_PERMUTE, v_sad_u8, v_msad_u8, _compile_pseudocode, _expr, compile_pseudocode)
|
||||
from extra.assembly.amd.test.helpers import ExecContext
|
||||
from extra.assembly.amd.autogen.rdna3.str_pcode import PCODE
|
||||
from extra.assembly.amd.autogen.rdna3.enum import VOP3SDOp, VOPCOp
|
||||
|
||||
# Compile pseudocode functions on demand for regression tests
|
||||
_VOP3SDOp_V_DIV_SCALE_F32 = compile_pseudocode('VOP3SDOp', 'V_DIV_SCALE_F32', PCODE[VOP3SDOp.V_DIV_SCALE_F32])
|
||||
_VOPCOp_V_CMP_CLASS_F32 = compile_pseudocode('VOPCOp', 'V_CMP_CLASS_F32', PCODE[VOPCOp.V_CMP_CLASS_F32_E32])
|
||||
|
||||
class TestReg(unittest.TestCase):
|
||||
def test_u32_read(self):
|
||||
r = Reg(0xDEADBEEF)
|
||||
self.assertEqual(int(r.u32), 0xDEADBEEF)
|
||||
|
||||
def test_u32_write(self):
|
||||
r = Reg(0)
|
||||
r.u32 = 0x12345678
|
||||
self.assertEqual(r._val, 0x12345678)
|
||||
|
||||
def test_f32_read(self):
|
||||
r = Reg(0x40400000) # 3.0f
|
||||
self.assertAlmostEqual(float(r.f32), 3.0)
|
||||
|
||||
def test_f32_write(self):
|
||||
r = Reg(0)
|
||||
r.f32 = 3.0
|
||||
self.assertEqual(r._val, 0x40400000)
|
||||
|
||||
def test_i32_signed(self):
|
||||
r = Reg(0xFFFFFFFF) # -1 as signed
|
||||
self.assertEqual(int(r.i32), -1)
|
||||
|
||||
def test_u64(self):
|
||||
r = Reg(0xDEADBEEFCAFEBABE)
|
||||
self.assertEqual(int(r.u64), 0xDEADBEEFCAFEBABE)
|
||||
|
||||
def test_f64(self):
|
||||
r = Reg(0x4008000000000000) # 3.0 as f64
|
||||
self.assertAlmostEqual(float(r.f64), 3.0)
|
||||
|
||||
class TestTypedView(unittest.TestCase):
|
||||
def test_bit_slice(self):
|
||||
r = Reg(0xDEADBEEF)
|
||||
# Slices return TypedView which supports .u32, .u16 etc (matching pseudocode like S1.u32[1:0].u32)
|
||||
self.assertEqual(r.u32[7:0].u32, 0xEF)
|
||||
self.assertEqual(r.u32[15:8].u32, 0xBE)
|
||||
self.assertEqual(r.u32[23:16].u32, 0xAD)
|
||||
self.assertEqual(r.u32[31:24].u32, 0xDE)
|
||||
# Also works with int() for arithmetic
|
||||
self.assertEqual(int(r.u32[7:0]), 0xEF)
|
||||
|
||||
def test_single_bit_read(self):
|
||||
r = Reg(0b11010101)
|
||||
self.assertEqual(r.u32[0], 1)
|
||||
self.assertEqual(r.u32[1], 0)
|
||||
self.assertEqual(r.u32[2], 1)
|
||||
self.assertEqual(r.u32[3], 0)
|
||||
|
||||
def test_single_bit_write(self):
|
||||
r = Reg(0)
|
||||
r.u32[5] = 1
|
||||
r.u32[3] = 1
|
||||
self.assertEqual(r._val, 0b00101000)
|
||||
|
||||
def test_nested_bit_access(self):
|
||||
# S0.u32[S1.u32[4:0]] - access bit at position from another register
|
||||
s0 = Reg(0b11010101)
|
||||
s1 = Reg(3)
|
||||
bit_pos = s1.u32[4:0] # TypedView, int value = 3
|
||||
bit_val = s0.u32[int(bit_pos)] # bit 3 of s0 = 0
|
||||
self.assertEqual(int(bit_pos), 3)
|
||||
self.assertEqual(bit_val, 0)
|
||||
|
||||
def test_arithmetic(self):
|
||||
r1 = Reg(0x40400000) # 3.0f
|
||||
r2 = Reg(0x40800000) # 4.0f
|
||||
result = r1.f32 + r2.f32
|
||||
self.assertAlmostEqual(result, 7.0)
|
||||
|
||||
def test_comparison(self):
|
||||
r1 = Reg(5)
|
||||
r2 = Reg(3)
|
||||
self.assertTrue(r1.u32 > r2.u32)
|
||||
self.assertFalse(r1.u32 < r2.u32)
|
||||
self.assertTrue(r1.u32 != r2.u32)
|
||||
|
||||
class TestTypedView(unittest.TestCase):
|
||||
def test_slice_read(self):
|
||||
r = Reg(0x56781234)
|
||||
self.assertEqual(r[15:0].u16, 0x1234)
|
||||
self.assertEqual(r[31:16].u16, 0x5678)
|
||||
|
||||
def test_slice_write(self):
|
||||
r = Reg(0)
|
||||
r[15:0].u16 = 0x1234
|
||||
r[31:16].u16 = 0x5678
|
||||
self.assertEqual(r._val, 0x56781234)
|
||||
|
||||
def test_slice_f16(self):
|
||||
r = Reg(0)
|
||||
r[15:0].f16 = 3.0
|
||||
self.assertAlmostEqual(_f16(r._val & 0xffff), 3.0, places=2)
|
||||
|
||||
class TestCompiler(unittest.TestCase):
|
||||
def test_ternary(self):
|
||||
result = _expr("a > b ? 1 : 0")
|
||||
self.assertIn("if", result)
|
||||
self.assertIn("else", result)
|
||||
|
||||
def test_type_prefix_strip(self):
|
||||
self.assertEqual(_expr("1'0U"), "0")
|
||||
self.assertEqual(_expr("32'1"), "1")
|
||||
self.assertEqual(_expr("16'0xFFFF"), "0xFFFF")
|
||||
|
||||
def test_suffix_strip(self):
|
||||
self.assertEqual(_expr("0ULL"), "0")
|
||||
self.assertEqual(_expr("1LL"), "1")
|
||||
self.assertEqual(_expr("5U"), "5")
|
||||
self.assertEqual(_expr("3.14F"), "3.14")
|
||||
|
||||
def test_boolean_ops(self):
|
||||
self.assertIn("and", _expr("a && b"))
|
||||
self.assertIn("or", _expr("a || b"))
|
||||
self.assertIn("!=", _expr("a <> b"))
|
||||
|
||||
def test_pack16(self):
|
||||
result = _expr("{ a, b }")
|
||||
self.assertIn("_pack", result)
|
||||
|
||||
def test_type_cast_strip(self):
|
||||
self.assertEqual(_expr("64'U(x)"), "(x)")
|
||||
self.assertEqual(_expr("32'I(y)"), "(y)")
|
||||
|
||||
class TestExecContext(unittest.TestCase):
|
||||
def test_float_add(self):
|
||||
ctx = ExecContext(s0=0x40400000, s1=0x40800000) # 3.0f, 4.0f
|
||||
ctx.D0.f32 = ctx.S0.f32 + ctx.S1.f32
|
||||
self.assertAlmostEqual(_f32(ctx.D0._val), 7.0)
|
||||
|
||||
def test_float_mul(self):
|
||||
ctx = ExecContext(s0=0x40400000, s1=0x40800000) # 3.0f, 4.0f
|
||||
ctx.run("D0.f32 = S0.f32 * S1.f32")
|
||||
self.assertAlmostEqual(_f32(ctx.D0._val), 12.0)
|
||||
|
||||
def test_scc_comparison(self):
|
||||
ctx = ExecContext(s0=42, s1=42)
|
||||
ctx.run("SCC = S0.u32 == S1.u32")
|
||||
self.assertEqual(ctx.SCC._val, 1)
|
||||
|
||||
def test_scc_comparison_false(self):
|
||||
ctx = ExecContext(s0=42, s1=43)
|
||||
ctx.run("SCC = S0.u32 == S1.u32")
|
||||
self.assertEqual(ctx.SCC._val, 0)
|
||||
|
||||
def test_ternary(self):
|
||||
code = _compile_pseudocode("D0.u32 = S0.u32 > S1.u32 ? 1'1U : 1'0U")
|
||||
ctx = ExecContext(s0=5, s1=3)
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val, 1)
|
||||
|
||||
def test_pack(self):
|
||||
code = _compile_pseudocode("D0 = { S1[15:0].u16, S0[15:0].u16 }")
|
||||
ctx = ExecContext(s0=0x1234, s1=0x5678)
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val, 0x56781234)
|
||||
|
||||
def test_tmp_with_typed_access(self):
|
||||
code = _compile_pseudocode("""tmp = S0.u32 + S1.u32
|
||||
D0.u32 = tmp.u32""")
|
||||
ctx = ExecContext(s0=100, s1=200)
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val, 300)
|
||||
|
||||
def test_s_add_u32_pattern(self):
|
||||
# Real pseudocode pattern from S_ADD_U32
|
||||
code = _compile_pseudocode("""tmp = 64'U(S0.u32) + 64'U(S1.u32)
|
||||
SCC = tmp >= 0x100000000ULL ? 1'1U : 1'0U
|
||||
D0.u32 = tmp.u32""")
|
||||
# Test overflow case
|
||||
ctx = ExecContext(s0=0xFFFFFFFF, s1=0x00000001)
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val, 0) # Wraps to 0
|
||||
self.assertEqual(ctx.SCC._val, 1) # Carry set
|
||||
|
||||
def test_s_add_u32_no_overflow(self):
|
||||
code = _compile_pseudocode("""tmp = 64'U(S0.u32) + 64'U(S1.u32)
|
||||
SCC = tmp >= 0x100000000ULL ? 1'1U : 1'0U
|
||||
D0.u32 = tmp.u32""")
|
||||
ctx = ExecContext(s0=100, s1=200)
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val, 300)
|
||||
self.assertEqual(ctx.SCC._val, 0) # No carry
|
||||
|
||||
def test_vcc_lane_read(self):
|
||||
ctx = ExecContext(vcc=0b1010, lane=1)
|
||||
# Lane 1 is set
|
||||
self.assertEqual(ctx.VCC.u64[1], 1)
|
||||
self.assertEqual(ctx.VCC.u64[2], 0)
|
||||
|
||||
def test_vcc_lane_write(self):
|
||||
ctx = ExecContext(vcc=0, lane=0)
|
||||
ctx.VCC.u64[3] = 1
|
||||
ctx.VCC.u64[1] = 1
|
||||
self.assertEqual(ctx.VCC._val, 0b1010)
|
||||
|
||||
def test_for_loop(self):
|
||||
# CTZ pattern - find first set bit
|
||||
code = _compile_pseudocode("""tmp = -1
|
||||
for i in 0 : 31 do
|
||||
if S0.u32[i] == 1 then
|
||||
tmp = i
|
||||
endif
|
||||
endfor
|
||||
D0.i32 = tmp""")
|
||||
ctx = ExecContext(s0=0b1000) # Bit 3 is set
|
||||
ctx.run(code)
|
||||
self.assertEqual(ctx.D0._val & MASK32, 3)
|
||||
|
||||
def test_result_dict(self):
|
||||
ctx = ExecContext(s0=5, s1=3)
|
||||
ctx.D0.u32 = 42
|
||||
ctx.SCC._val = 1
|
||||
result = ctx.result()
|
||||
self.assertEqual(result['d0'], 42)
|
||||
self.assertEqual(result['scc'], 1)
|
||||
|
||||
class TestPseudocodeRegressions(unittest.TestCase):
|
||||
"""Regression tests for pseudocode instruction emulation bugs."""
|
||||
|
||||
def test_v_div_scale_f32_vcc_always_returned(self):
|
||||
"""V_DIV_SCALE_F32 must always return VCC, even when VCC=0 (no scaling needed).
|
||||
Bug: when VCC._val == vcc (both 0), VCC wasn't returned, so VCC bits weren't written.
|
||||
This caused division to produce wrong results for multiple lanes."""
|
||||
# Normal case: 1.0 / 3.0, no scaling needed, VCC should be 0
|
||||
s0 = 0x3f800000 # 1.0
|
||||
s1 = 0x40400000 # 3.0
|
||||
s2 = 0x3f800000 # 1.0 (numerator)
|
||||
result = _VOP3SDOp_V_DIV_SCALE_F32(s0, s1, s2, 0, 0, 0, 0, 0xffffffff, 0, None)
|
||||
# Must always have VCC in result
|
||||
self.assertIn('VCC', result, "V_DIV_SCALE_F32 must always return VCC")
|
||||
self.assertEqual(result['VCC'] & 1, 0, "VCC lane 0 should be 0 when no scaling needed")
|
||||
|
||||
def test_v_cmp_class_f32_detects_quiet_nan(self):
|
||||
"""V_CMP_CLASS_F32 must correctly identify quiet NaN vs signaling NaN.
|
||||
Bug: isQuietNAN and isSignalNAN both used math.isnan which can't distinguish them."""
|
||||
quiet_nan = 0x7fc00000 # quiet NaN: exponent=255, bit22=1
|
||||
signal_nan = 0x7f800001 # signaling NaN: exponent=255, bit22=0
|
||||
# Test quiet NaN detection (bit 1 in mask)
|
||||
s1_quiet = 0b0000000010 # bit 1 = quiet NaN
|
||||
result = _VOPCOp_V_CMP_CLASS_F32(quiet_nan, s1_quiet, 0, 0, 0, 0, 0, 0xffffffff, 0, None)
|
||||
self.assertEqual(result['D0'] & 1, 1, "Should detect quiet NaN with quiet NaN mask")
|
||||
# Test signaling NaN detection (bit 0 in mask)
|
||||
s1_signal = 0b0000000001 # bit 0 = signaling NaN
|
||||
result = _VOPCOp_V_CMP_CLASS_F32(signal_nan, s1_signal, 0, 0, 0, 0, 0, 0xffffffff, 0, None)
|
||||
self.assertEqual(result['D0'] & 1, 1, "Should detect signaling NaN with signaling NaN mask")
|
||||
# Test that quiet NaN doesn't match signaling NaN mask
|
||||
result = _VOPCOp_V_CMP_CLASS_F32(quiet_nan, s1_signal, 0, 0, 0, 0, 0, 0xffffffff, 0, None)
|
||||
self.assertEqual(result['D0'] & 1, 0, "Quiet NaN should not match signaling NaN mask")
|
||||
# Test that signaling NaN doesn't match quiet NaN mask
|
||||
result = _VOPCOp_V_CMP_CLASS_F32(signal_nan, s1_quiet, 0, 0, 0, 0, 0, 0xffffffff, 0, None)
|
||||
self.assertEqual(result['D0'] & 1, 0, "Signaling NaN should not match quiet NaN mask")
|
||||
|
||||
def testisNAN_with_typed_view(self):
|
||||
"""isNAN must work with TypedView objects, not just Python floats.
|
||||
Bug: isNAN checked isinstance(x, float) which returned False for TypedView."""
|
||||
nan_reg = Reg(0x7fc00000) # quiet NaN
|
||||
normal_reg = Reg(0x3f800000) # 1.0
|
||||
inf_reg = Reg(0x7f800000) # +inf
|
||||
self.assertTrue(isNAN(nan_reg.f32), "isNAN should return True for NaN TypedView")
|
||||
self.assertFalse(isNAN(normal_reg.f32), "isNAN should return False for normal TypedView")
|
||||
self.assertFalse(isNAN(inf_reg.f32), "isNAN should return False for inf TypedView")
|
||||
|
||||
class TestBF16(unittest.TestCase):
|
||||
"""Tests for BF16 (bfloat16) support."""
|
||||
|
||||
def test_bf16_conversion(self):
|
||||
"""Test bf16 <-> f32 conversion."""
|
||||
# bf16 is just the top 16 bits of f32
|
||||
# 1.0f = 0x3f800000, bf16 = 0x3f80
|
||||
self.assertAlmostEqual(_bf16(0x3f80), 1.0, places=2)
|
||||
self.assertEqual(_ibf16(1.0), 0x3f80)
|
||||
# 2.0f = 0x40000000, bf16 = 0x4000
|
||||
self.assertAlmostEqual(_bf16(0x4000), 2.0, places=2)
|
||||
self.assertEqual(_ibf16(2.0), 0x4000)
|
||||
# -1.0f = 0xbf800000, bf16 = 0xbf80
|
||||
self.assertAlmostEqual(_bf16(0xbf80), -1.0, places=2)
|
||||
self.assertEqual(_ibf16(-1.0), 0xbf80)
|
||||
|
||||
def test_bf16_special_values(self):
|
||||
"""Test bf16 special values (inf, nan)."""
|
||||
import math
|
||||
# +inf: f32 = 0x7f800000, bf16 = 0x7f80
|
||||
self.assertTrue(math.isinf(_bf16(0x7f80)))
|
||||
self.assertEqual(_ibf16(float('inf')), 0x7f80)
|
||||
# -inf: f32 = 0xff800000, bf16 = 0xff80
|
||||
self.assertTrue(math.isinf(_bf16(0xff80)))
|
||||
self.assertEqual(_ibf16(float('-inf')), 0xff80)
|
||||
# NaN: quiet NaN bf16 = 0x7fc0
|
||||
self.assertTrue(math.isnan(_bf16(0x7fc0)))
|
||||
self.assertEqual(_ibf16(float('nan')), 0x7fc0)
|
||||
|
||||
def test_bf16_register_property(self):
|
||||
"""Test Reg.bf16 property."""
|
||||
r = Reg(0)
|
||||
r.bf16 = 3.0 # 3.0f = 0x40400000, bf16 = 0x4040
|
||||
self.assertEqual(r._val & 0xffff, 0x4040)
|
||||
self.assertAlmostEqual(float(r.bf16), 3.0, places=1)
|
||||
|
||||
def test_bf16_slice_property(self):
|
||||
"""Test TypedView.bf16 property."""
|
||||
r = Reg(0x40404040) # Two bf16 3.0 values
|
||||
self.assertAlmostEqual(r[15:0].bf16, 3.0, places=1)
|
||||
self.assertAlmostEqual(r[31:16].bf16, 3.0, places=1)
|
||||
|
||||
class TestBytePermute(unittest.TestCase):
|
||||
"""Tests for BYTE_PERMUTE helper function (V_PERM_B32)."""
|
||||
|
||||
def test_byte_select_0_to_7(self):
|
||||
"""Test selecting bytes 0-7 from 64-bit data."""
|
||||
# data = {s0, s1} where s0 is bytes 0-3, s1 is bytes 4-7
|
||||
# Combined: 0x0706050403020100 (byte 0 = 0x00, byte 7 = 0x07)
|
||||
data = 0x0706050403020100
|
||||
for i in range(8):
|
||||
self.assertEqual(BYTE_PERMUTE(data, i), i, f"byte {i} should be {i}")
|
||||
|
||||
def test_sign_extend_bytes(self):
|
||||
"""Test sign extension selectors 8-11."""
|
||||
# sel 8: sign of byte 1 (bits 15:8)
|
||||
# sel 9: sign of byte 3 (bits 31:24)
|
||||
# sel 10: sign of byte 5 (bits 47:40)
|
||||
# sel 11: sign of byte 7 (bits 63:56)
|
||||
data = 0x8000800080008000 # All relevant bytes have sign bit set
|
||||
self.assertEqual(BYTE_PERMUTE(data, 8), 0xff)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 9), 0xff)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 10), 0xff)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 11), 0xff)
|
||||
data = 0x7f007f007f007f00 # No sign bits set
|
||||
self.assertEqual(BYTE_PERMUTE(data, 8), 0x00)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 9), 0x00)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 10), 0x00)
|
||||
self.assertEqual(BYTE_PERMUTE(data, 11), 0x00)
|
||||
|
||||
def test_constant_zero(self):
|
||||
"""Test selector 12 returns 0x00."""
|
||||
self.assertEqual(BYTE_PERMUTE(0xffffffffffffffff, 12), 0x00)
|
||||
|
||||
def test_constant_ff(self):
|
||||
"""Test selectors >= 13 return 0xFF."""
|
||||
for sel in [13, 14, 15, 255]:
|
||||
self.assertEqual(BYTE_PERMUTE(0, sel), 0xff, f"sel {sel} should be 0xff")
|
||||
|
||||
class TestSADHelpers(unittest.TestCase):
|
||||
"""Tests for V_SAD_U8 and V_MSAD_U8 helper functions."""
|
||||
|
||||
def test_v_sad_u8_basic(self):
|
||||
"""Test v_sad_u8 with simple values."""
|
||||
# s0 = 0x04030201, s1 = 0x04030201 -> diff = 0 for all bytes
|
||||
result = v_sad_u8(0x04030201, 0x04030201, 0)
|
||||
self.assertEqual(result, 0)
|
||||
# s0 = 0x05040302, s1 = 0x04030201 -> diff = 1+1+1+1 = 4
|
||||
result = v_sad_u8(0x05040302, 0x04030201, 0)
|
||||
self.assertEqual(result, 4)
|
||||
|
||||
def test_v_sad_u8_with_accumulator(self):
|
||||
"""Test v_sad_u8 with non-zero accumulator."""
|
||||
# s0 = 0x05040302, s1 = 0x04030201, s2 = 100 -> 4 + 100 = 104
|
||||
result = v_sad_u8(0x05040302, 0x04030201, 100)
|
||||
self.assertEqual(result, 104)
|
||||
|
||||
def test_v_sad_u8_large_diff(self):
|
||||
"""Test v_sad_u8 with maximum byte differences."""
|
||||
# s0 = 0xffffffff, s1 = 0x00000000 -> diff = 255*4 = 1020
|
||||
result = v_sad_u8(0xffffffff, 0x00000000, 0)
|
||||
self.assertEqual(result, 1020)
|
||||
|
||||
def test_v_msad_u8_basic(self):
|
||||
"""Test v_msad_u8 masks when reference byte is 0."""
|
||||
# s0 = 0x10101010, s1 = 0x00000000 -> all masked, result = 0
|
||||
result = v_msad_u8(0x10101010, 0x00000000, 0)
|
||||
self.assertEqual(result, 0)
|
||||
# s0 = 0x10101010, s1 = 0x01010101 -> diff = |0x10-0x01|*4 = 15*4 = 60
|
||||
result = v_msad_u8(0x10101010, 0x01010101, 0)
|
||||
self.assertEqual(result, 60)
|
||||
|
||||
def test_v_msad_u8_partial_mask(self):
|
||||
"""Test v_msad_u8 with partial masking."""
|
||||
# s0 = 0x10101010, s1 = 0x00010001 -> bytes 1 and 3 masked
|
||||
# diff = |0x10-0x01| + |0x10-0x01| = 15 + 15 = 30
|
||||
result = v_msad_u8(0x10101010, 0x00010001, 0)
|
||||
self.assertEqual(result, 30)
|
||||
|
||||
def test_v_msad_u8_with_accumulator(self):
|
||||
"""Test v_msad_u8 with non-zero accumulator."""
|
||||
result = v_msad_u8(0x10101010, 0x01010101, 50)
|
||||
self.assertEqual(result, 110) # 60 + 50
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,95 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
import unittest, subprocess
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
from extra.assembly.amd.test.helpers import get_llvm_mc
|
||||
|
||||
def llvm_assemble(asm: str) -> bytes:
|
||||
"""Assemble using llvm-mc and return bytes."""
|
||||
result = subprocess.run(
|
||||
[get_llvm_mc(), "-triple=amdgcn", "-mcpu=gfx1100", "-show-encoding"],
|
||||
input=asm, capture_output=True, text=True
|
||||
)
|
||||
out = b''
|
||||
for line in result.stdout.split('\n'):
|
||||
if 'encoding:' in line:
|
||||
enc = line.split('encoding:')[1].strip()
|
||||
enc = enc.strip('[]').replace('0x', '').replace(',', '')
|
||||
out += bytes.fromhex(enc)
|
||||
if not out: raise ValueError(f"no encoding found: {result.stdout} {result.stderr}")
|
||||
return out
|
||||
|
||||
class TestRDNA3Asm(unittest.TestCase):
|
||||
def test_full_program(self):
|
||||
"""Test the full program from rdna3fun.py matches llvm-mc output."""
|
||||
program = [
|
||||
v_bfe_u32(v[1], v[0], 10, 10),
|
||||
s_load_b128(s[4:7], s[0:1], NULL),
|
||||
v_and_b32_e32(v[0], 0x3FF, v[0]),
|
||||
s_mulk_i32(s[3], 0x87),
|
||||
v_mad_u64_u32(v[1:2], NULL, s[2], 3, v[1:2]),
|
||||
v_mul_u32_u24_e32(v[0], 45, v[0]),
|
||||
v_ashrrev_i32_e32(v[2], 31, v[1]),
|
||||
v_add3_u32(v[0], v[0], s[3], v[1]),
|
||||
v_lshlrev_b64(v[2:3], 2, v[1:2]),
|
||||
v_ashrrev_i32_e32(v[1], 31, v[0]),
|
||||
v_lshlrev_b64(v[0:1], 2, v[0:1]),
|
||||
s_waitcnt(0xfc07), # lgkmcnt(0)
|
||||
v_add_co_u32(v[2], VCC_LO, s[6], v[2]),
|
||||
v_add_co_ci_u32_e32(v[3], s[7], v[3]),
|
||||
v_add_co_u32(v[0], VCC_LO, s[4], v[0]),
|
||||
global_load_b32(vdst=v[2], addr=v[2:3], saddr=OFF),
|
||||
v_add_co_ci_u32_e32(v[1], s[5], v[1]),
|
||||
s_waitcnt(0x03f7), # vmcnt(0)
|
||||
global_store_b32(addr=v[0:1], data=v[2], saddr=OFF),
|
||||
s_endpgm(),
|
||||
]
|
||||
|
||||
asm = """
|
||||
v_bfe_u32 v1, v0, 10, 10
|
||||
s_load_b128 s[4:7], s[0:1], null
|
||||
v_and_b32_e32 v0, 0x3FF, v0
|
||||
s_mulk_i32 s3, 0x87
|
||||
v_mad_u64_u32 v[1:2], null, s2, 3, v[1:2]
|
||||
v_mul_u32_u24_e32 v0, 45, v0
|
||||
v_ashrrev_i32_e32 v2, 31, v1
|
||||
v_add3_u32 v0, v0, s3, v1
|
||||
v_lshlrev_b64 v[2:3], 2, v[1:2]
|
||||
v_ashrrev_i32_e32 v1, 31, v0
|
||||
v_lshlrev_b64 v[0:1], 2, v[0:1]
|
||||
s_waitcnt lgkmcnt(0)
|
||||
v_add_co_u32 v2, vcc_lo, s6, v2
|
||||
v_add_co_ci_u32_e32 v3, vcc_lo, s7, v3, vcc_lo
|
||||
v_add_co_u32 v0, vcc_lo, s4, v0
|
||||
global_load_b32 v2, v[2:3], off
|
||||
v_add_co_ci_u32_e32 v1, vcc_lo, s5, v1, vcc_lo
|
||||
s_waitcnt vmcnt(0)
|
||||
global_store_b32 v[0:1], v2, off
|
||||
s_endpgm
|
||||
"""
|
||||
expected = llvm_assemble(asm)
|
||||
for inst,rt in zip(program, asm.strip().split("\n")): print(f"{inst.disasm():50s} {rt}")
|
||||
actual = b''.join(inst.to_bytes() for inst in program)
|
||||
self.assertEqual(actual, expected)
|
||||
|
||||
def test_sop2_s_add_u32(self):
|
||||
inst = SOP2(SOP2Op.S_ADD_U32, s[3], s[0], s[1])
|
||||
expected = llvm_assemble("s_add_u32 s3, s0, s1")
|
||||
self.assertEqual(inst.to_bytes(), expected)
|
||||
|
||||
def test_vop2_v_and_b32_inline_const(self):
|
||||
inst = v_and_b32_e32(v[0], 10, v[0])
|
||||
expected = llvm_assemble("v_and_b32_e32 v0, 10, v0")
|
||||
self.assertEqual(inst.to_bytes(), expected)
|
||||
|
||||
def test_sopp_s_endpgm(self):
|
||||
inst = s_endpgm()
|
||||
expected = llvm_assemble("s_endpgm")
|
||||
self.assertEqual(inst.to_bytes(), expected)
|
||||
|
||||
def test_sop1_s_mov_b32(self):
|
||||
inst = s_mov_b32(s[0], s[1])
|
||||
expected = llvm_assemble("s_mov_b32 s0, s1")
|
||||
self.assertEqual(inst.to_bytes(), expected)
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -67,12 +67,11 @@ def export_model_clang(functions:Dict[str,str], statements:Dict[str,Tuple[str,in
|
||||
forward_args = ",".join(f"{dtype}{'*' if name not in symbolic_vars.values() else ''} {name}" for name,dtype,_ in (outputs+inputs if wasm else inputs+outputs))
|
||||
|
||||
if not wasm:
|
||||
thread_id = 0 # NOTE: export does not support threading, thread_id is always 0
|
||||
for name,cl in bufs_to_save.items():
|
||||
weight = ''.join(["\\x%02X"%x for x in bytes(to_mv(cl._buf.va_addr, cl._buf.size))])
|
||||
cprog.append(f"unsigned char {name}_data[] = \"{weight}\";")
|
||||
cprog += [f"{dtype_map[dtype]} {name}[{len}];" if name not in bufs_to_save else f"{dtype_map[dtype]} *{name} = ({dtype_map[dtype]} *){name}_data;" for name,(len,dtype,_key) in bufs.items() if name not in input_names+output_names]
|
||||
cprog += [f"void net({forward_args}) {{"] + [f"{name}({', '.join(args)}, {thread_id});" for (name, args, _global_size, _local_size) in statements] + ["}"]
|
||||
cprog += [f"void net({forward_args}) {{"] + [f"{name}({', '.join(args)});" for (name, args, _global_size, _local_size) in statements] + ["}"]
|
||||
return '\n'.join(headers + cprog)
|
||||
else:
|
||||
if bufs_to_save:
|
||||
|
||||
@@ -28,7 +28,7 @@ def custom_matmul(output: UOp, inp: UOp, weight: UOp) -> UOp:
|
||||
return store_op.sink(arg=KernelInfo(name=f"fp8_matmul_{inp.shape}x{weight.shape}"))
|
||||
|
||||
def custom_matmul_backward(gradient: UOp, kernel: UOp) -> tuple[UOp, UOp]:
|
||||
_, input_uop, weight_uop = kernel.src
|
||||
_, input_uop, weight_uop = kernel.src[1:]
|
||||
input_tensor = Tensor(input_uop, device=input_uop.device)
|
||||
grad_tensor = Tensor(gradient, device=gradient.device)
|
||||
weight_tensor = Tensor(weight_uop, device=weight_uop.device)
|
||||
|
||||
+121
-274
@@ -6,16 +6,16 @@
|
||||
# Workgroup: 128 threads (arranged as 32x4 for coalesced memory access)
|
||||
# Inner loop: 8 iterations per K-block, processing 8 columns of A and 8 rows of B
|
||||
#
|
||||
# Accumulators: 128 vgprs (v[2-117], v[120-124], v[126-129], v[131-133])
|
||||
# Accumulators: 128 vgprs (v[2-129])
|
||||
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from tinygrad import Tensor, Device, Context, GlobalCounters
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo
|
||||
from tinygrad.helpers import getenv, colored
|
||||
from tinygrad.dtype import dtypes, AddrSpace
|
||||
from tinygrad.engine.realize import Estimates
|
||||
from extra.assembly.amd.dsl import s, v, VCC_LO, NULL
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
from tinygrad.renderer.amd.dsl import s, v, VCC_LO, NULL
|
||||
from tinygrad.runtime.autogen.amd.rdna3.ins import *
|
||||
|
||||
# =============================================================================
|
||||
# Kernel constants
|
||||
@@ -27,23 +27,20 @@ LDS_B_STRIDE = 0x200 # LDS stride for B tile (512 bytes)
|
||||
LDS_BASE_OFFSET = 0x1080 # Base LDS offset for tiles
|
||||
ADDR_MASK = 0x3fffff80 # Address alignment mask
|
||||
|
||||
# s_waitcnt encodings: wait for memory operations to complete
|
||||
WAIT_LGKM = 64519 # wait for LDS/GDS/KMEM (lgkm_cnt=0)
|
||||
WAIT_ALL = 0 # wait for everything
|
||||
WAIT_VMEM = 1015 # wait for VMEM only (vm_cnt=0, lgkm_cnt=63)
|
||||
|
||||
# =============================================================================
|
||||
# Named register assignments (VGPRs) - COMPACT LAYOUT
|
||||
# Named register assignments (VGPRs)
|
||||
# =============================================================================
|
||||
V_LANE_ID_MOD8 = 182 # lane_id & 7 (column within 8-wide tile chunk)
|
||||
V_OUTPUT_ROW = 171 # output row coordinate
|
||||
V_LANE_MOD8_X4 = 174 # V_LANE_ID_MOD8 << 2 (byte offset)
|
||||
V_LANE_DIV8_X4 = 175 # (lane_id >> 3) << 2
|
||||
V_ADDR_HI_ZERO = 188 # always 0 (for 64-bit address high bits)
|
||||
V_LDS_A_BASE = 186 # LDS A-tile base address for inner loop
|
||||
V_LDS_B_BASE = 170 # LDS B-tile base address for inner loop
|
||||
V_GLOBAL_A_ADDR = 171 # global memory A prefetch address (reuses V_OUTPUT_ROW slot during main loop)
|
||||
V_GLOBAL_B_ADDR = 178 # global memory B prefetch address
|
||||
V_LANE_ID = 0 # lane_id set on startup
|
||||
# Use tile gaps (v146-159) for named regs to minimize max VGPR
|
||||
V_LANE_ID_MOD8 = 146 # lane_id & 7
|
||||
V_LANE_MOD8_X4 = 147 # (lane_id & 7) << 2
|
||||
V_LANE_DIV8_X4 = 150 # ((lane_id >> 3) & 3) << 2
|
||||
V_LDS_B_BASE = 151 # LDS B-tile base address for inner loop
|
||||
V_LDS_A_BASE = 154 # LDS A-tile base address for inner loop
|
||||
V_GLOBAL_A_ADDR = 155 # global memory A prefetch address
|
||||
V_GLOBAL_B_ADDR = 158 # global memory B prefetch address
|
||||
V_LDS_A_ADDR = 159 # single base register for A stores
|
||||
V_LDS_B_ADDR = 162 # single base register for B stores
|
||||
|
||||
# LDS tile register destinations - SEPARATE from DATA to avoid overlap
|
||||
# A on banks 2-3, B on banks 0-1 to avoid bank conflicts in VOPD
|
||||
@@ -54,18 +51,15 @@ V_B_TILE_REGS = [132, 136, 140, 144, 148, 152, 156, 160] # B tile: banks 0,0,0,
|
||||
# Named register assignments (SGPRs)
|
||||
# =============================================================================
|
||||
S_OUT_PTR = (0, 1) # output C matrix base pointer
|
||||
S_TILE_X = 2 # workgroup_x << 7
|
||||
S_TILE_Y = 3 # workgroup_y << 7
|
||||
S_WORKGROUP_X = 2 # workgroup_id_x (system SGPR, follows user SGPRs)
|
||||
S_WORKGROUP_Y = 3 # workgroup_id_y (system SGPR)
|
||||
S_DIM_N = 4 # matrix dimension N
|
||||
S_LOOP_BOUND = 7 # K-8 (loop termination bound)
|
||||
S_A_PTR = (8, 9) # A matrix base pointer
|
||||
S_B_PTR = (10, 11) # B matrix base pointer
|
||||
S_LOOP_CTR = 12 # loop counter (increments by 8)
|
||||
S_PREFETCH_FLAG = 13 # prefetch condition flag / row stride in epilogue
|
||||
S_WORKGROUP_X = 14 # workgroup_id_x
|
||||
S_WORKGROUP_Y = 15 # workgroup_id_y
|
||||
# Kernarg load destinations (before copy to working regs)
|
||||
S_KERNARG_OUT = (16, 17) # output pointer from kernarg
|
||||
S_TILE_X = 14 # workgroup_x << 7
|
||||
S_TILE_Y = 15 # workgroup_y << 7
|
||||
# Kernarg load destinations
|
||||
S_KERNARG_A = (20, 21) # A pointer from kernarg
|
||||
S_KERNARG_B = (22, 23) # B pointer from kernarg
|
||||
# Prefetch base pointers (8 pairs each, 16KB/256KB apart)
|
||||
@@ -100,8 +94,6 @@ FMAC_PAIR_ORDER = [
|
||||
|
||||
def derive_fmac_pattern(acc_grid, a_tile_regs=None, b_tile_regs=None):
|
||||
"""Generate 64 dual FMAC ops from accumulator grid with optimized iteration order."""
|
||||
if a_tile_regs is None: a_tile_regs = V_A_TILE_REGS
|
||||
if b_tile_regs is None: b_tile_regs = V_B_TILE_REGS
|
||||
pattern = []
|
||||
for idx, (a_pair, b_pair) in enumerate(FMAC_PAIR_ORDER):
|
||||
a_even, a_odd = a_pair * 2, a_pair * 2 + 1
|
||||
@@ -120,14 +112,14 @@ def derive_fmac_pattern(acc_grid, a_tile_regs=None, b_tile_regs=None):
|
||||
return pattern
|
||||
|
||||
# Derived: 64 dual FMAC operations
|
||||
FMAC_PATTERN = derive_fmac_pattern(ACC_GRID)
|
||||
FMAC_PATTERN = derive_fmac_pattern(ACC_GRID, V_A_TILE_REGS, V_B_TILE_REGS)
|
||||
|
||||
def derive_permute_swaps(acc_grid, out_regs):
|
||||
"""Derive swap sequence to permute accumulators from FMAC layout to output order.
|
||||
|
||||
After FMAC loop: acc_grid[a][b] holds C[a,b]
|
||||
Output order: for row_half in 0,1; col_group in 0-3; row_in_group in 0-3; b_off in 0-3
|
||||
-> need C[row_half*4 + row_in_group, col_group*4 + b_off] in descending reg order
|
||||
-> need C[row_half*4 + row_in_group, col_group*4 + b_off] in specified reg order
|
||||
"""
|
||||
def target_ab(i):
|
||||
row_half, col_group = i // 64, (i // 16) % 4
|
||||
@@ -150,45 +142,40 @@ def derive_permute_swaps(acc_grid, out_regs):
|
||||
return swaps
|
||||
|
||||
# Derived: swap sequence to arrange accumulators for output
|
||||
OUT_REGS = list(range(129, 1, -1))
|
||||
# Each group of 4 registers is ascending for direct global_store_b128
|
||||
OUT_REGS = [r for i in range(32) for r in range(126 - i*4, 130 - i*4)]
|
||||
PERMUTE_SWAPS = derive_permute_swaps(ACC_GRID, OUT_REGS)
|
||||
|
||||
# =============================================================================
|
||||
# LDS tile staging registers - COMPACT LAYOUT
|
||||
# LDS tile staging registers
|
||||
# =============================================================================
|
||||
# DATA regs receive contiguous global prefetch, then write to LDS
|
||||
# TILE regs receive scattered LDS loads (ds_load_b64 pairs), then feed FMACs
|
||||
# These are SEPARATE - DATA lives during prefetch/store, TILE lives during inner loop
|
||||
V_LDS_A_ADDR = 189 # single base register for A stores (use +512 offsets)
|
||||
V_LDS_A_DATA = [155, 172, 173, 154, 159, 176, 177, 158] # 8 data registers for A prefetch (mod 4: 3,0,1,2,3,0,1,2)
|
||||
V_LDS_B_ADDR = 190 # single base register for B stores (use 16-bit offsets)
|
||||
V_LDS_B_DATA = [163, 180, 181, 162, 167, 184, 185, 166] # 8 data registers for B prefetch (mod 4: 3,0,1,2,3,0,1,2)
|
||||
# Contiguous layout with mod4=[3,0,1,2,3,0,1,2] for bank conflict avoidance
|
||||
V_LDS_A_DATA = [163, 164, 165, 166, 167, 168, 169, 170]
|
||||
V_LDS_B_DATA = [171, 172, 173, 174, 175, 176, 177, 178]
|
||||
|
||||
# Initial tile prefetch: (vdst, saddr_lo) - load into A data regs using B prefetch pointers (s[24:31])
|
||||
INIT_PREFETCH = [(V_LDS_A_DATA[i], S_PREFETCH_B+2*i) for i in range(4)]
|
||||
|
||||
# Global memory prefetch schedule: (vdst1, vdst2, addr_vreg, saddr_lo1, saddr_lo2)
|
||||
# First 2 pairs from B prefetch pointers (s[32:39]), next 4 pairs from A prefetch pointers (s[40:55])
|
||||
PREFETCH_LOADS = [(V_LDS_A_DATA[4+2*i], V_LDS_A_DATA[4+2*i+1], V_GLOBAL_B_ADDR, S_PREFETCH_B+8+4*i, S_PREFETCH_B+10+4*i) for i in range(2)] + \
|
||||
[(V_LDS_B_DATA[2*(i-2)], V_LDS_B_DATA[2*(i-2)+1], V_GLOBAL_A_ADDR, S_PREFETCH_A+4*(i-2), S_PREFETCH_A+2+4*(i-2)) for i in range(2, 6)]
|
||||
|
||||
# Initial tile prefetch: (vdst, saddr_lo) - load into A data regs using B prefetch pointers (s[24:31])
|
||||
INIT_PREFETCH = [(V_LDS_A_DATA[i], S_PREFETCH_B+2*i) for i in range(4)]
|
||||
|
||||
# Initial tile loads: (vdst, addr_lo) pairs - use temp regs in accumulator gaps
|
||||
INIT_TILE_LOADS = [(23,5),(24,9),(25,7),(26,2),(27,11),(28,13),(29,6),(30,8),(31,10),(12,12),(13,14),(3,2),(4,4),(5,8),(6,6),(7,10)]
|
||||
|
||||
# A matrix row offset registers (scattered to avoid accumulator conflicts)
|
||||
ROW_REGS = [165, 146, 147, 164, 169, 150, 151, 168] # mod 4: 1,2,3,0,1,2,3,0
|
||||
|
||||
# =============================================================================
|
||||
# Kernel class
|
||||
# =============================================================================
|
||||
|
||||
class Kernel:
|
||||
def __init__(self, arch='gfx1100'):
|
||||
self.instructions, self.labels, self.branch_targets, self.arch = [], {}, {}, arch
|
||||
def __init__(self, arch='gfx1100'): self.instructions, self.labels, self.pos, self.arch = [], {}, 0, arch
|
||||
def label(self, name): self.labels[name] = self.pos
|
||||
|
||||
def emit(self, inst): self.instructions.append(inst); return inst
|
||||
def label(self, name): self.labels[name] = len(self.instructions)
|
||||
def branch_to(self, label): self.branch_targets[len(self.instructions) - 1] = label
|
||||
def emit(self, inst, target=None):
|
||||
self.instructions.append(inst)
|
||||
inst._target, inst._pos = target, self.pos
|
||||
self.pos += inst.size()
|
||||
return inst
|
||||
|
||||
def waitcnt(self, lgkm=None, vm=None):
|
||||
"""Wait for memory operations. lgkm=N waits until N lgkm ops remain, vm=N waits until N vmem ops remain."""
|
||||
@@ -196,48 +183,14 @@ class Kernel:
|
||||
waitcnt = (expcnt & 0x7) | ((lgkmcnt & 0x3f) << 4) | ((vmcnt & 0x3f) << 10)
|
||||
self.emit(s_waitcnt(simm16=waitcnt))
|
||||
|
||||
def to_asm(self):
|
||||
import re
|
||||
# Instruction stream with labels
|
||||
label_at = {pos: name for name, pos in self.labels.items()}
|
||||
body = []
|
||||
for i, inst in enumerate(self.instructions):
|
||||
if i in label_at: body.append(f'.{label_at[i]}:')
|
||||
asm = inst.disasm()
|
||||
if i in self.branch_targets:
|
||||
asm = re.sub(r'(s_cbranch_\w+|s_branch)\s+\S+', rf'\1 .{self.branch_targets[i]}', asm)
|
||||
body.append('\t' + asm)
|
||||
|
||||
# limit wave occupancy by using more LDS
|
||||
lds_size = max(LDS_SIZE, 65536//getenv("LIMIT_OCC", 65536))
|
||||
|
||||
# HSA kernel descriptor attributes (zeros included for compatibility)
|
||||
hsa = [
|
||||
('group_segment_fixed_size', lds_size), ('private_segment_fixed_size', 0), ('kernarg_size', 36),
|
||||
('user_sgpr_count', 14), ('user_sgpr_dispatch_ptr', 0), ('user_sgpr_queue_ptr', 0),
|
||||
('user_sgpr_kernarg_segment_ptr', 1), ('user_sgpr_dispatch_id', 0), ('user_sgpr_private_segment_size', 0),
|
||||
('wavefront_size32', 1), ('uses_dynamic_stack', 0), ('enable_private_segment', 0),
|
||||
('system_sgpr_workgroup_id_x', 1), ('system_sgpr_workgroup_id_y', 1), ('system_sgpr_workgroup_id_z', 0),
|
||||
('system_sgpr_workgroup_info', 0), ('system_vgpr_workitem_id', 0), ('next_free_vgpr', 192),
|
||||
('next_free_sgpr', 16), ('float_round_mode_32', 0), ('float_round_mode_16_64', 0),
|
||||
('float_denorm_mode_32', 3), ('float_denorm_mode_16_64', 3), ('dx10_clamp', 1), ('ieee_mode', 1),
|
||||
('fp16_overflow', 0), ('workgroup_processor_mode', 0), ('memory_ordered', 1), ('forward_progress', 0),
|
||||
('shared_vgpr_count', 0)]
|
||||
|
||||
return '\n'.join([
|
||||
'\t.text', f'\t.amdgcn_target "amdgcn-amd-amdhsa--{self.arch}"',
|
||||
'\t.protected\tkernel', '\t.globl\tkernel', '\t.p2align\t8', '\t.type\tkernel,@function', 'kernel:',
|
||||
*body,
|
||||
'\t.section\t.rodata,"a",@progbits', '\t.p2align\t6, 0x0', '\t.amdhsa_kernel kernel',
|
||||
*[f'\t\t.amdhsa_{k} {v}' for k, v in hsa],
|
||||
'\t.end_amdhsa_kernel', '\t.text', '.Lfunc_end0:', '\t.size\tkernel, .Lfunc_end0-kernel',
|
||||
'\t.amdgpu_metadata', '---', 'amdhsa.kernels:', ' - .args:',
|
||||
*[f' - .address_space: global\n .offset: {i*8}\n .size: 8\n .value_kind: global_buffer' for i in range(3)],
|
||||
f' .group_segment_fixed_size: {lds_size}', ' .kernarg_segment_align: 8',
|
||||
' .kernarg_segment_size: 24', ' .max_flat_workgroup_size: 128', ' .name: kernel',
|
||||
' .private_segment_fixed_size: 0', ' .sgpr_count: 60', ' .symbol: kernel.kd',
|
||||
' .vgpr_count: 192', ' .wavefront_size: 32', f'amdhsa.target: amdgcn-amd-amdhsa--{self.arch}',
|
||||
'amdhsa.version:', ' - 1', ' - 2', '...', '\t.end_amdgpu_metadata'])
|
||||
def finalize(self):
|
||||
"""Patch branch offsets and return the finalized instruction list."""
|
||||
for inst in self.instructions:
|
||||
if inst._target is None: continue
|
||||
offset_dwords = (self.labels[inst._target] - inst._pos - inst.size()) // 4
|
||||
if not -32768 <= offset_dwords <= 32767: raise ValueError(f"branch to '{inst._target}' offset {offset_dwords} exceeds simm16 range")
|
||||
inst.simm16 = offset_dwords
|
||||
return self.instructions
|
||||
|
||||
|
||||
# =============================================================================
|
||||
@@ -251,27 +204,20 @@ def build_kernel(arch='gfx1100'):
|
||||
# PROLOGUE: Load kernel arguments, compute tile coordinates and addresses
|
||||
# ===========================================================================
|
||||
k.emit(s_load_b128(sdata=s[S_KERNARG_A[0]:S_KERNARG_B[1]], sbase=s[0:1], offset=0x0, soffset=NULL))
|
||||
k.emit(s_load_b64(sdata=s[S_KERNARG_OUT[0]:S_KERNARG_OUT[1]], sbase=s[0:1], offset=0x10, soffset=NULL))
|
||||
k.emit(s_load_b64(sdata=s[S_OUT_PTR[0]:S_OUT_PTR[1]], sbase=s[0:1], offset=0x10, soffset=NULL))
|
||||
k.emit(s_mov_b32(s[S_DIM_N], MATRIX_DIM))
|
||||
k.emit(s_mov_b32(s[S_LOOP_CTR], 0)) # used by LDS swizzle, always 0 for valid workgroups
|
||||
k.emit(s_lshl_b32(s[S_TILE_X], s[S_WORKGROUP_X], 7))
|
||||
k.emit(s_lshl_b32(s[S_TILE_Y], s[S_WORKGROUP_Y], 7))
|
||||
|
||||
# Lane-derived values
|
||||
k.emit(v_and_b32_e32(v[V_LANE_ID_MOD8], 7, v[0]))
|
||||
k.emit(v_lshrrev_b32_e32(v[4], 3, v[0]))
|
||||
k.emit(v_or_b32_e32(v[1], s[S_TILE_X], v[0]))
|
||||
k.emit(v_and_b32_e32(v[V_LANE_ID_MOD8], 7, v[V_LANE_ID]))
|
||||
k.emit(v_lshrrev_b32_e32(v[4], 3, v[V_LANE_ID]))
|
||||
k.emit(v_or_b32_e32(v[1], s[S_TILE_X], v[V_LANE_ID]))
|
||||
k.emit(v_or_b32_e32(v[22], s[S_TILE_Y], v[4]))
|
||||
k.emit(v_lshlrev_b32_e32(v[V_LANE_MOD8_X4], 2, v[V_LANE_ID_MOD8]))
|
||||
k.emit(v_mov_b32_e32(v[2], 0)) # v[1] always positive, sign extension is 0
|
||||
k.emit(v_lshlrev_b64(v[5:6], 2, v[1:2]))
|
||||
k.waitcnt(lgkm=0)
|
||||
|
||||
# Copy pointers to working registers
|
||||
k.emit(s_mov_b64(s[S_OUT_PTR[0]:S_OUT_PTR[1]], s[S_KERNARG_OUT[0]:S_KERNARG_OUT[1]]))
|
||||
k.emit(s_mov_b64(s[S_A_PTR[0]:S_A_PTR[1]], s[S_KERNARG_A[0]:S_KERNARG_A[1]]))
|
||||
k.emit(s_mov_b64(s[S_B_PTR[0]:S_B_PTR[1]], s[S_KERNARG_B[0]:S_KERNARG_B[1]]))
|
||||
|
||||
# Compute 8 A and B matrix tile base pointers for prefetch
|
||||
k.emit(s_mov_b64(s[S_PREFETCH_B:S_PREFETCH_B+1], s[S_KERNARG_B[0]:S_KERNARG_B[1]])) # B[0]: no offset
|
||||
for i in range(1, 8): # B: 16KB apart
|
||||
@@ -283,144 +229,61 @@ def build_kernel(arch='gfx1100'):
|
||||
k.emit(s_addc_u32(s[S_PREFETCH_A+i*2+1], s[S_KERNARG_A[1]], 0))
|
||||
|
||||
# Global prefetch addresses: B = (tile_x + lane_id) * 4, A = ((tile_y << 12) + (lane_id/8)*4K + lane_id%8) * 4
|
||||
k.emit(v_add_nc_u32_e32(v[V_GLOBAL_B_ADDR], s[S_TILE_X], v[0]))
|
||||
k.emit(v_add_nc_u32_e32(v[V_GLOBAL_B_ADDR], s[S_TILE_X], v[V_LANE_ID]))
|
||||
k.emit(v_lshlrev_b32_e32(v[V_GLOBAL_B_ADDR], 2, v[V_GLOBAL_B_ADDR]))
|
||||
k.emit(s_lshl_b32(s[19], s[S_TILE_Y], 12))
|
||||
k.emit(v_lshl_add_u32(v[V_GLOBAL_A_ADDR], v[4], 12, v[V_LANE_ID_MOD8])) # (lane_id/8)*4K + lane_id%8
|
||||
k.emit(v_add_nc_u32_e32(v[V_GLOBAL_A_ADDR], s[19], v[V_GLOBAL_A_ADDR]))
|
||||
k.emit(v_lshlrev_b32_e32(v[V_GLOBAL_A_ADDR], 2, v[V_GLOBAL_A_ADDR]))
|
||||
|
||||
# ===========================================================================
|
||||
# Tile address computation for initial A/B matrix loads
|
||||
# ===========================================================================
|
||||
k.emit(s_lshl_b32(s[S_LOOP_BOUND], s[S_DIM_N], 4)) # row stride = 16*N
|
||||
k.emit(v_mul_lo_u32(v[ROW_REGS[0]], v[22], s[S_DIM_N])) # A matrix row offsets
|
||||
for i in range(1, 8): k.emit(v_add_nc_u32_e32(v[ROW_REGS[i]], s[S_LOOP_BOUND], v[ROW_REGS[i-1]]))
|
||||
|
||||
def addr64(dst, base_s): # 64-bit address: v[dst:dst+1] = s[base_s:base_s+1] + v[dst]*4
|
||||
k.emit(v_mov_b32_e32(v[dst+1], 0)) # offset always positive, sign ext = 0
|
||||
k.emit(v_lshlrev_b64(v[dst:dst+1], 2, v[dst:dst+1]))
|
||||
k.emit(v_add_co_u32(v[dst], VCC_LO, s[base_s], v[dst]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[dst+1], s[base_s+1], v[dst+1]))
|
||||
|
||||
def b_addr(dst, mult, tmp=None): # B address for col + mult*N
|
||||
tmp = tmp if tmp is not None else dst
|
||||
k.emit(v_mad_u32_u24(v[tmp], s[S_DIM_N], mult, v[1]))
|
||||
if tmp != dst:
|
||||
k.emit(v_mov_b32_e32(v[tmp+1], 0)) # offset always positive
|
||||
k.emit(v_lshlrev_b64(v[dst:dst+1], 2, v[tmp:tmp+1]))
|
||||
k.emit(v_add_co_u32(v[dst], VCC_LO, s[S_B_PTR[0]], v[dst]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[dst+1], s[S_B_PTR[1]], v[dst+1]))
|
||||
else: addr64(dst, S_B_PTR[0])
|
||||
|
||||
def a_addr(dst, row_reg, tmp): # A address for row_reg + lane_id_mod8
|
||||
k.emit(v_add_nc_u32_e32(v[tmp], v[row_reg], v[V_LANE_ID_MOD8]))
|
||||
k.emit(v_mov_b32_e32(v[tmp+1], 0)) # offset always positive
|
||||
k.emit(v_lshlrev_b64(v[dst:dst+1], 2, v[tmp:tmp+1]))
|
||||
k.emit(v_add_co_u32(v[dst], VCC_LO, s[S_A_PTR[0]], v[dst]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[dst+1], s[S_A_PTR[1]], v[dst+1]))
|
||||
|
||||
# Batch 1: B addresses (cols 0-5) and loads
|
||||
k.emit(v_add_co_u32(v[5], VCC_LO, s[S_B_PTR[0]], v[5]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[6], s[S_B_PTR[1]], v[6]))
|
||||
for dst, mult in [(9,1), (7,2), (2,3), (11,4), (13,5)]: b_addr(dst, mult)
|
||||
k.emit(s_clause(simm16=5)) # 6 consecutive global loads
|
||||
for vdst, addr in INIT_TILE_LOADS[:6]: k.emit(global_load_b32(vdst=v[vdst], addr=v[addr:addr+1], saddr=NULL))
|
||||
|
||||
# Batch 2: A addresses (rows 0-4) and loads
|
||||
for dst, ri in [(6,0), (8,1), (10,2), (12,3), (14,4)]:
|
||||
k.emit(v_add_nc_u32_e32(v[dst], v[ROW_REGS[ri]], v[V_LANE_ID_MOD8]))
|
||||
addr64(dst, S_A_PTR[0])
|
||||
k.emit(s_clause(simm16=4)) # 5 consecutive global loads
|
||||
for vdst, addr in INIT_TILE_LOADS[6:11]: k.emit(global_load_b32(vdst=v[vdst], addr=v[addr:addr+1], saddr=NULL))
|
||||
|
||||
# Batch 3: B cols 6-7, A rows 5-7, and loads
|
||||
for dst, mult, tmp in [(2,6,15), (4,7,4)]: b_addr(dst, mult, tmp)
|
||||
for dst, ri, tmp in [(8,5,16), (6,6,18), (10,7,20)]: a_addr(dst, ROW_REGS[ri], tmp)
|
||||
k.emit(s_clause(simm16=4)) # 5 consecutive global loads
|
||||
for vdst, addr in INIT_TILE_LOADS[11:]: k.emit(global_load_b32(vdst=v[vdst], addr=v[addr:addr+1], saddr=NULL))
|
||||
# Do initial loads
|
||||
for vdst, saddr_lo in INIT_PREFETCH:
|
||||
k.emit(global_load_b32(vdst=v[vdst], addr=v[V_GLOBAL_B_ADDR], saddr=s[saddr_lo:saddr_lo+1]))
|
||||
for iter in range(6):
|
||||
vdst1, vdst2, addr, slo1, slo2 = PREFETCH_LOADS[iter]
|
||||
k.emit(global_load_b32(vdst=v[vdst1], addr=v[addr], saddr=s[slo1:slo1+1]))
|
||||
k.emit(global_load_b32(vdst=v[vdst2], addr=v[addr], saddr=s[slo2:slo2+1]))
|
||||
|
||||
# ===========================================================================
|
||||
# LDS store address computation (bank-conflict-avoiding swizzle)
|
||||
# ===========================================================================
|
||||
# This section computes LDS store addresses with a swizzle pattern to avoid bank conflicts.
|
||||
# Key outputs:
|
||||
# v[8]: A-tile initial store base (used only for initial stores with stride64)
|
||||
# V_LDS_B_ADDR (v145): B-tile store base (used for both initial and main loop)
|
||||
# V_LANE_DIV8_X4 (v135): (lane_id >> 3) << 2 for epilogue
|
||||
#
|
||||
# The swizzle ensures that threads in the same wavefront write to different LDS banks.
|
||||
# Formula: swizzled_addr = base + (lane_id & 7) * LDS_A_STRIDE + swizzle_offset
|
||||
# where swizzle_offset depends on (lane_id >> 3) to distribute across banks.
|
||||
|
||||
# v[22] = tile_y | (lane_id >> 3) from prologue, used as base for row offsets
|
||||
# Compute 7 row offsets for B-tile rows 1-7 (row 0 computed separately in v[9])
|
||||
k.emit(v_add_nc_u32_e32(v[9], s[S_LOOP_CTR], v[22])) # row 0 base (S_LOOP_CTR=0)
|
||||
for i in range(7): k.emit(v_or_b32_e32(v[10 + i if i < 2 else 12 + i], 16 * (i + 1), v[22])) # rows 1-7
|
||||
|
||||
# Extract sign bit of workgroup_x (always 0 for valid workgroups, used for masking)
|
||||
k.emit(s_bfe_i32(s[S_LOOP_BOUND], s[S_WORKGROUP_X], 0x10018))
|
||||
k.emit(v_add_nc_u32_e32(v[9], s[S_LOOP_CTR], v[22])) # row 0 base
|
||||
k.emit(v_and_b32_e32(v[9], ADDR_MASK, v[9]))
|
||||
k.emit(s_lshr_b32(s[S_LOOP_BOUND], s[S_LOOP_BOUND], 25))
|
||||
|
||||
# Compute masked row offsets for bank conflict avoidance pattern
|
||||
# Pattern: v[row] = row_val - (row_val & ADDR_MASK) extracts lower bits
|
||||
k.emit(v_add_nc_u32_e32(v[19], s[S_LOOP_CTR], v[10]))
|
||||
k.emit(v_add_nc_u32_e32(v[8], s[S_LOOP_BOUND], v[1])) # A-tile base computation
|
||||
for d, r in zip([20, 21, 32, 33, 34, 35], [11, 14, 15, 16, 17, 18]):
|
||||
k.emit(v_add_nc_u32_e32(v[d], s[S_LOOP_CTR], v[r]))
|
||||
k.emit(v_and_b32_e32(v[8], ADDR_MASK, v[8]))
|
||||
k.emit(v_sub_nc_u32_e32(v[9], v[22], v[9])) # row 0 swizzle offset
|
||||
for d, s_ in zip([19, 20, 21, 22, 32, 33, 34], [20, 21, 22, 32, 33, 34, 35]):
|
||||
k.emit(v_and_b32_e32(v[d], ADDR_MASK, v[s_]))
|
||||
k.emit(v_sub_nc_u32_e32(v[8], v[1], v[8])) # A-tile swizzle
|
||||
|
||||
# Apply swizzle offsets and scale to byte offsets
|
||||
k.emit(v_lshlrev_b32_e32(v[9], 2, v[9])) # row 0 offset * 4
|
||||
for r, t in zip([10, 11, 14, 15, 16, 17, 18], [19, 20, 21, 22, 32, 33, 34]):
|
||||
k.emit(v_sub_nc_u32_e32(v[r], v[r], v[t])) # rows 1-7 swizzle
|
||||
k.emit(v_bfe_u32(v[2], v[0], 3, 2)) # v[2] = (lane_id >> 3) & 3
|
||||
k.emit(v_lshlrev_b32_e32(v[8], 2, v[8])) # A-tile base * 4
|
||||
|
||||
# Compute B-tile base address: LDS_A_STRIDE * (lane_id % 8) + row0_offset
|
||||
k.emit(v_lshlrev_b32_e32(v[9], 2, v[9])) # * 4
|
||||
k.emit(v_mad_u32_u24(v[V_LDS_B_ADDR], LDS_A_STRIDE, v[V_LANE_ID_MOD8], v[9]))
|
||||
# Scale row offsets 1-7 to byte offsets (row 0 already in v[9])
|
||||
for d, r in zip([9, 10, 11, 14, 15, 16, 17], [10, 11, 14, 15, 16, 17, 18]):
|
||||
k.emit(v_lshlrev_b32_e32(v[d], 2, v[r]))
|
||||
|
||||
# For V_LDS_A_BASE and epilogue
|
||||
k.emit(v_bfe_u32(v[2], v[V_LANE_ID], 3, 2)) # v[2] = (lane_id >> 3) & 3
|
||||
k.emit(v_lshlrev_b32_e32(v[V_LANE_DIV8_X4], 2, v[2]))
|
||||
k.emit(v_add_nc_u32_e32(v[8], 0x80, v[8])) # A-tile initial store base + 128
|
||||
|
||||
# Store initial tile data to LDS
|
||||
k.waitcnt(vm=0)
|
||||
for i, (d0, d1) in enumerate([(0,1), (2,3), (4,5), (11,12)]):
|
||||
k.emit(ds_store_2addr_stride64_b32(addr=v[8], data0=v[INIT_TILE_LOADS[d0][0]], data1=v[INIT_TILE_LOADS[d1][0]], offset0=16+i*4, offset1=18+i*4))
|
||||
# B stores: single base with offsets 0,64,128,192,256,320,384,448
|
||||
for i, idx in enumerate([6,7,8,9,10,13,14,15]):
|
||||
offset = i * 64
|
||||
k.emit(ds_store_b32(addr=v[V_LDS_B_ADDR], data0=v[INIT_TILE_LOADS[idx][0]], offset0=offset & 0xFF, offset1=offset >> 8))
|
||||
|
||||
# ===========================================================================
|
||||
# INIT: Compute LDS base addresses, then zero accumulators
|
||||
# ===========================================================================
|
||||
# v[3] = v[1] & 0x7F (lower 7 bits) since S_LOOP_BOUND=0 for valid workgroups
|
||||
# Compute LDS load/store base addresses for inner loop
|
||||
k.emit(v_lshlrev_b32_e32(v[2], 4, v[2]))
|
||||
k.emit(v_add_nc_u32_e32(v[3], s[S_LOOP_BOUND], v[1]))
|
||||
k.emit(v_and_b32_e32(v[3], ADDR_MASK, v[3]))
|
||||
k.emit(v_sub_nc_u32_e32(v[3], v[1], v[3]))
|
||||
k.emit(v_and_b32_e32(v[3], 0x7F, v[1])) # simplified from 3 lines
|
||||
k.emit(v_lshl_or_b32(v[V_LDS_B_BASE], v[V_LANE_ID_MOD8], 4, LDS_BASE_OFFSET))
|
||||
k.emit(v_lshl_add_u32(v[V_LDS_A_ADDR], v[3], 2, LDS_BASE_OFFSET))
|
||||
k.emit(v_lshlrev_b32_e32(v[3], 2, v[0]))
|
||||
k.emit(v_lshlrev_b32_e32(v[3], 2, v[V_LANE_ID]))
|
||||
k.emit(v_and_or_b32(v[V_LDS_A_BASE], 0x180, v[3], v[2]))
|
||||
|
||||
# Do initial stores
|
||||
k.waitcnt(vm=0)
|
||||
for i in range(4): # A tile: 8 values via 4 stride64 stores
|
||||
k.emit(ds_store_2addr_stride64_b32(addr=v[V_LDS_A_ADDR], data0=v[V_LDS_A_DATA[i*2]], data1=v[V_LDS_A_DATA[i*2+1]], offset0=i*4, offset1=i*4+2))
|
||||
for i in range(8): # B tile: 8 values via 8 scalar stores with 64-byte spacing
|
||||
offset = i * 64
|
||||
k.emit(ds_store_b32(addr=v[V_LDS_B_ADDR], data0=v[V_LDS_B_DATA[i]], offset0=offset & 0xFF, offset1=offset >> 8))
|
||||
|
||||
# Zero all 128 accumulators using VOPD dual moves (64 instructions instead of 128)
|
||||
for i in range(0, len(OUT_REGS), 2):
|
||||
k.emit(VOPD(VOPDOp.V_DUAL_MOV_B32, VOPDOp.V_DUAL_MOV_B32, vdstx=v[OUT_REGS[i]], vdsty=v[OUT_REGS[i+1]], srcx0=0, srcy0=0))
|
||||
|
||||
k.emit(s_add_i32(s[S_LOOP_BOUND], s[S_DIM_N], -8))
|
||||
k.emit(s_add_u32(s[S_A_PTR[0]], s[S_A_PTR[0]], 32))
|
||||
k.emit(s_addc_u32(s[S_A_PTR[1]], s[S_A_PTR[1]], 0))
|
||||
|
||||
# S_LOOP_CTR is already 0 from prologue initialization
|
||||
k.emit(s_branch(simm16=0)); k.branch_to('LOOP_ENTRY')
|
||||
k.emit(s_branch(), target='LOOP_ENTRY')
|
||||
|
||||
# ===========================================================================
|
||||
# MAIN GEMM LOOP
|
||||
@@ -431,19 +294,19 @@ def build_kernel(arch='gfx1100'):
|
||||
k.label('LOOP_INC')
|
||||
k.emit(s_add_i32(s[S_LOOP_CTR], s[S_LOOP_CTR], 8))
|
||||
k.emit(s_cmp_ge_i32(s[S_LOOP_CTR], s[S_DIM_N]))
|
||||
k.emit(s_cbranch_scc1(simm16=0)); k.branch_to('EPILOGUE')
|
||||
k.emit(s_cbranch_scc1(), target='EPILOGUE')
|
||||
|
||||
k.label('LOOP_ENTRY')
|
||||
k.emit(s_cmp_lt_i32(s[S_LOOP_CTR], s[S_LOOP_BOUND]))
|
||||
k.emit(s_cselect_b32(s[S_PREFETCH_FLAG], -1, 0)) # s_cselect doesn't modify SCC
|
||||
k.emit(s_cbranch_scc0(simm16=0)); k.branch_to('SKIP_PREFETCH') # branch if loop_ctr >= loop_bound
|
||||
k.emit(s_cbranch_scc0(), target='SKIP_PREFETCH') # branch if loop_ctr >= loop_bound
|
||||
|
||||
if not NO_GLOBAL:
|
||||
# Advance prefetch pointers (VGPR)
|
||||
#k.emit(v_add_nc_u32_e32(v[V_GLOBAL_B_ADDR], 0x20000, v[V_GLOBAL_B_ADDR]))
|
||||
#k.emit(v_add_nc_u32_e32(v[V_GLOBAL_A_ADDR], 0x20, v[V_GLOBAL_A_ADDR]))
|
||||
|
||||
# Advance prefetch pointers (SGPRs, 64-bit adds)
|
||||
# Advance prefetch pointers (64-bit adds)
|
||||
k.emit(s_clause(simm16=31))
|
||||
for i in range(8):
|
||||
k.emit(s_add_u32(s[S_PREFETCH_B+i*2], s[S_PREFETCH_B+i*2], 0x20000))
|
||||
@@ -490,7 +353,7 @@ def build_kernel(arch='gfx1100'):
|
||||
k.emit(VOPD(VOPDOp.V_DUAL_FMAC_F32, VOPDOp.V_DUAL_FMAC_F32,
|
||||
vdstx=v[vdst_x], vdsty=v[vdst_y], srcx0=v[ax], vsrcx1=v[bx], srcy0=v[ay], vsrcy1=v[by]))
|
||||
|
||||
# wait for all global stores to finish
|
||||
# wait for all global loads to finish
|
||||
# then sync the warp so it's safe to store local
|
||||
k.waitcnt(vm=0)
|
||||
k.emit(s_barrier())
|
||||
@@ -507,7 +370,7 @@ def build_kernel(arch='gfx1100'):
|
||||
offset = i * 64
|
||||
k.emit(ds_store_b32(addr=v[V_LDS_B_ADDR], data0=v[V_LDS_B_DATA[i]], offset0=offset & 0xFF, offset1=offset >> 8))
|
||||
|
||||
k.emit(s_branch(simm16=0)); k.branch_to('LOOP_INC')
|
||||
k.emit(s_branch(), target='LOOP_INC')
|
||||
|
||||
# ===========================================================================
|
||||
# EPILOGUE: Permute and store results
|
||||
@@ -518,59 +381,52 @@ def build_kernel(arch='gfx1100'):
|
||||
for a, b in PERMUTE_SWAPS:
|
||||
k.emit(v_swap_b32_e32(v[a], v[b]))
|
||||
|
||||
# Compute output coordinates: v[V_LANE_ID_MOD8] = col, v[V_OUTPUT_ROW] = row
|
||||
k.emit(VOPD(VOPDOp.V_DUAL_MOV_B32, VOPDOp.V_DUAL_MOV_B32,
|
||||
vdstx=v[149], vdsty=v[150], srcx0=v[V_LANE_MOD8_X4], vsrcx1=v[0], srcy0=v[V_LANE_DIV8_X4], vsrcy1=v[0]))
|
||||
k.emit(v_and_b32_e32(v[0], 0x60, v[0]))
|
||||
k.emit(v_or_b32_e32(v[V_LANE_ID_MOD8], s[S_TILE_X], v[149]))
|
||||
k.emit(v_add_nc_u32_e32(v[0], s[S_TILE_Y], v[0]))
|
||||
k.emit(v_or_b32_e32(v[V_OUTPUT_ROW], v[0], v[150]))
|
||||
# Compute output base coordinates
|
||||
# v[130] = col_base = tile_x + (lane_id & 7) * 4
|
||||
# v[131] = row_base = tile_y + (lane_id & 0x60) + ((lane_id >> 3) & 3) * 4
|
||||
# v[132] = 0 (for 64-bit address high part)
|
||||
k.emit(v_add_nc_u32_e32(v[130], s[S_TILE_X], v[V_LANE_MOD8_X4]))
|
||||
k.emit(v_and_b32_e32(v[131], 0x60, v[V_LANE_ID]))
|
||||
k.emit(v_add_nc_u32_e32(v[131], s[S_TILE_Y], v[131]))
|
||||
k.emit(v_add_nc_u32_e32(v[131], v[V_LANE_DIV8_X4], v[131]))
|
||||
k.emit(v_mov_b32_e32(v[132], 0))
|
||||
|
||||
# Precompute row offsets: v[144-147] for rows 0-3, v[148-151] for rows 16-19
|
||||
for base, row_off in [(144, 0), (148, 16)]:
|
||||
if row_off: k.emit(v_or_b32_e32(v[1], row_off, v[V_OUTPUT_ROW]))
|
||||
k.emit(v_mul_lo_u32(v[base], v[1] if row_off else v[V_OUTPUT_ROW], s[S_DIM_N]))
|
||||
for i in range(3): k.emit(v_add_nc_u32_e32(v[base + 1 + i], s[S_DIM_N], v[base + i]))
|
||||
# Precompute row offsets: v[133-136] for rows 0-3, v[137-140] for rows 16-19
|
||||
for base, row_off in [(133, 0), (137, 16)]:
|
||||
if row_off: k.emit(v_add_nc_u32_e32(v[141], row_off, v[131]))
|
||||
k.emit(v_mul_lo_u32(v[base], v[141] if row_off else v[131], s[S_DIM_N]))
|
||||
for j in range(3): k.emit(v_add_nc_u32_e32(v[base + 1 + j], s[S_DIM_N], v[base + j]))
|
||||
|
||||
k.emit(v_mov_b32_e32(v[V_ADDR_HI_ZERO], 0))
|
||||
k.emit(s_lshl_b32(s[S_PREFETCH_FLAG], s[S_DIM_N], 2)) # row stride in bytes
|
||||
# s[S_PREFETCH_FLAG] = row stride in bytes (N * 4)
|
||||
k.emit(s_lshl_b32(s[S_PREFETCH_FLAG], s[S_DIM_N], 2))
|
||||
|
||||
# Store 128 output values as 32 groups of 4 (128-bit stores)
|
||||
# Layout: 2 row halves (0-3, 16-19) x 4 col groups x 4 rows = 32 stores of 4 floats
|
||||
epilogue_reserved = {V_LANE_ID_MOD8, V_OUTPUT_ROW, V_LANE_MOD8_X4, V_LANE_DIV8_X4, V_ADDR_HI_ZERO}
|
||||
|
||||
for i, (row_half, col_off, row_in_group) in enumerate([(rh, co, ri)
|
||||
for rh in range(2) for co in [0, 32, 64, 96] for ri in range(4)]):
|
||||
row = row_half * 16 + row_in_group
|
||||
srcs = OUT_REGS[i*4:(i+1)*4]
|
||||
src = OUT_REGS[i*4] # first reg of ascending group of 4
|
||||
|
||||
# Find temp register for scaled values (must not conflict with reserved regs)
|
||||
tmp = max(srcs) + 5
|
||||
while any(r in epilogue_reserved for r in range(tmp, tmp + 4)): tmp += 1
|
||||
if row_in_group == 0:
|
||||
# First row of group: compute full address
|
||||
if col_off == 0: k.emit(v_mov_b32_e32(v[141], v[130]))
|
||||
else: k.emit(v_add_nc_u32_e32(v[141], col_off, v[130]))
|
||||
row_base = 133 + row if row < 4 else 137 + row - 16
|
||||
k.emit(v_add_nc_u32_e32(v[141], v[row_base], v[141]))
|
||||
k.emit(v_lshlrev_b32_e32(v[141], 2, v[141]))
|
||||
k.emit(v_add_co_u32(v[141], VCC_LO, s[S_OUT_PTR[0]], v[141]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[142], s[S_OUT_PTR[1]], v[132]))
|
||||
else:
|
||||
# Subsequent rows: add stride
|
||||
k.emit(v_add_co_u32(v[141], VCC_LO, s[S_PREFETCH_FLAG], v[141]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[142], v[142], v[132]))
|
||||
|
||||
# Copy values to temp regs for output (alpha=1.0 hardcoded, so just move)
|
||||
for j, src in enumerate(srcs):
|
||||
k.emit(v_mov_b32_e32(v[tmp + j], v[src]))
|
||||
|
||||
# Compute output address
|
||||
if row_in_group == 0: # first row: compute base address for this column group
|
||||
if col_off == 0: k.emit(v_mov_b32_e32(v[0], v[V_LANE_ID_MOD8]))
|
||||
else: k.emit(v_add_nc_u32_e32(v[0], col_off, v[V_LANE_ID_MOD8]))
|
||||
row_base = 144 + row if row < 4 else 148 + row - 16
|
||||
k.emit(v_add_nc_u32_e32(v[0], v[row_base], v[0]))
|
||||
k.emit(v_lshlrev_b32_e32(v[0], 2, v[0]))
|
||||
k.emit(v_add_co_u32(v[0], VCC_LO, s[S_OUT_PTR[0]], v[0]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[1], s[S_OUT_PTR[1]], v[V_ADDR_HI_ZERO]))
|
||||
else: # subsequent rows: just add stride
|
||||
k.emit(v_add_co_u32(v[0], VCC_LO, s[S_PREFETCH_FLAG], v[0]))
|
||||
k.emit(v_add_co_ci_u32_e32(v[1], v[1], v[V_ADDR_HI_ZERO]))
|
||||
|
||||
k.emit(global_store_b128(addr=v[0:1], data=v[tmp:tmp+3], saddr=NULL))
|
||||
k.emit(global_store_b128(addr=v[141:142], data=v[src:src+3], saddr=NULL))
|
||||
|
||||
k.emit(s_sendmsg(simm16=3)) # DEALLOC_VGPRS
|
||||
k.emit(s_endpgm())
|
||||
|
||||
return k.to_asm()
|
||||
return k.finalize()
|
||||
|
||||
# =============================================================================
|
||||
# Test harness
|
||||
@@ -582,18 +438,9 @@ THREADS = 128
|
||||
|
||||
def test_matmul():
|
||||
dev = Device[Device.DEFAULT]
|
||||
print(f"Device arch: {dev.arch}")
|
||||
print(f"Device arch: {dev.renderer.arch}")
|
||||
|
||||
if getenv("STOCK", 0):
|
||||
# Load the stock kernel from amd_seb/kernel8_batched_gmem.s
|
||||
stock_path = Path(__file__).parent / "amd_seb" / "kernel8_batched_gmem.s"
|
||||
asm = stock_path.read_text()
|
||||
print(f"Loaded stock kernel from {stock_path}")
|
||||
else:
|
||||
asm = build_kernel(dev.arch)
|
||||
|
||||
binary = dev.compiler.compile(asm)
|
||||
print(f"Compiled! Binary size: {len(binary)} bytes")
|
||||
insts = build_kernel(dev.renderer.arch)
|
||||
|
||||
rng = np.random.default_rng(42)
|
||||
a = Tensor(rng.random((N, N), dtype=np.float32) - 0.5)
|
||||
@@ -608,10 +455,10 @@ def test_matmul():
|
||||
def asm_kernel(A:UOp, B:UOp, C:UOp) -> UOp:
|
||||
gidxs = [UOp.special(n, f"gidx{i}") for i,n in enumerate(grid)]
|
||||
lidxs = [UOp.special(n, f"lidx{i}") for i,n in enumerate(local)]
|
||||
sink = UOp.sink(A.base, B.base, C.base, *gidxs, *lidxs, arg=KernelInfo(name=colored("kernel", "cyan"),
|
||||
estimates=Estimates(ops=N*N*N*2, mem=N*N*4*3)))
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg=dname), UOp(Ops.LINEAR, src=(*sink.src, sink)), UOp(Ops.SOURCE, arg=asm),
|
||||
UOp(Ops.BINARY, arg=binary)))
|
||||
lds = UOp(Ops.DEFINE_LOCAL, dtypes.uint8.ptr(size=max(LDS_SIZE, 65536//getenv("LIMIT_OCC", 65536)), addrspace=AddrSpace.LOCAL), (), 'lds')
|
||||
sink = UOp.sink(A.base, B.base, C.base, lds, *gidxs, *lidxs, arg=KernelInfo(name=colored("kernel", "cyan"),
|
||||
estimates=Estimates(ops=N*N*N*2, mem=N*N*4*3)))
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg=dname), UOp(Ops.LINEAR, src=tuple([UOp(Ops.INS, arg=x) for x in insts]))))
|
||||
c = Tensor.custom_kernel(a, b, c, fxn=asm_kernel)[2]
|
||||
ei = c.schedule()[0].lower()
|
||||
|
||||
@@ -652,6 +499,6 @@ def run_sqtt():
|
||||
print(f"Wrote {len(output)} bytes to /tmp/sqtt_trace.txt")
|
||||
|
||||
if __name__ == "__main__":
|
||||
if getenv("ASM", 0): print(build_kernel(Device[Device.DEFAULT].arch))
|
||||
if getenv("ASM", 0): print("\n".join(str(inst) for inst in build_kernel(Device[Device.DEFAULT].renderer.arch)))
|
||||
elif getenv("SQTT", 0): run_sqtt()
|
||||
else: test_matmul()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,102 @@
|
||||
import atexit, functools
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
from tinygrad import Tensor, Device, dtypes
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo, AxisType
|
||||
from tinygrad.renderer import Estimates
|
||||
from tinygrad.helpers import getenv, all_same, dedup
|
||||
from extra.gemm.asm.cdna.asm import build_kernel, GEMM_ARGS
|
||||
|
||||
# ** CDNA4 assembly gemm
|
||||
|
||||
WORKGROUP_SIZE = 256
|
||||
|
||||
@functools.cache
|
||||
def custom_asm_gemm(C:UOp, A:UOp, B:UOp, dname:str, arch:str, wg:int) -> UOp:
|
||||
batch, M, K = A.shape
|
||||
K2, N = B.shape[(1 if B.ndim == 3 else 0):]
|
||||
assert K == K2
|
||||
lidx = UOp.special(WORKGROUP_SIZE, "lidx0")
|
||||
gidx = UOp.special(wg, "gidx0")
|
||||
k = build_kernel(batch, M, N, K, A.dtype.base)
|
||||
sink = UOp.sink(C.base, A.base, B.base, lidx, gidx,
|
||||
arg=KernelInfo(name=k.name, estimates=Estimates(ops=2*batch*M*N*K, mem=(batch*M*K + K*N + batch*M*N)*2)))
|
||||
# TODO: you shouldn't have to call the compiler here, BINARY should be auto-added
|
||||
binary = HIPCompiler(arch).compile(k.to_asm())
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg=dname), UOp(Ops.LINEAR, src=(*sink.src, sink)),
|
||||
UOp(Ops.SOURCE, arg=k.to_text()), UOp(Ops.BINARY, arg=binary)))
|
||||
|
||||
counters = {"used":0, "todos":[]}
|
||||
def todo(msg:str) -> bool: counters["todos"].append(msg); return False
|
||||
atexit.register(lambda: print(f'asm_gemm: {counters["used"]} used, {len(counters["todos"])} not used'))
|
||||
|
||||
def can_use_asm_gemm(a:Tensor, b:Tensor) -> bool:
|
||||
if a.dtype != b.dtype: return todo(f"dtypes must match {a.dtype} != {b.dtype}")
|
||||
if a.dtype not in {dtypes.bfloat16, dtypes.float16}: return todo(f"only bfloat16/float16, got {a.dtype}")
|
||||
batch, M, K = (1, *a.shape) if a.ndim == 2 else a.shape
|
||||
N = b.shape[1]
|
||||
# only sharding on the batch or K is tested, others might work too
|
||||
if isinstance(a.device, tuple):
|
||||
if a.ndim == 2 and a.uop.axis == 1 and b.uop.axis == 0: K //= len(a.device)
|
||||
elif a.ndim == 3 and a.uop.axis == 0 and b.uop.axis is None: batch //= len(a.device)
|
||||
else: return todo(f"sharding mismatch a.ndim={a.ndim} a.uop.axis={a.uop.axis} b.uop.axis={b.uop.axis}")
|
||||
dname = a.device[0]
|
||||
else: dname = a.device
|
||||
arch = getattr(Device[dname].renderer, "arch", "")
|
||||
if batch not in {1, 2}: return todo(f"GEMM batch size {batch}")
|
||||
if (key:=(M, N, K)) not in GEMM_ARGS and arch == "gfx950": return todo(f"GEMM shape not supported {key} on {arch}")
|
||||
return True
|
||||
|
||||
# ** UOp gemm to test Tensor.custom_kernel multi and backward correctness on non cdna4
|
||||
# note: this can be removed after we have GEMM on mixins
|
||||
|
||||
def custom_uop_gemm(C:UOp, A:UOp, B:UOp) -> UOp:
|
||||
M, K = A.shape[0]*A.shape[1], A.shape[2]
|
||||
K2, N = B.shape[(1 if B.ndim == 3 else 0):]
|
||||
assert K == K2
|
||||
m = UOp.range(M, 1, AxisType.LOOP)
|
||||
n = UOp.range(N, 2, AxisType.LOOP)
|
||||
k = UOp.range(K, 0, AxisType.REDUCE)
|
||||
mul = (A.index((m*UOp.const(dtypes.index, K)+k))*B.index((k*UOp.const(dtypes.index, N)+n))).cast(dtypes.float32)
|
||||
red = mul.reduce(k, arg=Ops.ADD, dtype=dtypes.float32).cast(C.dtype.base)
|
||||
store = C.index((m*UOp.const(dtypes.index, N)+n), ptr=True).store(red).end(m, n)
|
||||
return store.sink(arg=KernelInfo(name=f'uop_gemm_{M}_{N}_{K}'))
|
||||
|
||||
# ** backward gemm, might use the asm gemm
|
||||
|
||||
def custom_gemm_bw(gradient:UOp, kernel:UOp):
|
||||
out, a, b = kernel.src[1:]
|
||||
assert all_same([gradient.device, a.device, b.device, out.device])
|
||||
a_t, b_t, g_t = Tensor(a, device=a.device), Tensor(b, device=a.device), Tensor(gradient, device=a.device)
|
||||
# TODO: this needs to be cleaned up and done properly, the batch dim of grad and a multi need to align
|
||||
g_t = g_t[:a.shape[0]]
|
||||
grad_a = (g_t @ b_t.T).uop
|
||||
grad_b = (a_t.permute(2, 0, 1).reshape(a_t.shape[2], -1) @ g_t.reshape(-1, g_t.shape[-1])).uop
|
||||
return (None, grad_a, grad_b)
|
||||
|
||||
# ** main gemm function
|
||||
|
||||
def asm_gemm(a:Tensor, b:Tensor) -> Tensor:
|
||||
assert can_use_asm_gemm(a, b), f"{counters['todos'][-1]}"
|
||||
counters["used"] += 1
|
||||
squeeze = a.ndim == 2
|
||||
if squeeze: a = a.unsqueeze(0)
|
||||
|
||||
batch, M, K = a.shape
|
||||
N = b.shape[1]
|
||||
is_multi = isinstance(a.device, tuple)
|
||||
if (k_sharded:=is_multi and a.uop.axis == 2): K //= len(a.device)
|
||||
|
||||
if is_multi:
|
||||
out = Tensor(Tensor.empty(batch//len(a.device) if a.uop.axis==0 else batch, M, N, dtype=a.dtype, device=a.device).uop.multi(0), device=a.device)
|
||||
else:
|
||||
out = Tensor.empty(batch, M, N, dtype=a.dtype, device=a.device)
|
||||
|
||||
dname = a.device[0] if is_multi else a.device
|
||||
arch = getattr(Device[dname].renderer, "arch", "")
|
||||
if arch.startswith("gfx950") and getenv("USE_ASM", 1):
|
||||
numWG = GEMM_ARGS[(M, N, K)][0]
|
||||
out = Tensor.custom_kernel(out, a, b, fxn=functools.partial(custom_asm_gemm, dname=dname, wg=numWG, arch=arch), grad_fxn=custom_gemm_bw)[0]
|
||||
else:
|
||||
out = Tensor.custom_kernel(out, a, b, fxn=custom_uop_gemm, grad_fxn=custom_gemm_bw)[0]
|
||||
if k_sharded: out = out.sum(0)
|
||||
return out.squeeze(0) if squeeze else out
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,78 +0,0 @@
|
||||
.text
|
||||
.section .text.
|
||||
.global gemm
|
||||
.p2align 8
|
||||
.type gemm,@function
|
||||
|
||||
gemm:
|
||||
INSTRUCTIONS
|
||||
|
||||
.section .rodata,"a",@progbits
|
||||
.p2align 6, 0x0
|
||||
.amdhsa_kernel gemm
|
||||
# basic memory requirements
|
||||
.amdhsa_group_segment_fixed_size 133120
|
||||
.amdhsa_private_segment_fixed_size 0
|
||||
.amdhsa_kernarg_size 28
|
||||
# register usage (RSRC1)
|
||||
.amdhsa_next_free_vgpr 504
|
||||
.amdhsa_next_free_sgpr 96
|
||||
# workgroup / workitem IDs (RSRC2)
|
||||
.amdhsa_system_sgpr_workgroup_id_x 1
|
||||
.amdhsa_system_sgpr_workgroup_id_y 1
|
||||
.amdhsa_system_sgpr_workgroup_id_z 1
|
||||
# user SGPRs, we only specify the kernel args ptr in s[0:1]
|
||||
.amdhsa_user_sgpr_kernarg_segment_ptr 1
|
||||
.amdhsa_user_sgpr_count 2
|
||||
.amdhsa_user_sgpr_kernarg_preload_length 0
|
||||
.amdhsa_user_sgpr_kernarg_preload_offset 0
|
||||
# gfx90a / gfx940 specifics (RSRC3)
|
||||
.amdhsa_accum_offset 248
|
||||
.amdhsa_uses_dynamic_stack 0
|
||||
.amdhsa_tg_split 0
|
||||
.end_amdhsa_kernel
|
||||
|
||||
.amdgpu_metadata
|
||||
---
|
||||
amdhsa.kernels:
|
||||
- .name: gemm
|
||||
.symbol: gemm.kd
|
||||
.args:
|
||||
- .name: C
|
||||
.address_space: global
|
||||
.offset: 0
|
||||
.size: 8
|
||||
.value_kind: global_buffer
|
||||
.value_type: bf16
|
||||
- .name: B
|
||||
.address_space: global
|
||||
.offset: 8
|
||||
.size: 8
|
||||
.value_kind: global_buffer
|
||||
.value_type: bf16
|
||||
- .name: A
|
||||
.address_space: global
|
||||
.offset: 16
|
||||
.size: 8
|
||||
.value_kind: global_buffer
|
||||
.value_type: bf16
|
||||
- .name: sz
|
||||
.offset: 24
|
||||
.size: 4
|
||||
.value_kind: by_value
|
||||
.value_type: u32
|
||||
.group_segment_fixed_size: 133120
|
||||
.private_segment_fixed_size: 0
|
||||
.kernarg_segment_align: 8
|
||||
.kernarg_segment_size: 28
|
||||
.max_flat_workgroup_size: 256
|
||||
.sgpr_count: 88
|
||||
.sgpr_spill_count: 0
|
||||
.vgpr_count: 248
|
||||
.vgpr_spill_count: 0
|
||||
.wavefront_size: 64
|
||||
amdhsa.version:
|
||||
- 1
|
||||
- 0
|
||||
...
|
||||
.end_amdgpu_metadata
|
||||
@@ -1,72 +0,0 @@
|
||||
# Run assembly on the AMD runtime and check correctness
|
||||
# VIZ=2 to profile
|
||||
import pathlib
|
||||
from tinygrad import Tensor, Device, dtypes, Context
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo
|
||||
from tinygrad.helpers import getenv
|
||||
|
||||
fp = pathlib.Path(__file__).parent/"gemm.s"
|
||||
|
||||
N = getenv("N", 8192)
|
||||
THREADS_PER_WG = 256
|
||||
NUM_WG = N//THREADS_PER_WG * N//THREADS_PER_WG
|
||||
|
||||
assert N % THREADS_PER_WG == 0, "N must be divisible by THREADS_PER_WG"
|
||||
|
||||
# ** generate inputs on CPU
|
||||
|
||||
scale = 10.0
|
||||
|
||||
import torch
|
||||
torch.manual_seed(0)
|
||||
A = (torch.randn(N, N, dtype=torch.float32, device="cpu") / scale).to(torch.bfloat16).contiguous()
|
||||
B = (torch.randn(N, N, dtype=torch.float32, device="cpu") / scale).to(torch.bfloat16).contiguous()
|
||||
Bt = B.t().contiguous() # transpose B for the asm gemm
|
||||
C_torch = A@B
|
||||
|
||||
# ** copy buffers to AMD
|
||||
|
||||
# input creation and validation run on the copy engine for simpler tracing
|
||||
|
||||
def from_torch(t:torch.Tensor) -> Tensor:
|
||||
return Tensor.from_blob(t.data_ptr(), t.shape, dtype=dtypes.bfloat16, device="cpu").to(Device.DEFAULT).realize()
|
||||
|
||||
C_tiny = from_torch(A) @ from_torch(B)
|
||||
C_asm = Tensor.empty_like(C_tiny)
|
||||
|
||||
# ** assembly custom kernel
|
||||
|
||||
def custom_asm_gemm(C:UOp, A:UOp, B:UOp) -> UOp:
|
||||
lidx = UOp.special(THREADS_PER_WG, "lidx0")
|
||||
gidx = UOp.special(NUM_WG, "gidx0")
|
||||
|
||||
src = (pathlib.Path(__file__).parent/"template.s").read_text().replace("INSTRUCTIONS", fp.read_text())
|
||||
|
||||
sz = UOp.variable("SZ", 256, 8192)
|
||||
|
||||
sink = UOp.sink(C.base, A.base, B.base, sz, lidx, gidx, arg=KernelInfo(name="gemm"))
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg=Device.DEFAULT), UOp(Ops.LINEAR, src=(*sink.src, sink)), UOp(Ops.SOURCE, arg=src)))
|
||||
|
||||
C_asm = Tensor.custom_kernel(C_asm, from_torch(A), from_torch(Bt), fxn=custom_asm_gemm)[0]
|
||||
|
||||
# ** run gemms
|
||||
|
||||
sched = Tensor.schedule(C_tiny, C_asm)
|
||||
eis = [si.lower() for si in sched]
|
||||
|
||||
with Context(DEBUG=2):
|
||||
for ei in eis:
|
||||
et = ei.run({"SZ":N}, wait=True)
|
||||
print(f"{(N*N*N*2 / et)*1e-12:.2f} REAL TFLOPS")
|
||||
|
||||
# ** correctness
|
||||
|
||||
import ctypes
|
||||
|
||||
def torch_bf16(t:Tensor) -> torch.tensor:
|
||||
asm_out = t.to("cpu").realize().uop.buffer._buf
|
||||
buf = (ctypes.c_uint16*C_asm.uop.size).from_address(asm_out.va_addr)
|
||||
return torch.frombuffer(buf, dtype=torch.bfloat16, count=C_asm.uop.size).reshape(C_asm.shape)
|
||||
|
||||
assert torch.allclose(torch_bf16(C_asm), C_torch, rtol=1e-2, atol=1e-3)
|
||||
assert torch.allclose(torch_bf16(C_tiny), C_torch, rtol=1e-2, atol=1e-3)
|
||||
@@ -37,7 +37,7 @@ b.copyin(row.data)
|
||||
c.copyin(mat.data)
|
||||
ret = prog(a._buf, b._buf, c._buf, global_size=[1,1,1], local_size=[8,1,1], wait=True)
|
||||
print(ret)
|
||||
out = np.frombuffer(a.as_buffer(), np.float32)
|
||||
out = np.frombuffer(a.as_memoryview(), np.float32)
|
||||
real = row.astype(np.float32)@mat.T.astype(np.float32)
|
||||
print("out:", out)
|
||||
print("real", real)
|
||||
|
||||
@@ -98,10 +98,10 @@ if __name__ == "__main__":
|
||||
# check correctness
|
||||
if getenv("VERIFY"):
|
||||
from tinygrad.engine.realize import run_schedule
|
||||
triton_buf = np.frombuffer(si.bufs[0].as_buffer(), np.float16).reshape(M,N)
|
||||
triton_buf = np.frombuffer(si.bufs[0].as_memoryview(), np.float16).reshape(M,N)
|
||||
print(triton_buf)
|
||||
run_schedule(sched)
|
||||
tinygrad_buf = np.frombuffer(si.bufs[0].as_buffer(), np.float16).reshape(M,N)
|
||||
tinygrad_buf = np.frombuffer(si.bufs[0].as_memoryview(), np.float16).reshape(M,N)
|
||||
print(tinygrad_buf)
|
||||
np.testing.assert_allclose(triton_buf, tinygrad_buf)
|
||||
print("correct!")
|
||||
|
||||
+6
-14
@@ -1,14 +1,15 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
import argparse, glob, os, time, subprocess, sys
|
||||
from tinygrad.helpers import temp
|
||||
|
||||
def scan_devs_based_on_lock(prefix:str, args) -> list[str]:
|
||||
target_dev = args.pci_bus if 'pci_bus' in args.__dir__() else ""
|
||||
|
||||
devs = []
|
||||
for dev in glob.glob(f'/tmp/{prefix}_*.lock'):
|
||||
dev_id = dev[8:-5]
|
||||
if os.path.exists(f"/sys/bus/pci/devices/{dev_id}") and dev_id.startswith(target_dev): devs.append(dev_id)
|
||||
for dev in glob.glob(temp(f'{prefix}_*.lock')):
|
||||
dev_id = dev.split('/')[-1][len(prefix)+1:-5]
|
||||
if dev_id.startswith(target_dev): devs.append(dev_id)
|
||||
return devs
|
||||
|
||||
def _do_reset_device(pci_bus): os.system(f"sudo sh -c 'echo 1 > /sys/bus/pci/devices/{pci_bus}/reset'")
|
||||
@@ -53,16 +54,7 @@ def cmd_show_pids(args):
|
||||
|
||||
for dev in devs:
|
||||
try:
|
||||
pid = subprocess.check_output(['sudo', 'lsof', f'/tmp/{prefix}_{dev}.lock']).decode('utf-8').strip().split('\n')[1].split()[1]
|
||||
print(f"{dev}: {pid}")
|
||||
except subprocess.CalledProcessError: print(f"{dev}: No processes found using this device")
|
||||
|
||||
def cmd_kill_pids(args):
|
||||
devs = scan_devs_based_on_lock(prefix:={"amd":"am", "nv":"nv"}[args.backend], args)
|
||||
|
||||
for dev in devs:
|
||||
try:
|
||||
pid = subprocess.check_output(['sudo', 'lsof', f'/tmp/{prefix}_{dev}.lock']).decode('utf-8').strip().split('\n')[1].split()[1]
|
||||
pid = subprocess.check_output(['sudo', 'lsof', temp(f'{prefix}_{dev}.lock')]).decode('utf-8').strip().split('\n')[1].split()[1]
|
||||
print(f"{dev}: {pid}")
|
||||
except subprocess.CalledProcessError: print(f"{dev}: No processes found using this device")
|
||||
|
||||
@@ -74,7 +66,7 @@ def cmd_kill_pids(args):
|
||||
if i > 0: time.sleep(0.2)
|
||||
|
||||
try:
|
||||
try: pid = subprocess.check_output(['sudo', 'lsof', f'/tmp/{prefix}_{dev}.lock']).decode('utf-8').strip().split('\n')[1].split()[1]
|
||||
try: pid = subprocess.check_output(['sudo', 'lsof', temp(f'{prefix}_{dev}.lock')]).decode('utf-8').strip().split('\n')[1].split()[1]
|
||||
except subprocess.CalledProcessError: break
|
||||
|
||||
print(f"Killing process {pid} (which uses {dev})")
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -13,7 +13,7 @@ def get_struct(argp, stype):
|
||||
|
||||
def format_struct(s):
|
||||
sdats = []
|
||||
for field_name, field_type in s._fields_:
|
||||
for field_name, *_ in s._real_fields_:
|
||||
dat = getattr(s, field_name)
|
||||
if isinstance(dat, int): sdats.append(f"{field_name}:0x{dat:X}")
|
||||
else: sdats.append(f"{field_name}:{dat}")
|
||||
@@ -53,13 +53,13 @@ def print_aql_queue(read_pointer_address):
|
||||
queue_base = read_pointer_address - rptr_offset
|
||||
queue = hsa.amd_queue_v2_t.from_address(queue_base)
|
||||
print(f" AQL Queue @ 0x{queue_base:X}:")
|
||||
for field_name, field_type in hsa.amd_queue_v2_t._fields_:
|
||||
for field_name, *_ in hsa.amd_queue_v2_t._real_fields_:
|
||||
val = getattr(queue, field_name)
|
||||
if isinstance(val, int): print(f" {field_name}: 0x{val:X}")
|
||||
elif hasattr(val, '_length_'):
|
||||
arr_vals = [f"{format_struct(v)}" if hasattr(v, '_fields_') else f"{v:#X}" for v in val]
|
||||
arr_vals = [f"{format_struct(v)}" if hasattr(v, '_real_fields_') else f"{v:#X}" for v in val]
|
||||
print(f" {field_name}: [{', '.join(arr_vals)}]")
|
||||
elif hasattr(val, '_fields_'): print(f" {field_name}: {format_struct(val)}")
|
||||
elif hasattr(val, '_real_fields_'): print(f" {field_name}: {format_struct(val)}")
|
||||
else: print(f" {field_name}: {val}")
|
||||
|
||||
def ioctls_from_header():
|
||||
|
||||
@@ -18,7 +18,7 @@ prg = dev.runtime("write_ones", mbin)
|
||||
prg(buf0._buf, global_size=(1,65537,1), local_size=(1,1,1), wait=True)
|
||||
|
||||
import numpy as np
|
||||
def to_np(buf): return np.frombuffer(buf.as_buffer().cast(buf.dtype.base.fmt), dtype=_to_np_dtype(buf.dtype.base))
|
||||
def to_np(buf): return np.frombuffer(buf.as_memoryview().cast(buf.dtype.base.fmt), dtype=_to_np_dtype(buf.dtype.base))
|
||||
|
||||
big = to_np(buf0)
|
||||
print(big)
|
||||
|
||||
@@ -8,14 +8,14 @@ from tinygrad.helpers import _ensure_downloads_dir
|
||||
DOWNLOADS_DIR = _ensure_downloads_dir() / "models"
|
||||
from tinygrad.helpers import tqdm
|
||||
|
||||
def snapshot_download_with_retry(*, repo_id: str, allow_patterns: list[str]|tuple[str, ...]|None=None, cache_dir: str|Path|None=None,
|
||||
def snapshot_download_with_retry(*, repo_id: str, allow_patterns: list[str]|tuple[str, ...]|None=None, local_dir: str|Path|None=None,
|
||||
tries: int=2, **kwargs) -> Path:
|
||||
for attempt in range(tries):
|
||||
try:
|
||||
return Path(snapshot_download(
|
||||
repo_id=repo_id,
|
||||
allow_patterns=allow_patterns,
|
||||
cache_dir=str(cache_dir) if cache_dir is not None else None,
|
||||
local_dir=str(local_dir) if local_dir is not None else None,
|
||||
**kwargs
|
||||
))
|
||||
except Exception as e:
|
||||
@@ -144,14 +144,14 @@ class HuggingFaceONNXManager:
|
||||
root_path = snapshot_download_with_retry(
|
||||
repo_id=model_id,
|
||||
allow_patterns=allow_patterns,
|
||||
cache_dir=str(self.models_dir)
|
||||
local_dir=str(self.models_dir / model_id)
|
||||
)
|
||||
|
||||
# Download config files (usually small)
|
||||
snapshot_download_with_retry(
|
||||
repo_id=model_id,
|
||||
allow_patterns=["*config.json"],
|
||||
cache_dir=str(self.models_dir)
|
||||
local_dir=str(self.models_dir / model_id)
|
||||
)
|
||||
|
||||
model_data["download_path"] = str(root_path)
|
||||
|
||||
@@ -88,8 +88,8 @@ if __name__ == "__main__":
|
||||
# repo id
|
||||
# validates all onnx models inside repo
|
||||
repo_id = "/".join(path)
|
||||
root_path = snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*.onnx", "*.onnx_data"], cache_dir=DOWNLOADS_DIR)
|
||||
snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*config.json"], cache_dir=DOWNLOADS_DIR)
|
||||
root_path = snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*.onnx", "*.onnx_data"], local_dir=DOWNLOADS_DIR / repo_id)
|
||||
snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*config.json"], local_dir=DOWNLOADS_DIR / repo_id)
|
||||
config = get_config(root_path)
|
||||
for onnx_model in root_path.rglob("*.onnx"):
|
||||
rtol, atol = get_tolerances(onnx_model.name)
|
||||
@@ -101,8 +101,8 @@ if __name__ == "__main__":
|
||||
onnx_model = path[-1]
|
||||
assert path[-1].endswith(".onnx")
|
||||
repo_id, relative_path = "/".join(path[:2]), "/".join(path[2:])
|
||||
root_path = snapshot_download_with_retry(repo_id=repo_id, allow_patterns=[relative_path], cache_dir=DOWNLOADS_DIR)
|
||||
snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*config.json"], cache_dir=DOWNLOADS_DIR)
|
||||
root_path = snapshot_download_with_retry(repo_id=repo_id, allow_patterns=[relative_path], local_dir=DOWNLOADS_DIR / repo_id)
|
||||
snapshot_download_with_retry(repo_id=repo_id, allow_patterns=["*config.json"], local_dir=DOWNLOADS_DIR / repo_id)
|
||||
config = get_config(root_path)
|
||||
rtol, atol = get_tolerances(onnx_model)
|
||||
print(f"validating {relative_path} with truncate={args.truncate}, {rtol=}, {atol=}")
|
||||
|
||||
+78
-73
@@ -1,100 +1,105 @@
|
||||
import os, pathlib
|
||||
import os
|
||||
|
||||
# TODO: there is a timing bug without this
|
||||
os.environ["AMD_AQL"] = "1"
|
||||
|
||||
from tinygrad.device import Device
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler
|
||||
from tinygrad.runtime.ops_amd import AMDProgram
|
||||
from tinygrad import Tensor, Device
|
||||
from tinygrad.helpers import getenv
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo
|
||||
from tinygrad.renderer import Estimates
|
||||
from tinygrad.renderer.amd.dsl import Reg, Inst, s, v
|
||||
|
||||
NUM_WORKGROUPS = 96
|
||||
WAVE_SIZE = 32
|
||||
NUM_WAVES = 2
|
||||
NUM_WAVES = 4
|
||||
FLOPS_PER_MATMUL = 16*16*16*2
|
||||
INTERNAL_LOOP = 1_000_00
|
||||
INTERNAL_LOOP = getenv("LOOP", 10_000)
|
||||
INSTRUCTIONS_PER_LOOP = 200
|
||||
DIRECTIVE = ".amdhsa_wavefront_size32 1"
|
||||
|
||||
assemblyTemplate = (pathlib.Path(__file__).parent / "template.s").read_text()
|
||||
def repeat(insts:list[Inst], n:int, counter_sreg:Reg) -> list[Inst]:
|
||||
insts_bytes = b"".join([inst.to_bytes() for inst in insts])
|
||||
sub_inst, cmp_inst = s_sub_u32(counter_sreg, counter_sreg, 1), s_cmp_lg_i32(counter_sreg, 0)
|
||||
loop_sz = len(insts_bytes) + sub_inst.size() + cmp_inst.size()
|
||||
branch_inst = s_cbranch_scc1(simm16=-((loop_sz // 4) + 1) & 0xFFFF)
|
||||
return [s_mov_b32(counter_sreg, n)] + insts + [sub_inst, cmp_inst, branch_inst, s_endpgm()]
|
||||
|
||||
def launchBenchmark(instruction, vgprIndices, dense=True, accum=False, extra=""):
|
||||
def launchBenchmark(instruction, vgprIndices, dense=True, accum=False, **kwargs):
|
||||
if accum:
|
||||
instructions = "{} a[0:{}], v[{}:{}], v[{}:{}], 1{}\n".format(instruction, vgprIndices[0],
|
||||
vgprIndices[1], vgprIndices[2],
|
||||
vgprIndices[1], vgprIndices[2], extra)
|
||||
inst = instruction(v[0:vgprIndices[0]], v[vgprIndices[1]:vgprIndices[2]], v[vgprIndices[1]:vgprIndices[2]], 1, acc_cd=1, **kwargs)
|
||||
elif dense:
|
||||
instructions = "{} v[0:{}], v[{}:{}], v[{}:{}], 1\n".format(instruction, vgprIndices[0],
|
||||
vgprIndices[1], vgprIndices[2],
|
||||
vgprIndices[1], vgprIndices[2])
|
||||
inst = instruction(v[0:vgprIndices[0]], v[vgprIndices[1]:vgprIndices[2]], v[vgprIndices[1]:vgprIndices[2]], 1)
|
||||
else:
|
||||
instructions = "{} v[0:{}], v[{}:{}], v[{}:{}], v{}\n".format(instruction, vgprIndices[0],
|
||||
vgprIndices[1], vgprIndices[2],
|
||||
vgprIndices[3], vgprIndices[4],
|
||||
vgprIndices[5])
|
||||
src = assemblyTemplate.replace("INTERNAL_LOOP", str(INTERNAL_LOOP)).replace("INSTRUCTION", instructions*INSTRUCTIONS_PER_LOOP)
|
||||
src = src.replace("DIRECTIVE", DIRECTIVE)
|
||||
lib = COMPILER.compile(src)
|
||||
fxn = AMDProgram(DEV, "matmul", lib)
|
||||
elapsed = min([fxn(global_size=(NUM_WORKGROUPS,1,1), local_size=(WAVE_SIZE*NUM_WAVES,1,1), wait=True) for _ in range(2)])
|
||||
inst = instruction(v[0:vgprIndices[0]], v[vgprIndices[1]:vgprIndices[2]], v[vgprIndices[3]:vgprIndices[4]], v[vgprIndices[5]])
|
||||
insts = repeat([inst for _ in range(INSTRUCTIONS_PER_LOOP)], n=INTERNAL_LOOP, counter_sreg=s[1])
|
||||
def fxn(A:UOp) -> UOp:
|
||||
threads = UOp.special(WAVE_SIZE * NUM_WAVES, "lidx0")
|
||||
gidx = UOp.special(NUM_WORKGROUPS, "gidx0")
|
||||
FLOPs = FLOPS_PER_MATMUL * NUM_WAVES * NUM_WORKGROUPS * INTERNAL_LOOP * INSTRUCTIONS_PER_LOOP
|
||||
sink = UOp.sink(A.base, threads, gidx, arg=KernelInfo(inst.op.name.lower(), estimates=Estimates(ops=FLOPs, mem=0)))
|
||||
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=tuple([UOp(Ops.INS, arg=x) for x in insts]))))
|
||||
dummy = Tensor.zeros(1).contiguous().realize()
|
||||
out = Tensor.custom_kernel(dummy, fxn=fxn)[0]
|
||||
ei = out.schedule()[-1].lower()
|
||||
elapsed = min([ei.run(wait=True) for _ in range(2)])
|
||||
FLOPs = FLOPS_PER_MATMUL * NUM_WAVES * NUM_WORKGROUPS * INTERNAL_LOOP * INSTRUCTIONS_PER_LOOP
|
||||
print(f"{instruction:<29} : {FLOPs/elapsed/10**12:.2f} T(FL)OPS")
|
||||
print(f"{inst.op_name.lower():<29} : {FLOPs/elapsed/10**12:.2f} T(FL)OPS")
|
||||
|
||||
if __name__=="__main__":
|
||||
DEVICENUM = os.getenv("DEVICENUM", "0")
|
||||
try:
|
||||
DEV = Device['AMD:' + DEVICENUM]
|
||||
except:
|
||||
raise RuntimeError("Error while initiating AMD device")
|
||||
DEV = Device[Device.DEFAULT]
|
||||
arch = DEV.renderer.arch
|
||||
|
||||
COMPILER = HIPCompiler(DEV.arch)
|
||||
if DEV.arch in {'gfx1100', 'gfx1103', 'gfx1151'}:
|
||||
if DEV.arch == 'gfx1103': NUM_WORKGROUPS = 8
|
||||
if DEV.arch == 'gfx1151': NUM_WORKGROUPS = 32
|
||||
launchBenchmark("v_wmma_bf16_16x16x16_bf16", (7,8,15))
|
||||
launchBenchmark("v_wmma_f16_16x16x16_f16", (7,8,15))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_bf16", (7,8,15))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_f16", (7,8,15))
|
||||
launchBenchmark("v_wmma_i32_16x16x16_iu4", (7,8,9))
|
||||
launchBenchmark("v_wmma_i32_16x16x16_iu8", (7,8,11))
|
||||
elif DEV.arch == 'gfx1201':
|
||||
if arch in {'gfx1100', 'gfx1103', 'gfx1151'}:
|
||||
from tinygrad.runtime.autogen.amd.rdna3.ins import *
|
||||
if arch == 'gfx1103': NUM_WORKGROUPS = 8
|
||||
if arch == 'gfx1151': NUM_WORKGROUPS = 32
|
||||
launchBenchmark(v_wmma_bf16_16x16x16_bf16, (7,8,15))
|
||||
launchBenchmark(v_wmma_f16_16x16x16_f16, (7,8,15))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_bf16, (7,8,15))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_f16, (7,8,15))
|
||||
launchBenchmark(v_wmma_i32_16x16x16_iu4, (7,8,9))
|
||||
launchBenchmark(v_wmma_i32_16x16x16_iu8, (7,8,11))
|
||||
elif arch in {'gfx1200', 'gfx1201'}:
|
||||
from tinygrad.runtime.autogen.amd.rdna4.ins import *
|
||||
# this instruction does not exist in the rdna4 isa, use the co version
|
||||
s_sub_u32 = s_sub_co_u32
|
||||
NUM_WORKGROUPS = 64
|
||||
launchBenchmark("v_wmma_bf16_16x16x16_bf16", (3,4,7))
|
||||
launchBenchmark("v_wmma_f16_16x16x16_f16", (3,4,7))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_bf16", (7,8,11))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_f16", (7,8,11))
|
||||
launchBenchmark("v_wmma_i32_16x16x16_iu4", (7,8,8))
|
||||
launchBenchmark("v_wmma_i32_16x16x16_iu8", (7,8,9))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_fp8_fp8", (7,8,9))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_fp8_bf8", (7,8,9))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_bf8_fp8", (7,8,9))
|
||||
launchBenchmark("v_wmma_f32_16x16x16_bf8_bf8", (7,8,9))
|
||||
launchBenchmark(v_wmma_bf16_16x16x16_bf16, (3,4,7))
|
||||
launchBenchmark(v_wmma_f16_16x16x16_f16, (3,4,7))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_bf16, (7,8,11))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_f16, (7,8,11))
|
||||
launchBenchmark(v_wmma_i32_16x16x16_iu4, (7,8,8))
|
||||
launchBenchmark(v_wmma_i32_16x16x16_iu8, (7,8,9))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_fp8_fp8, (7,8,9))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_fp8_bf8, (7,8,9))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_bf8_fp8, (7,8,9))
|
||||
launchBenchmark(v_wmma_f32_16x16x16_bf8_bf8, (7,8,9))
|
||||
FLOPS_PER_MATMUL = 16*16*32*2
|
||||
launchBenchmark("v_wmma_i32_16X16X32_iu4", (7,8,9))
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_f16", (7,8,11,12,19,20), False)
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_bf16", (7,8,11,12,19,20), False)
|
||||
launchBenchmark("v_swmmac_f16_16x16x32_f16", (3,4,7,8,15,16), False)
|
||||
launchBenchmark("v_swmmac_bf16_16x16x32_bf16", (3,4,7,8,15,16), False)
|
||||
launchBenchmark("v_swmmac_i32_16x16x32_iu8", (7,8,9,10,13,14), False)
|
||||
launchBenchmark("v_swmmac_i32_16x16x32_iu4", (7,8,8,9,10,11), False)
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_fp8_fp8", (7,8,9,10,13,14), False)
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_fp8_bf8", (7,8,9,10,13,14), False)
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_bf8_fp8", (7,8,9,10,13,14), False)
|
||||
launchBenchmark("v_swmmac_f32_16x16x32_bf8_bf8", (7,8,9,10,13,14), False)
|
||||
launchBenchmark(v_wmma_i32_16x16x32_iu4, (7,8,9))
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_f16, (7,8,11,12,19,20), False)
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_bf16, (7,8,11,12,19,20), False)
|
||||
launchBenchmark(v_swmmac_f16_16x16x32_f16, (3,4,7,8,15,16), False)
|
||||
launchBenchmark(v_swmmac_bf16_16x16x32_bf16, (3,4,7,8,15,16), False)
|
||||
launchBenchmark(v_swmmac_i32_16x16x32_iu8, (7,8,9,10,13,14), False)
|
||||
launchBenchmark(v_swmmac_i32_16x16x32_iu4, (7,8,8,9,10,11), False)
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_fp8_fp8, (7,8,9,10,13,14), False)
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_fp8_bf8, (7,8,9,10,13,14), False)
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_bf8_fp8, (7,8,9,10,13,14), False)
|
||||
launchBenchmark(v_swmmac_f32_16x16x32_bf8_bf8, (7,8,9,10,13,14), False)
|
||||
FLOPS_PER_MATMUL = 16*16*64*2
|
||||
launchBenchmark("v_swmmac_i32_16x16x64_iu4", (7,8,9,10,13,14), False)
|
||||
elif DEV.arch == 'gfx950':
|
||||
DIRECTIVE = ".amdhsa_accum_offset 4"
|
||||
launchBenchmark(v_swmmac_i32_16x16x64_iu4, (7,8,9,10,13,14), False)
|
||||
elif arch == 'gfx950':
|
||||
from tinygrad.runtime.autogen.amd.cdna.ins import *
|
||||
NUM_WORKGROUPS = 256
|
||||
WAVE_SIZE = 64
|
||||
NUM_WAVES = 4
|
||||
launchBenchmark("v_mfma_f32_16x16x16_f16", (3,0,1), accum=True)
|
||||
launchBenchmark("v_mfma_f32_16x16x16_bf16", (3,0,1), accum=True)
|
||||
launchBenchmark(v_mfma_f32_16x16x16_f16, (3,0,1), accum=True)
|
||||
launchBenchmark(v_mfma_f32_16x16x16_bf16, (3,0,1), accum=True)
|
||||
FLOPS_PER_MATMUL = 16*16*32*2
|
||||
launchBenchmark("v_mfma_f32_16x16x32_f16", (3,0,3), accum=True)
|
||||
launchBenchmark("v_mfma_f32_16x16x32_bf16", (3,0,3), accum=True)
|
||||
launchBenchmark(v_mfma_f32_16x16x32_f16, (3,0,3), accum=True)
|
||||
launchBenchmark(v_mfma_f32_16x16x32_bf16, (3,0,3), accum=True)
|
||||
FLOPS_PER_MATMUL = 16*16*128*2
|
||||
launchBenchmark("v_mfma_f32_16x16x128_f8f6f4", (3,0,7), accum=True) # fp8
|
||||
launchBenchmark("v_mfma_f32_16x16x128_f8f6f4", (3,0,5), accum=True, extra=", cbsz:2 blgp:2") # fp6
|
||||
launchBenchmark("v_mfma_f32_16x16x128_f8f6f4", (3,0,3), accum=True, extra=", cbsz:4 blgp:4") # fp4
|
||||
launchBenchmark(v_mfma_f32_16x16x128_f8f6f4, (3,0,7), accum=True) # fp8
|
||||
launchBenchmark(v_mfma_f32_16x16x128_f8f6f4, (3,0,5), accum=True, cbsz=2, blgp=2) # fp6
|
||||
launchBenchmark(v_mfma_f32_16x16x128_f8f6f4, (3,0,3), accum=True, cbsz=4, blgp=4) # fp4
|
||||
else:
|
||||
raise RuntimeError(f"arch {DEV.arch} not supported.")
|
||||
raise RuntimeError(f"arch {arch} not supported.")
|
||||
|
||||
@@ -1,40 +0,0 @@
|
||||
.text
|
||||
.globl matmul
|
||||
.p2align 8
|
||||
.type matmul,@function
|
||||
matmul:
|
||||
s_mov_b32 s1, INTERNAL_LOOP
|
||||
s_mov_b32 s2, 0
|
||||
inner_loop:
|
||||
INSTRUCTION
|
||||
s_sub_u32 s1, s1, 1
|
||||
s_cmp_lg_i32 s1, s2
|
||||
s_cbranch_scc1 inner_loop
|
||||
s_endpgm
|
||||
|
||||
.rodata
|
||||
.p2align 6
|
||||
.amdhsa_kernel matmul
|
||||
.amdhsa_next_free_vgpr .amdgcn.next_free_vgpr
|
||||
.amdhsa_next_free_sgpr .amdgcn.next_free_sgpr
|
||||
DIRECTIVE
|
||||
.end_amdhsa_kernel
|
||||
|
||||
.amdgpu_metadata
|
||||
---
|
||||
amdhsa.version:
|
||||
- 1
|
||||
- 0
|
||||
amdhsa.kernels:
|
||||
- .name: matmul
|
||||
.symbol: matmul.kd
|
||||
.kernarg_segment_size: 0
|
||||
.group_segment_fixed_size: 0
|
||||
.private_segment_fixed_size: 0
|
||||
.kernarg_segment_align: 4
|
||||
.wavefront_size: 32
|
||||
.sgpr_count: 8
|
||||
.vgpr_count: 32
|
||||
.max_flat_workgroup_size: 1024
|
||||
...
|
||||
.end_amdgpu_metadata
|
||||
@@ -5,7 +5,6 @@ from tinygrad.nn import Linear, LayerNorm, Embedding, Conv2d
|
||||
from typing import List, Optional, Union, Tuple, Dict
|
||||
from abc import ABC, abstractmethod
|
||||
from functools import lru_cache
|
||||
from PIL import Image
|
||||
import numpy as np
|
||||
import re, gzip
|
||||
|
||||
@@ -444,7 +443,8 @@ class OpenClipEncoder:
|
||||
# TODO:
|
||||
# Should be doable in pure tinygrad, would just require some work and verification.
|
||||
# This is very desirable since it would allow for full generation->evaluation in a single JIT call.
|
||||
def prepare_image(self, image:Image.Image) -> Tensor:
|
||||
def prepare_image(self, image) -> Tensor:
|
||||
from PIL import Image
|
||||
SIZE = 224
|
||||
w, h = image.size
|
||||
scale = min(SIZE / h, SIZE / w)
|
||||
|
||||
+17
-9
@@ -55,12 +55,15 @@ class Attention:
|
||||
xqkv = x @ self.wqkv.T
|
||||
xq, xk, xv = xqkv.split([self.wq.weight.shape[0], self.wk.weight.shape[0], self.wv.weight.shape[0]], dim=2)
|
||||
else:
|
||||
xq, xk, xv = self.wq(x), self.wk(x), self.wv(x)
|
||||
xq, xk, xv = self.wq(x), self.wk(x.contiguous_backward()), self.wv(x)
|
||||
|
||||
if self.q_norm is not None and self.k_norm is not None:
|
||||
xq = self.q_norm(xq)
|
||||
xk = self.k_norm(xk)
|
||||
|
||||
# cast_float_to_bf16 is expensive in reduction loops, break it out
|
||||
if x.dtype == dtypes.bfloat16: xq, xk = xq.contiguous_backward(), xk.contiguous_backward()
|
||||
|
||||
xq = xq.reshape(xq.shape[0], xq.shape[1], self.n_heads, self.head_dim)
|
||||
xk = xk.reshape(xk.shape[0], xk.shape[1], self.n_kv_heads, self.head_dim)
|
||||
xv = xv.reshape(xv.shape[0], xv.shape[1], self.n_kv_heads, self.head_dim)
|
||||
@@ -86,20 +89,23 @@ class Attention:
|
||||
assert start_pos == 0
|
||||
keys, values = xk, xv
|
||||
|
||||
keys, values = repeat_kv(keys, self.n_rep), repeat_kv(values, self.n_rep)
|
||||
xq, keys, values = xq.transpose(1, 2), keys.transpose(1, 2), values.transpose(1, 2)
|
||||
attn = xq.scaled_dot_product_attention(keys, values, mask).transpose(1, 2)
|
||||
if self.max_context:
|
||||
keys, values = repeat_kv(keys, self.n_rep), repeat_kv(values, self.n_rep)
|
||||
xq, keys, values = xq.transpose(1, 2), keys.transpose(1, 2), values.transpose(1, 2)
|
||||
attn = xq.scaled_dot_product_attention(keys, values, mask).transpose(1, 2)
|
||||
else:
|
||||
xq, keys, values = xq.transpose(1, 2), keys.transpose(1, 2), values.transpose(1, 2)
|
||||
attn = xq.scaled_dot_product_attention(keys, values, is_causal=True, enable_gqa=True).transpose(1, 2)
|
||||
if getenv("STUB_ATTENTION"):
|
||||
# TODO: do we need mask?
|
||||
from tinygrad.uop.ops import UOp, KernelInfo
|
||||
def fa_custom_forward(attn:UOp, q:UOp, k:UOp, v:UOp) -> UOp:
|
||||
return UOp.sink(arg=KernelInfo(name="fa_custom_forward"))
|
||||
def fa_custom_backward(out_q:UOp, out_k:UOp, out_v:UOp, grad:UOp, q:UOp, k:UOp, v:UOp) -> UOp:
|
||||
return UOp.sink(arg=KernelInfo(name="fa_custom_backward"))
|
||||
def fa_backward(grad:UOp, kernel:UOp) -> tuple[None, UOp, UOp, UOp]:
|
||||
grad_q = Tensor.empty_like(q:=Tensor(kernel.src[1]))
|
||||
grad_k = Tensor.empty_like(k:=Tensor(kernel.src[2]))
|
||||
grad_v = Tensor.empty_like(v:=Tensor(kernel.src[3]))
|
||||
grad_q = Tensor.empty_like(q:=Tensor(kernel.src[2]))
|
||||
grad_k = Tensor.empty_like(k:=Tensor(kernel.src[3]))
|
||||
grad_v = Tensor.empty_like(v:=Tensor(kernel.src[4]))
|
||||
ck = Tensor.custom_kernel(grad_q, grad_k, grad_v, Tensor(grad), q, k, v, fxn=fa_custom_backward)[:3]
|
||||
return (None, ck[0].uop, ck[1].uop, ck[2].uop)
|
||||
attn = Tensor.empty_like(attn).custom_kernel(xq, keys, values, fxn=fa_custom_forward, grad_fxn=fa_backward)[0]
|
||||
@@ -197,7 +203,9 @@ class Transformer:
|
||||
h = self.tok_embeddings(tokens)
|
||||
freqs_cis = self.freqs_cis.cast(h.dtype)[:, start_pos:start_pos+seqlen, :, :, :]
|
||||
|
||||
mask = Tensor.full((1, 1, seqlen, start_pos+seqlen), float("-inf"), dtype=h.dtype, device=h.device).triu(start_pos+1) if seqlen > 1 else None
|
||||
if self.max_context != 0 and seqlen > 1:
|
||||
mask = Tensor.full((1, 1, seqlen, start_pos+seqlen), float("-inf"), dtype=h.dtype, device=h.device).triu(start_pos+1)
|
||||
else: mask = None
|
||||
for layer in self.layers: h = layer(h, start_pos, freqs_cis, mask)
|
||||
logits = self.output(self.norm(h))
|
||||
if math.isnan(temperature): return logits
|
||||
|
||||
@@ -150,7 +150,7 @@ class ResNet:
|
||||
continue # Skip FC if transfer learning
|
||||
|
||||
if 'bn' not in k and 'downsample' not in k: assert obj.shape == dat.shape, (k, obj.shape, dat.shape)
|
||||
obj.assign(dat.to(obj.device).reshape(obj.shape))
|
||||
obj.assign(dat.to(obj.device).cast(obj.dtype).reshape(obj.shape))
|
||||
|
||||
ResNet18 = lambda num_classes=1000: ResNet(18, num_classes=num_classes)
|
||||
ResNet34 = lambda num_classes=1000: ResNet(34, num_classes=num_classes)
|
||||
|
||||
+112
-24
@@ -1,6 +1,7 @@
|
||||
# type: ignore
|
||||
import ctypes, ctypes.util, struct, platform, pathlib, re, time, os, signal
|
||||
from tinygrad.helpers import from_mv, to_mv, getenv, init_c_struct_t
|
||||
from tinygrad.helpers import from_mv, to_mv, getenv
|
||||
from tinygrad.runtime.support.c import init_c_struct_t
|
||||
from hexdump import hexdump
|
||||
start = time.perf_counter()
|
||||
|
||||
@@ -10,18 +11,21 @@ processor = platform.processor()
|
||||
IOCTL_SYSCALL = {"aarch64": 0x1d, "x86_64":16}[processor]
|
||||
MMAP_SYSCALL = {"aarch64": 0xde, "x86_64":0x09}[processor]
|
||||
|
||||
IOCTL_PRINT = getenv("IOCTL_PRINT", getenv("IOCTL", 0))
|
||||
GRAB_PMA = getenv("GRAB_PMA", 0)
|
||||
|
||||
def get_struct(argp, stype):
|
||||
return ctypes.cast(ctypes.c_void_p(argp), ctypes.POINTER(stype)).contents
|
||||
|
||||
def dump_struct(st):
|
||||
if getenv("IOCTL", 0) == 0: return
|
||||
if IOCTL_PRINT == 0: return
|
||||
print("\t", st.__class__.__name__, end=" { ")
|
||||
for v in type(st)._fields_: print(f"{v[0]}={getattr(st, v[0])}", end=" ")
|
||||
for v in type(st)._real_fields_: print(f"{v[0]}={getattr(st, v[0])}", end=" ")
|
||||
print("}")
|
||||
|
||||
def format_struct(s):
|
||||
sdats = []
|
||||
for field in s._fields_:
|
||||
for field in s._real_fields_:
|
||||
dat = getattr(s, field[0])
|
||||
if isinstance(dat, int): sdats.append(f"{field[0]}:0x{dat:X}")
|
||||
else: sdats.append(f"{field[0]}:{dat}")
|
||||
@@ -58,6 +62,29 @@ def install_hook(c_function, python_function):
|
||||
return orig_func
|
||||
|
||||
# *** ioctl lib end ***
|
||||
|
||||
# PMA buffer tracking for raw PC sampling data (only when GRAB_PMA is enabled)
|
||||
pma_mem_handle = 0 # hMemPmaBuffer from ALLOC_PMA_STREAM
|
||||
pma_buffer_size = 0
|
||||
pma_buffer_va = 0 # actual mapped VA (found via /proc/self/maps)
|
||||
pma_get_offset = 0 # current read offset in ring buffer
|
||||
pma_pending_map = False # flag to check for new mapping on next ioctl
|
||||
pma_maps_before = set() # mappings before MAP_MEMORY
|
||||
pma_raw_dumps: list[bytes] = [] # raw PMA buffer dumps
|
||||
|
||||
def get_pma_raw_dumps() -> list[bytes]: return pma_raw_dumps
|
||||
def clear_pma_raw_dumps(): pma_raw_dumps.clear()
|
||||
|
||||
def get_proc_maps():
|
||||
"""Read current process memory mappings as set of (start, end) tuples."""
|
||||
result = set()
|
||||
with open("/proc/self/maps", "r") as f:
|
||||
for line in f:
|
||||
addr_range = line.split()[0]
|
||||
start, end = addr_range.split("-")
|
||||
result.add((int(start, 16), int(end, 16)))
|
||||
return result
|
||||
|
||||
from tinygrad.runtime.autogen import nv_570 as nv_gpu
|
||||
nvescs = {getattr(nv_gpu, x):x for x in dir(nv_gpu) if x.startswith("NV_ESC")}
|
||||
nvcmds = {getattr(nv_gpu, x):(x, getattr(nv_gpu, "struct_"+x+"_PARAMS", getattr(nv_gpu, "struct_"+x.replace("_CMD_", "_")+"_PARAMS", None))) for x in dir(nv_gpu) if \
|
||||
@@ -69,6 +96,7 @@ def get_classes():
|
||||
"NV20_SUBDEVICE_0"}
|
||||
for nm,val in nv_gpu.__dict__.items():
|
||||
if not isinstance(val, int): continue
|
||||
if nm.endswith("PARAMETERS_MESSAGE_ID"): continue
|
||||
if 0x3000 < val < 0xffff: res[val] = nm
|
||||
if nm in known_classes: res[val] = nm
|
||||
return res
|
||||
@@ -80,37 +108,92 @@ global_ioctl_id = 0
|
||||
gpus_user_modes = []
|
||||
gpus_mmio = []
|
||||
gpus_fifo = []
|
||||
offset_load = 0
|
||||
|
||||
@ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_int, ctypes.c_ulong, ctypes.c_void_p)
|
||||
def ioctl(fd, request, argp):
|
||||
global global_ioctl_id, gpus_user_modes, gpus_mmio
|
||||
global pma_mem_handle, pma_buffer_size, pma_buffer_va, pma_get_offset, pma_pending_map, pma_maps_before
|
||||
global_ioctl_id += 1
|
||||
|
||||
# Check for new PMA buffer mapping from previous MAP_MEMORY call (only when GRAB_PMA is enabled)
|
||||
if GRAB_PMA and pma_pending_map:
|
||||
pma_pending_map = False
|
||||
new_maps = get_proc_maps()
|
||||
for start, end in new_maps - pma_maps_before:
|
||||
if end - start == pma_buffer_size:
|
||||
pma_buffer_va = start
|
||||
if IOCTL_PRINT >= 1: print(f"\t PMA buffer mapped at CPU VA=0x{pma_buffer_va:x}")
|
||||
break
|
||||
|
||||
st = time.perf_counter()
|
||||
ret = libc.syscall(IOCTL_SYSCALL, ctypes.c_int(fd), ctypes.c_ulong(request), ctypes.c_void_p(argp))
|
||||
et = time.perf_counter()-st
|
||||
fn = os.readlink(f"/proc/self/fd/{fd}")
|
||||
#print(f"ioctl {request:8x} {fn:20s}")
|
||||
|
||||
idir, size, itype, nr = (request>>30), (request>>16)&0x3FFF, (request>>8)&0xFF, request&0xFF
|
||||
if getenv("IOCTL", 0) >= 1: print(f"#{global_ioctl_id}: ", end="")
|
||||
if IOCTL_PRINT >= 1: print(f"#{global_ioctl_id}: ", end="")
|
||||
if itype == ord(nv_gpu.NV_IOCTL_MAGIC):
|
||||
if nr == nv_gpu.NV_ESC_RM_CONTROL:
|
||||
s = get_struct(argp, nv_gpu.NVOS54_PARAMETERS)
|
||||
if s.cmd in nvcmds:
|
||||
name, struc = nvcmds[s.cmd]
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
print(f"NV_ESC_RM_CONTROL cmd={name:30s} hClient={s.hClient}, hObject={s.hObject}, flags={s.flags}, params={s.params}, paramsSize={s.paramsSize}, status={s.status}")
|
||||
|
||||
if struc is not None: dump_struct(get_struct(s.params, struc))
|
||||
elif hasattr(nv_gpu, name+"_PARAMS"): dump_struct(get_struct(argp, getattr(nv_gpu, name+"_PARAMS")))
|
||||
elif name == "NVA06C_CTRL_CMD_GPFIFO_SCHEDULE": dump_struct(get_struct(argp, nv_gpu.NVA06C_CTRL_GPFIFO_SCHEDULE_PARAMS))
|
||||
elif name == "NV83DE_CTRL_CMD_GET_MAPPINGS": dump_struct(get_struct(s.params, nv_gpu.NV83DE_CTRL_DEBUG_GET_MAPPINGS_PARAMETERS))
|
||||
elif name == "NVB0CC_CTRL_CMD_SET_HS_CREDITS":
|
||||
hs_params = get_struct(s.params, nv_gpu.NVB0CC_CTRL_SET_HS_CREDITS_PARAMS)
|
||||
dump_struct(hs_params)
|
||||
if IOCTL_PRINT >= 2:
|
||||
for i in range(hs_params.numEntries):
|
||||
print(f"\t\t", end="")
|
||||
dump_struct(hs_params.creditInfo[i])
|
||||
|
||||
# PMA buffer tracking (only when GRAB_PMA is enabled)
|
||||
if GRAB_PMA and name == "NVB0CC_CTRL_CMD_ALLOC_PMA_STREAM":
|
||||
pma_params = get_struct(s.params, nv_gpu.struct_NVB0CC_CTRL_ALLOC_PMA_STREAM_PARAMS)
|
||||
pma_mem_handle = pma_params.hMemPmaBuffer
|
||||
pma_buffer_size = pma_params.pmaBufferSize
|
||||
pma_get_offset = 0 # Reset read offset for new stream
|
||||
if IOCTL_PRINT >= 1: print(f"\t PMA buffer: hMem=0x{pma_mem_handle:x} size={pma_buffer_size}")
|
||||
if GRAB_PMA and name == "NVB0CC_CTRL_CMD_PMA_STREAM_UPDATE_GET_PUT":
|
||||
pma_update = get_struct(s.params, nv_gpu.struct_NVB0CC_CTRL_PMA_STREAM_UPDATE_GET_PUT_PARAMS)
|
||||
if pma_update.bytesAvailable > 0 and pma_buffer_va and pma_buffer_size > 0:
|
||||
avail = pma_update.bytesAvailable
|
||||
read_offset = pma_get_offset
|
||||
# Handle ring buffer wrap-around
|
||||
if pma_get_offset + avail <= pma_buffer_size:
|
||||
pma_data = bytes(to_mv(pma_buffer_va + pma_get_offset, avail))
|
||||
else:
|
||||
# Wrap around: read to end, then from start
|
||||
first_part = pma_buffer_size - pma_get_offset
|
||||
second_part = avail - first_part
|
||||
pma_data = bytes(to_mv(pma_buffer_va + pma_get_offset, first_part)) + bytes(to_mv(pma_buffer_va, second_part))
|
||||
pma_raw_dumps.append(pma_data)
|
||||
pma_get_offset = (pma_get_offset + avail) % pma_buffer_size
|
||||
if IOCTL_PRINT >= 2:
|
||||
print(f"\t PMA data: {avail} bytes from offset=0x{read_offset:x}, new offset=0x{pma_get_offset:x}")
|
||||
hexdump(pma_data)
|
||||
|
||||
# Dump regOps for EXEC_REG_OPS when IOCTL >= 3
|
||||
if name == "NVB0CC_CTRL_CMD_EXEC_REG_OPS" and struc is not None and IOCTL_PRINT >= 3:
|
||||
reg_params = get_struct(s.params, struc)
|
||||
for i in range(reg_params.regOpCount):
|
||||
print(f"\t\t", end="")
|
||||
dump_struct(reg_params.regOps[i])
|
||||
# val = (op.regValueHi << 32) | op.regValueLo
|
||||
# print(f"\t regOps[{i:3d}]: op={op.regOp} type={op.regType} status={op.regStatus} offset=0x{op.regOffset:08x} value=0x{val:016x}")
|
||||
else:
|
||||
if getenv("IOCTL", 0) >= 1: print("unhandled cmd", hex(s.cmd))
|
||||
if IOCTL_PRINT >= 1: print("unhandled cmd", hex(s.cmd))
|
||||
# format_struct(s)
|
||||
# print(f"{(st-start)*1000:7.2f} ms +{et*1000.:7.2f} ms : {ret:2d} = {name:40s}", ' '.join(format_struct(s)))
|
||||
elif nr == nv_gpu.NV_ESC_RM_ALLOC:
|
||||
s = get_struct(argp, nv_gpu.NVOS21_PARAMETERS)
|
||||
if getenv("IOCTL", 0) >= 1: print(f"NV_ESC_RM_ALLOC hClass={nvclasses.get(s.hClass, f'unk=0x{s.hClass:X}'):30s}, hRoot={s.hRoot}, hObjectParent={s.hObjectParent}, pAllocParms={s.pAllocParms}, hObjectNew={s.hObjectNew} status={s.status}")
|
||||
if IOCTL_PRINT >= 1: print(f"NV_ESC_RM_ALLOC hClass={nvclasses.get(s.hClass, f'unk=0x{s.hClass:X}'):30s}, hRoot={s.hRoot}, hObjectParent={s.hObjectParent}, pAllocParms={s.pAllocParms}, hObjectNew={s.hObjectNew} status={s.status}")
|
||||
if s.pAllocParms is not None:
|
||||
if s.hClass == nv_gpu.NV01_DEVICE_0: dump_struct(get_struct(s.pAllocParms, nv_gpu.NV0080_ALLOC_PARAMETERS))
|
||||
if s.hClass == nv_gpu.FERMI_VASPACE_A: dump_struct(get_struct(s.pAllocParms, nv_gpu.NV_VASPACE_ALLOCATION_PARAMETERS))
|
||||
@@ -118,7 +201,8 @@ def ioctl(fd, request, argp):
|
||||
if s.hClass == nv_gpu.NV1_MEMORY_USER: dump_struct(get_struct(s.pAllocParms, nv_gpu.NV_MEMORY_ALLOCATION_PARAMS))
|
||||
if s.hClass == nv_gpu.NV1_MEMORY_SYSTEM: dump_struct(get_struct(s.pAllocParms, nv_gpu.NV_MEMORY_ALLOCATION_PARAMS))
|
||||
if s.hClass == nv_gpu.GT200_DEBUGGER: dump_struct(get_struct(s.pAllocParms, nv_gpu.NV83DE_ALLOC_PARAMETERS))
|
||||
if s.hClass == nv_gpu.AMPERE_CHANNEL_GPFIFO_A:
|
||||
if s.hClass == nv_gpu.MAXWELL_PROFILER_DEVICE: dump_struct(get_struct(s.pAllocParms, nv_gpu.NVB2CC_ALLOC_PARAMETERS))
|
||||
if s.hClass in {nv_gpu.AMPERE_CHANNEL_GPFIFO_A, nv_gpu.BLACKWELL_CHANNEL_GPFIFO_A}:
|
||||
sx = get_struct(s.pAllocParms, nv_gpu.NV_CHANNELGPFIFO_ALLOCATION_PARAMETERS)
|
||||
dump_struct(sx)
|
||||
gpus_fifo.append((sx.gpFifoOffset, sx.gpFifoEntries))
|
||||
@@ -126,31 +210,35 @@ def ioctl(fd, request, argp):
|
||||
if s.hClass == nv_gpu.TURING_USERMODE_A: gpus_user_modes.append(s.hObjectNew)
|
||||
elif nr == nv_gpu.NV_ESC_RM_MAP_MEMORY:
|
||||
# nv_ioctl_nvos33_parameters_with_fd
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
s = get_struct(argp, nv_gpu.NVOS33_PARAMETERS)
|
||||
s = get_struct(argp, nv_gpu.NVOS33_PARAMETERS)
|
||||
if IOCTL_PRINT >= 1:
|
||||
print(f"NV_ESC_RM_MAP_MEMORY hClient={s.hClient}, hDevice={s.hDevice}, hMemory={s.hMemory}, length={s.length} flags={s.flags} pLinearAddress={s.pLinearAddress}")
|
||||
# Track PMA buffer mapping - save maps now, check for new mapping on next ioctl (after mmap happens)
|
||||
if GRAB_PMA and pma_mem_handle and s.hMemory == pma_mem_handle:
|
||||
pma_maps_before = get_proc_maps()
|
||||
pma_pending_map = True
|
||||
elif nr == nv_gpu.NV_ESC_RM_UPDATE_DEVICE_MAPPING_INFO:
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
s = get_struct(argp, nv_gpu.NVOS56_PARAMETERS)
|
||||
print(f"NV_ESC_RM_UPDATE_DEVICE_MAPPING_INFO hClient={s.hClient}, hDevice={s.hDevice}, hMemory={s.hMemory}, pOldCpuAddress={s.pOldCpuAddress} pNewCpuAddress={s.pNewCpuAddress} status={s.status}")
|
||||
elif nr == nv_gpu.NV_ESC_RM_ALLOC_MEMORY:
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
s = get_struct(argp, nv_gpu.nv_ioctl_nvos02_parameters_with_fd)
|
||||
print(f"NV_ESC_RM_ALLOC_MEMORY fd={s.fd}, hRoot={s.params.hRoot}, hObjectParent={s.params.hObjectParent}, hObjectNew={s.params.hObjectNew}, hClass={s.params.hClass}, flags={s.params.flags}, pMemory={s.params.pMemory}, limit={s.params.limit}, status={s.params.status}")
|
||||
elif nr == nv_gpu.NV_ESC_ALLOC_OS_EVENT:
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
s = get_struct(argp, nv_gpu.nv_ioctl_alloc_os_event_t)
|
||||
print(f"NV_ESC_ALLOC_OS_EVENT hClient={s.hClient} hDevice={s.hDevice} fd={s.fd} Status={s.Status}")
|
||||
elif nr == nv_gpu.NV_ESC_REGISTER_FD:
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
s = get_struct(argp, nv_gpu.nv_ioctl_register_fd_t)
|
||||
print(f"NV_ESC_REGISTER_FD fd={s.ctl_fd}")
|
||||
elif nr in nvescs:
|
||||
if getenv("IOCTL", 0) >= 1: print(nvescs[nr])
|
||||
if IOCTL_PRINT >= 1: print(nvescs[nr])
|
||||
else:
|
||||
if getenv("IOCTL", 0) >= 1: print("unhandled NR", nr)
|
||||
if IOCTL_PRINT >= 1: print("unhandled NR", nr)
|
||||
elif fn.endswith("nvidia-uvm"):
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
print(f"{nvuvms.get(request, f'UVM UNKNOWN {request=}')}")
|
||||
if nvuvms.get(request) is not None: dump_struct(get_struct(argp, getattr(nv_gpu, nvuvms.get(request)+"_PARAMS")))
|
||||
if nvuvms.get(request) == "UVM_MAP_EXTERNAL_ALLOCATION":
|
||||
@@ -159,7 +247,7 @@ def ioctl(fd, request, argp):
|
||||
print("perGpuAttributes[{i}] = ", end="")
|
||||
dump_struct(st.perGpuAttributes[i])
|
||||
|
||||
if getenv("IOCTL") >= 2: print("ioctl", f"{idir=} {size=} {itype=} {nr=} {fd=} {ret=}", fn)
|
||||
if IOCTL_PRINT >= 2: print("ioctl", f"{idir=} {size=} {itype=} {nr=} {fd=} {ret=}", fn)
|
||||
return ret
|
||||
|
||||
@ctypes.CFUNCTYPE(ctypes.c_void_p, ctypes.c_void_p, ctypes.c_size_t, ctypes.c_int, ctypes.c_int, ctypes.c_int, ctypes.c_long)
|
||||
@@ -172,14 +260,14 @@ def _mmap(addr, length, prot, flags, fd, offset):
|
||||
return ret
|
||||
|
||||
install_hook(libc.ioctl, ioctl)
|
||||
if getenv("IOCTL") >= 3: orig_mmap_mv = install_hook(libc.mmap, _mmap)
|
||||
if getenv("IOCTL") >= 4: orig_mmap_mv = install_hook(libc.mmap, _mmap)
|
||||
|
||||
import collections
|
||||
old_gpputs = collections.defaultdict(int)
|
||||
def _dump_gpfifo(mark):
|
||||
launches = []
|
||||
|
||||
# print("_dump_gpfifo:", mark)
|
||||
print("_dump_gpfifo:", mark)
|
||||
for start, size in gpus_fifo:
|
||||
gpfifo_controls = nv_gpu.AmpereAControlGPFifo.from_address(start+size*8)
|
||||
gpfifo = to_mv(start, size * 8).cast("Q")
|
||||
@@ -205,7 +293,7 @@ def make_qmd_struct_type():
|
||||
fields.append((name.replace("NVC6C0_QMDV03_00_", "").lower(), ctypes.c_uint32, data[0]-data[1]+1))
|
||||
if len(fields) >= 2 and fields[-2][0].endswith('_lower') and fields[-1][0].endswith('_upper') and fields[-1][0][:-6] == fields[-2][0][:-6]:
|
||||
fields = fields[:-2] + [(fields[-1][0][:-6], ctypes.c_uint64, fields[-1][2] + fields[-2][2])]
|
||||
return init_c_struct_t(tuple(fields))
|
||||
return init_c_struct_t(0x40 * 4, tuple(fields))
|
||||
qmd_struct_t = make_qmd_struct_type()
|
||||
assert ctypes.sizeof(qmd_struct_t) == 0x40 * 4
|
||||
|
||||
@@ -222,7 +310,7 @@ def _dump_qmd(address, packets):
|
||||
subc = (dat>>13) & 7
|
||||
mthd = (dat<<2) & 0x7FFF
|
||||
method_name = nvqcmds.get(mthd, f"unknown method #{mthd}")
|
||||
if getenv("IOCTL", 0) >= 1:
|
||||
if IOCTL_PRINT >= 1:
|
||||
print(f"\t\t{method_name}, {typ=} {size=} {subc=} {mthd=}")
|
||||
for j in range(size): print(f"\t\t\t{j}: {gpfifo[i+j+1]} | 0x{gpfifo[i+j+1]:x}")
|
||||
if mthd == 792:
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
examples/
|
||||
@@ -0,0 +1,135 @@
|
||||
import pickle, os, sys, functools, numpy as np
|
||||
from pathlib import Path
|
||||
|
||||
os.environ["DEV"] = "CUDA"
|
||||
os.environ["PROFILE"] = os.environ.get("PROFILE", "2")
|
||||
from extra.nv_pma.cupti import cu_prof_ext
|
||||
cu_prof_ext.enable_auto()
|
||||
|
||||
from tinygrad import Tensor, Device
|
||||
|
||||
if not os.environ.get("IOCTL") or not os.environ.get("GRAB_PMA"):
|
||||
print("Usage: GRAB_PMA=1 IOCTL=1 IOCTL_PRINT=0 python3 extra/nv_pma/collect.py")
|
||||
sys.exit(1)
|
||||
|
||||
assert Device.DEFAULT == "CUDA", "only works with CUDA"
|
||||
|
||||
EXAMPLES_DIR = Path(__file__).parent / "examples"
|
||||
_collectors: list[tuple[str, callable]] = []
|
||||
|
||||
def pcsampling_test(name: str):
|
||||
def decorator(fn):
|
||||
@functools.wraps(fn)
|
||||
def wrapper():
|
||||
cu_prof_ext.clear_pma_raw_dumps()
|
||||
cu_prof_ext.clear_cupti_pc_samples()
|
||||
|
||||
fn()
|
||||
Device["CUDA"].synchronize()
|
||||
|
||||
dumps = cu_prof_ext.get_pma_raw_dumps()
|
||||
# from hexdump import hexdump
|
||||
# hexdump(dumps[0][:0x40])
|
||||
|
||||
return {"test_name": name, "pma_raw_dumps": list(cu_prof_ext.get_pma_raw_dumps()), "cupti_pc_samples": list(cu_prof_ext.get_cupti_pc_samples())}
|
||||
_collectors.append((name, wrapper))
|
||||
return wrapper
|
||||
return decorator
|
||||
|
||||
# Refs
|
||||
|
||||
@pcsampling_test("test_plus")
|
||||
def test_plus():
|
||||
a = Tensor([1, 2, 3, 4])
|
||||
b = Tensor([5, 6, 7, 8])
|
||||
(a + b).realize()
|
||||
|
||||
@pcsampling_test("test_matmul")
|
||||
def test_matmul():
|
||||
a = Tensor(np.random.rand(12, 12).astype(np.float32))
|
||||
b = Tensor(np.random.rand(12, 12).astype(np.float32))
|
||||
(a @ b).realize()
|
||||
|
||||
@pcsampling_test("test_reduce_sum")
|
||||
def test_reduce_sum():
|
||||
a = Tensor(np.random.rand(1024).astype(np.float32))
|
||||
a.sum().realize()
|
||||
|
||||
@pcsampling_test("test_reduce_max")
|
||||
def test_reduce_max():
|
||||
a = Tensor(np.random.rand(1024).astype(np.float32))
|
||||
a.max().realize()
|
||||
|
||||
@pcsampling_test("test_exp")
|
||||
def test_exp():
|
||||
a = Tensor(np.random.rand(256).astype(np.float32))
|
||||
a.exp().realize()
|
||||
|
||||
@pcsampling_test("test_softmax")
|
||||
def test_softmax():
|
||||
a = Tensor(np.random.rand(64, 64).astype(np.float32))
|
||||
a.softmax().realize()
|
||||
|
||||
@pcsampling_test("test_conv2d")
|
||||
def test_conv2d():
|
||||
x = Tensor(np.random.rand(1, 3, 32, 32).astype(np.float32))
|
||||
w = Tensor(np.random.rand(8, 3, 3, 3).astype(np.float32))
|
||||
x.conv2d(w).realize()
|
||||
|
||||
@pcsampling_test("test_large_matmul")
|
||||
def test_large_matmul():
|
||||
a = Tensor(np.random.rand(128, 128).astype(np.float32))
|
||||
b = Tensor(np.random.rand(128, 128).astype(np.float32))
|
||||
(a @ b).realize()
|
||||
|
||||
@pcsampling_test("test_elementwise_chain")
|
||||
def test_elementwise_chain():
|
||||
a = Tensor(np.random.rand(512).astype(np.float32))
|
||||
((a + 1) * 2 - 0.5).relu().realize()
|
||||
|
||||
@pcsampling_test("test_broadcast")
|
||||
def test_broadcast():
|
||||
a = Tensor(np.random.rand(64, 1).astype(np.float32))
|
||||
b = Tensor(np.random.rand(1, 64).astype(np.float32))
|
||||
(a + b).realize()
|
||||
|
||||
@pcsampling_test("test_plus_big")
|
||||
def test_plus_big():
|
||||
a = Tensor(np.random.rand(64, 32).astype(np.float32))
|
||||
b = Tensor(np.random.rand(64, 32).astype(np.float32))
|
||||
(a + b).realize()
|
||||
|
||||
def save_example(name: str, data: dict):
|
||||
pma_bytes = sum(len(d) for d in data['pma_raw_dumps'])
|
||||
cupti_samples = sum(r['samples'] for r in data['cupti_pc_samples'])
|
||||
print(f" PMA: {len(data['pma_raw_dumps'])} buffers, {pma_bytes} bytes")
|
||||
print(f" CUPTI: {len(data['cupti_pc_samples'])} records, {cupti_samples} samples")
|
||||
|
||||
outfile = EXAMPLES_DIR / f"{name}.pkl"
|
||||
with open(outfile, "wb") as f:
|
||||
pickle.dump(data, f)
|
||||
print(f" Saved to {outfile}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
EXAMPLES_DIR.mkdir(exist_ok=True)
|
||||
|
||||
# Run specific tests if provided as arguments, otherwise run all
|
||||
if len(sys.argv) > 1:
|
||||
test_names = sys.argv[1:]
|
||||
collectors = [(name, fn) for name, fn in _collectors if name in test_names]
|
||||
if not collectors:
|
||||
print(f"Unknown tests: {test_names}")
|
||||
print(f"Available: {[name for name, _ in _collectors]}")
|
||||
sys.exit(1)
|
||||
else:
|
||||
collectors = _collectors
|
||||
|
||||
for name, collect_fn in collectors:
|
||||
print(f"\nCollecting {name}...")
|
||||
try:
|
||||
data = collect_fn()
|
||||
save_example(name, data)
|
||||
except Exception as e:
|
||||
print(f" ERROR: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
@@ -0,0 +1,26 @@
|
||||
# CUPTI autogen loader for nv_pma
|
||||
# To regenerate: REGEN=1 python -c "import extra.nv_pma.cupti"
|
||||
import importlib, pathlib
|
||||
from tinygrad.helpers import getenv
|
||||
|
||||
root = pathlib.Path(__file__).parents[3]
|
||||
here = pathlib.Path(__file__).parent
|
||||
|
||||
def load(name, dll, files, **kwargs):
|
||||
if not (f:=here/f"{name}.py").exists() or getenv('REGEN'):
|
||||
kwargs['args'] = kwargs.get('args', [])
|
||||
f.write_text(importlib.import_module("tinygrad.runtime.support.autogen").gen(name, dll, files, **kwargs))
|
||||
return importlib.import_module(f"extra.nv_pma.cupti.{name}")
|
||||
|
||||
def __getattr__(nm):
|
||||
match nm:
|
||||
case "cupti":
|
||||
return load("cupti", "'/usr/local/cuda/targets/x86_64-linux/lib/libcupti.so'", [
|
||||
"/usr/local/cuda/include/cupti_result.h", "/usr/local/cuda/include/cupti_activity.h",
|
||||
"/usr/local/cuda/include/cupti_callbacks.h", "/usr/local/cuda/include/cupti_events.h",
|
||||
"/usr/local/cuda/include/cupti_metrics.h", "/usr/local/cuda/include/cupti_driver_cbid.h",
|
||||
"/usr/local/cuda/include/cupti_runtime_cbid.h", "/usr/local/cuda/include/cupti_profiler_target.h",
|
||||
"/usr/local/cuda/include/cupti_profiler_host.h", "/usr/local/cuda/include/cupti_pmsampling.h",
|
||||
"/usr/local/cuda/include/generated_cuda_meta.h", "/usr/local/cuda/include/generated_cuda_runtime_api_meta.h"
|
||||
], args=["-D__CUDA_API_VERSION_INTERNAL", "-I/usr/local/cuda/include"], parse_macros=False)
|
||||
case _: raise AttributeError(f"no such autogen: {nm}")
|
||||
@@ -0,0 +1,164 @@
|
||||
from __future__ import annotations
|
||||
import ctypes
|
||||
from tinygrad.helpers import DEBUG, getenv
|
||||
from extra.nv_pma.cupti import cupti
|
||||
|
||||
def stall_reason_name(reason: int) -> str:
|
||||
name = cupti.CUpti_ActivityPCSamplingStallReason.get(reason)
|
||||
return name.replace("CUPTI_ACTIVITY_PC_SAMPLING_STALL_", "").lower() if name else str(reason)
|
||||
|
||||
class CUPTIProfiler:
|
||||
def __init__(self):
|
||||
self.initialized = False
|
||||
self.pc_sampling_enabled = False
|
||||
self.buffers: list[ctypes.Array] = []
|
||||
self.kernel_stalls: dict[int, dict[int, int]] = {}
|
||||
self.raw_buffers: list[bytes] = []
|
||||
self.pc_samples: list[dict] = []
|
||||
|
||||
def _check_cupti(self, status, soft=False):
|
||||
if status != cupti.CUPTI_SUCCESS:
|
||||
if soft: return False
|
||||
raise RuntimeError(f"CUPTI Error {status}")
|
||||
return True
|
||||
|
||||
def init(self, ctx, device_id: int = 0, profile_level: int = 2):
|
||||
if self.initialized: return
|
||||
|
||||
# Initialize profiler API
|
||||
init_params = cupti.CUpti_Profiler_Initialize_Params()
|
||||
init_params.structSize = 16
|
||||
cupti.cuptiProfilerInitialize(ctypes.byref(init_params))
|
||||
|
||||
# Register buffer callbacks for Activity API
|
||||
self._buf_req_cb = cupti.CUpti_BuffersCallbackRequestFunc(self._buffer_requested)
|
||||
self._buf_comp_cb = cupti.CUpti_BuffersCallbackCompleteFunc(self._buffer_completed)
|
||||
self._check_cupti(cupti.cuptiActivityRegisterCallbacks(self._buf_req_cb, self._buf_comp_cb))
|
||||
|
||||
# PROFILE=1: kernel timing, PROFILE=2: PC sampling with stall reasons
|
||||
if profile_level >= 2:
|
||||
# PC sampling for stall analysis (requires elevated privileges)
|
||||
if DEBUG >= 1: print(" CUPTI: PC sampling mode (before)")
|
||||
pc_status = cupti.cuptiActivityEnable(cupti.CUPTI_ACTIVITY_KIND_PC_SAMPLING)
|
||||
if pc_status == cupti.CUPTI_SUCCESS:
|
||||
config = cupti.CUpti_ActivityPCSamplingConfig()
|
||||
config.size, config.samplingPeriod = 16, cupti.CUPTI_ACTIVITY_PC_SAMPLING_PERIOD_MIN
|
||||
cfg_status = cupti.dll.cuptiActivityConfigurePCSampling(ctx, ctypes.byref(config))
|
||||
if cfg_status == cupti.CUPTI_SUCCESS:
|
||||
if DEBUG >= 1: print(" CUPTI: PC sampling mode (before stall analysis)")
|
||||
cupti.cuptiActivityEnable(cupti.CUPTI_ACTIVITY_KIND_PC_SAMPLING_RECORD_INFO)
|
||||
self.pc_sampling_enabled = True
|
||||
if DEBUG >= 1: print(" CUPTI: PC sampling mode (stall analysis)")
|
||||
elif cfg_status == 35:
|
||||
if DEBUG >= 1: print(" CUPTI: PC sampling needs: echo 'options nvidia NVreg_RestrictProfilingToAdminUsers=0'|sudo tee /etc/modprobe.d/nvidia.conf && sudo reboot")
|
||||
# Fall back to kernel timing if PC sampling setup failed
|
||||
if not self.pc_sampling_enabled:
|
||||
self._check_cupti(cupti.cuptiActivityEnable(cupti.CUPTI_ACTIVITY_KIND_KERNEL))
|
||||
else:
|
||||
# Kernel activity tracing for timing
|
||||
self._check_cupti(cupti.cuptiActivityEnable(cupti.CUPTI_ACTIVITY_KIND_KERNEL))
|
||||
|
||||
self.initialized = True
|
||||
|
||||
def _buffer_requested(self, buffer, size, max_num_records):
|
||||
buf = (ctypes.c_uint8 * 1024 * 1024)() # 1MB buffer
|
||||
self.buffers.append(buf)
|
||||
buffer[0] = ctypes.cast(buf, ctypes.POINTER(ctypes.c_uint8))
|
||||
size[0] = ctypes.sizeof(buf)
|
||||
max_num_records[0] = 0
|
||||
|
||||
def _buffer_completed(self, ctx, stream_id, buffer, size, valid_size):
|
||||
if valid_size > 0:
|
||||
record = ctypes.POINTER(cupti.CUpti_Activity)()
|
||||
while cupti.cuptiActivityGetNextRecord(buffer, valid_size, ctypes.byref(record)) == cupti.CUPTI_SUCCESS:
|
||||
kind = record.contents.kind
|
||||
if kind == cupti.CUPTI_ACTIVITY_KIND_CONCURRENT_KERNEL:
|
||||
kernel = ctypes.cast(record, ctypes.POINTER(cupti.CUpti_ActivityKernel9)).contents
|
||||
name = ctypes.string_at(kernel.name).decode() if kernel.name else "unknown"
|
||||
duration_us = (kernel.end - kernel.start) / 1000.0
|
||||
grid, block = (kernel.gridX, kernel.gridY, kernel.gridZ), (kernel.blockX, kernel.blockY, kernel.blockZ)
|
||||
print(f" CUPTI: {name[:40]:40s} | {duration_us:10.2f} us | grid={grid} block={block} | regs={kernel.registersPerThread:3d} smem={kernel.staticSharedMemory + kernel.dynamicSharedMemory:6d}B")
|
||||
elif kind == cupti.CUPTI_ACTIVITY_KIND_PC_SAMPLING:
|
||||
pc = ctypes.cast(record, ctypes.POINTER(cupti.CUpti_ActivityPCSampling3)).contents
|
||||
cid = pc.correlationId
|
||||
if cid not in self.kernel_stalls: self.kernel_stalls[cid] = {}
|
||||
self.kernel_stalls[cid][pc.stallReason] = self.kernel_stalls[cid].get(pc.stallReason, 0) + pc.samples
|
||||
self.pc_samples.append({
|
||||
'correlationId': pc.correlationId, 'pcOffset': pc.pcOffset, 'stallReason': pc.stallReason,
|
||||
'samples': pc.samples, 'latencySamples': pc.latencySamples, 'functionId': pc.functionId, 'sourceLocatorId': pc.sourceLocatorId
|
||||
})
|
||||
if DEBUG >= 3:
|
||||
print(f" PC {pc.pcOffset:#x} stall={stall_reason_name(pc.stallReason)} samples={pc.samples} latency={pc.latencySamples} func={pc.functionId} src={pc.sourceLocatorId}")
|
||||
elif kind == cupti.CUPTI_ACTIVITY_KIND_PC_SAMPLING_RECORD_INFO:
|
||||
info = ctypes.cast(record, ctypes.POINTER(cupti.CUpti_ActivityPCSamplingRecordInfo)).contents
|
||||
cid = info.correlationId
|
||||
if cid in self.kernel_stalls:
|
||||
stalls = self.kernel_stalls[cid]
|
||||
total = sum(stalls.values())
|
||||
if total > 0:
|
||||
top = sorted(stalls.items(), key=lambda x: -x[1])[:5]
|
||||
stall_str = " ".join(f"{stall_reason_name(r)}:{100*c//total}%" for r,c in top if c > 0)
|
||||
print(f" CUPTI stalls (corr={cid}): {total} samples | {stall_str}")
|
||||
del self.kernel_stalls[cid]
|
||||
else: print(f" CUPTI: Unhandled activity kind {kind}")
|
||||
|
||||
def flush(self):
|
||||
if not self.initialized: return
|
||||
self._check_cupti(cupti.cuptiActivityFlushAll(0))
|
||||
|
||||
# Module-level profiler instance
|
||||
_profiler: CUPTIProfiler | None = None
|
||||
|
||||
def get_profiler() -> CUPTIProfiler | None:
|
||||
return _profiler
|
||||
|
||||
def get_cupti_raw_buffers() -> list[bytes]:
|
||||
return _profiler.raw_buffers if _profiler else []
|
||||
|
||||
def clear_cupti_raw_buffers():
|
||||
if _profiler: _profiler.raw_buffers.clear()
|
||||
|
||||
def get_cupti_pc_samples() -> list[dict]:
|
||||
return _profiler.pc_samples if _profiler else []
|
||||
|
||||
def clear_cupti_pc_samples():
|
||||
if _profiler: _profiler.pc_samples.clear()
|
||||
|
||||
# Raw PMA buffer access (from ioctl interception)
|
||||
def get_pma_raw_dumps() -> list[bytes]:
|
||||
try:
|
||||
from extra.nv_gpu_driver.nv_ioctl import get_pma_raw_dumps as _get
|
||||
return _get()
|
||||
except ImportError: return []
|
||||
|
||||
def clear_pma_raw_dumps():
|
||||
try:
|
||||
from extra.nv_gpu_driver.nv_ioctl import clear_pma_raw_dumps as _clear
|
||||
_clear()
|
||||
except ImportError: pass
|
||||
|
||||
def enable(profile_level:int=2):
|
||||
global _profiler
|
||||
if _profiler is not None: return
|
||||
|
||||
_profiler = CUPTIProfiler()
|
||||
|
||||
# Patch CUDADevice to initialize CUPTI profiler
|
||||
from tinygrad.runtime.ops_cuda import CUDADevice
|
||||
_orig_init = CUDADevice.__init__
|
||||
_orig_sync = CUDADevice.synchronize
|
||||
|
||||
def _patched_init(self, device: str):
|
||||
_orig_init(self, device)
|
||||
device_id = int(device.split(":")[1]) if ":" in device else 0
|
||||
_profiler.init(self.context, device_id, profile_level)
|
||||
|
||||
def _patched_sync(self):
|
||||
_orig_sync(self)
|
||||
if _profiler: _profiler.flush()
|
||||
|
||||
CUDADevice.__init__ = _patched_init
|
||||
CUDADevice.synchronize = _patched_sync
|
||||
|
||||
def enable_auto():
|
||||
if (profile_level:=getenv("PROFILE", 0)) > 0: enable(profile_level)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,189 @@
|
||||
#!/usr/bin/env python3
|
||||
from __future__ import annotations
|
||||
import enum, collections
|
||||
from typing import Iterator
|
||||
from tinygrad.helpers import colored
|
||||
from tinygrad.renderer.amd.sqtt import PacketType, bits
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# STALL REASONS
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class StallReason(enum.IntEnum):
|
||||
# Based on CUpti_ActivityPCSamplingStallReason
|
||||
INVALID = 0
|
||||
NONE = 1 # selected, selected_not_issued
|
||||
INST_FETCH = 2 # branch_resolving, no_instructions
|
||||
EXEC_DEPENDENCY = 3 # short_scoreboard, wait
|
||||
MEMORY_DEPENDENCY = 4 # long_scoreboard
|
||||
TEXTURE = 5 # tex_throttle
|
||||
SYNC = 6 # barrier, membar
|
||||
CONSTANT_MEMORY = 7 # imc_miss
|
||||
PIPE_BUSY = 8 # mio_throttle, math_pipe_throttle
|
||||
MEMORY_THROTTLE = 9 # drain, lg_throttle
|
||||
NOT_SELECTED = 10 # not_selected
|
||||
OTHER = 11 # misc, dispatch_stall
|
||||
SLEEPING = 12 # sleeping
|
||||
|
||||
STALL_KEY_MAP_AMPERE: dict[int, StallReason] = {
|
||||
1: StallReason.MEMORY_THROTTLE, 15: StallReason.MEMORY_THROTTLE,
|
||||
2: StallReason.CONSTANT_MEMORY,
|
||||
3: StallReason.SYNC,
|
||||
6: StallReason.INST_FETCH, 11: StallReason.INST_FETCH,
|
||||
7: StallReason.EXEC_DEPENDENCY, 10: StallReason.EXEC_DEPENDENCY,
|
||||
9: StallReason.MEMORY_DEPENDENCY,
|
||||
12: StallReason.PIPE_BUSY,
|
||||
17: StallReason.OTHER, 20: StallReason.OTHER,
|
||||
18: StallReason.NONE,
|
||||
}
|
||||
|
||||
STALL_KEY_MAP_BLACKWELL: dict[int, StallReason] = {
|
||||
0x01: StallReason.MEMORY_THROTTLE, 0x0e: StallReason.MEMORY_THROTTLE,
|
||||
0x02: StallReason.SYNC,
|
||||
0x05: StallReason.INST_FETCH, 0x0a: StallReason.INST_FETCH,
|
||||
0x06: StallReason.EXEC_DEPENDENCY, 0x09: StallReason.EXEC_DEPENDENCY,
|
||||
0x08: StallReason.MEMORY_DEPENDENCY,
|
||||
0x0b: StallReason.PIPE_BUSY, 0x0f: StallReason.PIPE_BUSY,
|
||||
0x10: StallReason.OTHER, 0x13: StallReason.OTHER,
|
||||
0x11: StallReason.NONE,
|
||||
}
|
||||
|
||||
# Lookup table for extracting sample bytes from 32-byte packet (bytes 0-3, 8-31, skipping header at 4-7)
|
||||
LOOKUP_28B = [0, 1, 2, 3, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# PACKET HEADER
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class PMAHeader(PacketType):
|
||||
num_bytes = bits[4:0] # number of sample bytes in this packet
|
||||
tpc_id_lo = bits[15:8] # TPC identifier low 8 bits
|
||||
tpc_id_hi = bits[27:25] # TPC identifier high 3 bits
|
||||
dropped = bits[28:28] # dropped flag (resets byte accumulator)
|
||||
@property
|
||||
def tpc_id(self) -> int: return self.tpc_id_lo | (self.tpc_id_hi << 8)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# 8-BYTE SAMPLE FORMAT (Ampere/Ada/Hopper)
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class PMASampleAmpere8B(PacketType):
|
||||
pc_raw = bits[44:0] # raw PC value (pc_offset = pc_raw << 4)
|
||||
stall_key = bits[49:45] # stall reason key
|
||||
wave_id = bits[55:50] # warp/wave identifier
|
||||
active = bits[62:62] # 1 if warp was executing, 0 if scheduled but not issued
|
||||
@property
|
||||
def pc_offset(self) -> int: return self.pc_raw << 4
|
||||
@property
|
||||
def stall_reason(self) -> StallReason: return STALL_KEY_MAP_AMPERE.get(self.stall_key, StallReason.OTHER)
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# 9-BYTE SAMPLE FORMAT (Blackwell+)
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
class PMASampleBlackwell9B(PacketType):
|
||||
stall_key = bits[5:0] # stall reason key
|
||||
pc_raw = bits[60:8] # raw PC value (pc_offset = pc_raw << 4)
|
||||
wave_hi = bits[7:6] # wave_id high 2 bits
|
||||
wave_lo = bits[71:68] # wave_id low 4 bits
|
||||
active = bits[67:67] # 1 if warp was executing, 0 if scheduled but not issued
|
||||
@property
|
||||
def pc_offset(self) -> int: return self.pc_raw << 4
|
||||
@property
|
||||
def stall_reason(self) -> StallReason: return STALL_KEY_MAP_BLACKWELL.get(self.stall_key, StallReason.OTHER)
|
||||
@property
|
||||
def wave_id(self) -> int: return (self.wave_hi << 4) | self.wave_lo
|
||||
|
||||
PMASample = PMASampleAmpere8B|PMASampleBlackwell9B
|
||||
|
||||
def decode(data: bytes, sm_version: int = 0x800) -> Iterator[tuple[PMASample, int]]:
|
||||
use_9byte = sm_version >= 0xa04
|
||||
record_size = 9 if use_9byte else 8
|
||||
sample_cls = PMASampleBlackwell9B if use_9byte else PMASampleAmpere8B
|
||||
|
||||
tpc_state: dict[int, list[int]] = collections.defaultdict(list)
|
||||
for pkt_idx in range(len(data) // 32):
|
||||
pkt = data[pkt_idx * 32:(pkt_idx + 1) * 32]
|
||||
hdr = PMAHeader.from_raw(int.from_bytes(pkt[4:8], 'little'))
|
||||
|
||||
if hdr.dropped: tpc_state[hdr.tpc_id].clear()
|
||||
|
||||
for i in range(hdr.num_bytes):
|
||||
tpc_state[hdr.tpc_id].append(pkt[LOOKUP_28B[i]])
|
||||
|
||||
while len(tpc_state[hdr.tpc_id]) >= record_size:
|
||||
yield sample_cls.from_raw(int.from_bytes(bytes(tpc_state[hdr.tpc_id][:record_size]), 'little')), hdr.tpc_id
|
||||
del tpc_state[hdr.tpc_id][:record_size]
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# CLI
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
STALL_COLORS = {
|
||||
StallReason.NONE: "green", StallReason.INST_FETCH: "yellow", StallReason.EXEC_DEPENDENCY: "cyan",
|
||||
StallReason.MEMORY_DEPENDENCY: "red", StallReason.SYNC: "magenta", StallReason.CONSTANT_MEMORY: "blue",
|
||||
StallReason.PIPE_BUSY: "yellow", StallReason.MEMORY_THROTTLE: "RED", StallReason.OTHER: "white",
|
||||
}
|
||||
|
||||
def decode_tpc_id(tpc_id:int) -> tuple[int, int, int]:
|
||||
# NOTE: valid only for ops_nv, cuda encoding is different
|
||||
return (tpc_id >> 5, (tpc_id >> 1) & 0xf, tpc_id & 1)
|
||||
|
||||
def print_packets(data:bytes, sm_version:int=0x800) -> None:
|
||||
record_size = 9 if sm_version >= 0x890 else 8
|
||||
tpc_state: dict[int, list[int]] = collections.defaultdict(list)
|
||||
for i in range(len(data) // 32):
|
||||
pkt = data[i * 32:(i + 1) * 32]
|
||||
hdr = PMAHeader.from_raw(int.from_bytes(pkt[4:8], 'little'))
|
||||
if hdr.dropped: tpc_state[hdr.tpc_id].clear()
|
||||
for j in range(hdr.num_bytes): tpc_state[hdr.tpc_id].append(pkt[LOOKUP_28B[j]])
|
||||
# Show complete records extracted from this packet
|
||||
records = []
|
||||
while len(tpc_state[hdr.tpc_id]) >= record_size:
|
||||
records.append(bytes(tpc_state[hdr.tpc_id][:record_size]).hex())
|
||||
del tpc_state[hdr.tpc_id][:record_size]
|
||||
leftover = len(tpc_state[hdr.tpc_id])
|
||||
print(f"Pkt {i:3d}: tpc={hdr.tpc_id:4d} n={hdr.num_bytes:2d} drop={hdr.dropped} left={leftover} | {' '.join(records)}")
|
||||
|
||||
def print_aggregated(samples:list[tuple[PMASample, int]]) -> None:
|
||||
if not samples: return
|
||||
base_pc = min(s.pc_offset for s, _ in samples)
|
||||
counter: collections.Counter[tuple[int, StallReason]] = collections.Counter((s.pc_offset, s.stall_reason) for s, _ in samples)
|
||||
print(f"\nAggregated samples (base_pc=0x{base_pc:x}):")
|
||||
for (pc, reason), cnt in sorted(counter.items()):
|
||||
stall_str = colored(f"{reason.name:17}", STALL_COLORS.get(reason, "white"))
|
||||
print(f" pc=0x{pc - base_pc:06x} {stall_str} samples={cnt:4d}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys, pickle
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: python decode.py <pkl_file> [--raw] [--sm=0xNNN]")
|
||||
sys.exit(1)
|
||||
|
||||
with open(sys.argv[1], "rb") as f:
|
||||
data = pickle.load(f)
|
||||
|
||||
if isinstance(data, dict):
|
||||
sm_version = 0x800 # default to Ampere
|
||||
for arg in sys.argv:
|
||||
if arg.startswith("--sm="): sm_version = int(arg[5:], 0)
|
||||
dumps = [(i, x, sm_version) for i, x in enumerate(data["pma_raw_dumps"])]
|
||||
else:
|
||||
devs = {e.device: e for e in data if type(e).__name__ == "ProfileDeviceEvent"}
|
||||
dumps = []
|
||||
for i, e in enumerate(e for e in data if type(e).__name__ == "ProfilePMAEvent"):
|
||||
dumps.append((i, e.blob, devs[e.device].props.get('sm_version', 0x800)))
|
||||
|
||||
for dump_idx, raw, sm_ver in dumps:
|
||||
print(f"\n{'='*60}\nDump {dump_idx} ({len(raw)} bytes, {len(raw)//32} packets)\n{'='*60}")
|
||||
if "--raw" in sys.argv: print_packets(raw, sm_ver)
|
||||
else:
|
||||
samples = []
|
||||
for s, tpc_id in decode(raw, sm_ver):
|
||||
gpc, tpc, sm = decode_tpc_id(tpc_id)
|
||||
stall_str = colored(f"{s.stall_reason.name:17}", STALL_COLORS.get(s.stall_reason, "white"))
|
||||
print(f"pc=0x{s.pc_offset:06x} {stall_str} ev={s.stall_key:2d} active={s.active} wave={s.wave_id:2d} gpc={gpc} tpc={tpc} sm={sm}")
|
||||
samples.append((s, tpc_id))
|
||||
print(f"\nDecoded {len(samples)} samples:")
|
||||
print_aggregated(samples)
|
||||
@@ -0,0 +1,76 @@
|
||||
import pickle, unittest
|
||||
from collections import Counter
|
||||
from pathlib import Path
|
||||
|
||||
from extra.nv_pma.decode import decode
|
||||
from tinygrad.helpers import DEBUG
|
||||
|
||||
EXAMPLES_DIR = Path(__file__).parent.parent / "examples"
|
||||
EXAMPLES_5090_DIR = Path(__file__).parent.parent / "examples_5090"
|
||||
|
||||
def decode_and_aggregate(raw_dumps: list[bytes], sm_version: int = 0x800) -> Counter[tuple[int, int]]:
|
||||
"""Decode all PMA buffers and aggregate by (relative_pc, stall_reason). Each dump is normalized separately."""
|
||||
result: Counter[tuple[int, int]] = Counter()
|
||||
for raw in raw_dumps:
|
||||
samples = [s for s, _ in decode(raw, sm_version)]
|
||||
if not samples: continue
|
||||
base_pc = min(s.pc_offset for s in samples)
|
||||
result += Counter((s.pc_offset - base_pc, int(s.stall_reason)) for s in samples)
|
||||
return result
|
||||
|
||||
def cupti_to_counter(cupti_records: list[dict]) -> Counter[tuple[int, int]]:
|
||||
"""Convert CUPTI records to Counter[(pcOffset, stallReason)]."""
|
||||
counter: Counter[tuple[int, int]] = Counter()
|
||||
for r in cupti_records:
|
||||
counter[(r['pcOffset'], r['stallReason'])] += r['samples']
|
||||
return counter
|
||||
|
||||
class TestNVProf(unittest.TestCase):
|
||||
def _test_example(self, name: str, sm_version: int = 0x800, examples_dir: Path = EXAMPLES_DIR):
|
||||
pkl_file = examples_dir / f"{name}.pkl"
|
||||
if not pkl_file.exists():
|
||||
self.skipTest(f"Example data not found: {pkl_file}. Run collect.py first.")
|
||||
|
||||
with open(pkl_file, "rb") as f:
|
||||
data = pickle.load(f)
|
||||
|
||||
self.assertEqual(data["test_name"], name)
|
||||
pma_agg = decode_and_aggregate(data["pma_raw_dumps"], sm_version)
|
||||
cupti_agg = cupti_to_counter(data["cupti_pc_samples"])
|
||||
|
||||
if DEBUG >= 2:
|
||||
total = sum(cupti_agg.values())
|
||||
mismatched = sum(abs(pma_agg.get(k, 0) - v) for k, v in cupti_agg.items())
|
||||
mismatched += sum(v for k, v in pma_agg.items() if k not in cupti_agg)
|
||||
mismatched //= 2
|
||||
|
||||
print(f"\n=== Test: {name} ===")
|
||||
print(f"Total samples: {total}, Mismatched: {mismatched} ({mismatched/total*100 if total else 0:.1f}%)")
|
||||
|
||||
self.assertEqual(pma_agg, cupti_agg, f"PMA: {dict(pma_agg)}\nCUPTI: {dict(cupti_agg)}")
|
||||
|
||||
# Ampere tests (8-byte format)
|
||||
def test_decode_test_plus(self): self._test_example("test_plus")
|
||||
def test_decode_test_reduce_sum(self): self._test_example("test_reduce_sum")
|
||||
def test_decode_test_broadcast(self): self._test_example("test_broadcast")
|
||||
def test_decode_test_matmul(self): self._test_example("test_matmul")
|
||||
def test_decode_test_plus_big(self): self._test_example("test_plus_big")
|
||||
def test_decode_test_elementwise_chain(self): self._test_example("test_elementwise_chain")
|
||||
def test_decode_test_conv2d(self): self._test_example("test_conv2d")
|
||||
def test_decode_test_large_matmul(self): self._test_example("test_large_matmul")
|
||||
|
||||
# Blackwell/5090 tests (9-byte format)
|
||||
def test_5090_test_plus(self): self._test_example("test_plus", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_plus_big(self): self._test_example("test_plus_big", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_broadcast(self): self._test_example("test_broadcast", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_matmul(self): self._test_example("test_matmul", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_large_matmul(self): self._test_example("test_large_matmul", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_reduce_sum(self): self._test_example("test_reduce_sum", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_reduce_max(self): self._test_example("test_reduce_max", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_elementwise_chain(self): self._test_example("test_elementwise_chain", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_conv2d(self): self._test_example("test_conv2d", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_exp(self): self._test_example("test_exp", 0xa04, EXAMPLES_5090_DIR)
|
||||
def test_5090_test_softmax(self): self._test_example("test_softmax", 0xa04, EXAMPLES_5090_DIR)
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -1,12 +1,13 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
export PAGE_SIZE=1
|
||||
export PYTHONPATH=.
|
||||
export LOGOPS=/tmp/ops
|
||||
export CAPTURE_PROCESS_REPLAY=1
|
||||
rm $LOGOPS
|
||||
rm "$LOGOPS" 2>/dev/null || true
|
||||
test/external/process_replay/reset.py
|
||||
|
||||
CI=1 python3 -m pytest -n=auto test/test_ops.py test/test_nn.py test/test_winograd.py test/models/test_real_world.py --durations=20
|
||||
CI=1 python3 -m pytest -n=auto test/backend/test_ops.py test/backend/test_nn.py test/unit/test_winograd.py test/null/test_real_world.py --durations=20
|
||||
CL=1 python3 -m pytest test/test_tiny.py
|
||||
|
||||
# extract, sort and uniq
|
||||
|
||||
@@ -1,31 +0,0 @@
|
||||
import random
|
||||
from extra.optimization.helpers import load_worlds, ast_str_to_lin
|
||||
from tinygrad.codegen.opt.search import actions
|
||||
from tinygrad.codegen.opt.kernel import Kernel
|
||||
from tinygrad.codegen.opt.heuristic import hand_coded_optimizations
|
||||
from tinygrad.helpers import tqdm
|
||||
|
||||
tactions = set()
|
||||
def test_rebuild(lin):
|
||||
linr = Kernel(lin.ast)
|
||||
for o in lin.applied_opts:
|
||||
assert o in actions, f"{o} is not in actions"
|
||||
tactions.add(o)
|
||||
linr.apply_opt(o)
|
||||
|
||||
assert len(lin.sts) == len(linr.sts)
|
||||
for st1,st2 in zip(lin.sts, linr.sts):
|
||||
assert st1 == st2, f"{st1} != {st2}"
|
||||
|
||||
if __name__ == "__main__":
|
||||
ast_strs = load_worlds(False, False, False)
|
||||
random.shuffle(ast_strs)
|
||||
ast_strs = ast_strs[:2000]
|
||||
for ast_str in tqdm(ast_strs):
|
||||
lin = ast_str_to_lin(ast_str)
|
||||
#if not lin.apply_tensor_cores():
|
||||
lin.apply_opts(hand_coded_optimizations(lin))
|
||||
test_rebuild(lin)
|
||||
|
||||
print(len(tactions), len(actions))
|
||||
print(sorted(list(tactions)))
|
||||
@@ -1,76 +0,0 @@
|
||||
import os
|
||||
import numpy as np
|
||||
import math, random
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.nn.state import get_parameters, get_state_dict, safe_save, safe_load, load_state_dict
|
||||
from tinygrad.codegen.opt.search import actions, bufs_from_lin, get_kernel_actions
|
||||
from tinygrad.nn.optim import Adam
|
||||
from extra.optimization.extract_policynet import PolicyNet
|
||||
from extra.optimization.helpers import load_worlds, ast_str_to_lin, lin_to_feats, time_linearizer
|
||||
|
||||
if __name__ == "__main__":
|
||||
net = PolicyNet()
|
||||
if os.path.isfile("/tmp/policynet.safetensors"): load_state_dict(net, safe_load("/tmp/policynet.safetensors"))
|
||||
optim = Adam(get_parameters(net))
|
||||
|
||||
ast_strs = load_worlds()
|
||||
|
||||
# select a world
|
||||
all_feats, all_acts, all_rews = [], [], []
|
||||
while 1:
|
||||
Tensor.training = False
|
||||
lin = ast_str_to_lin(random.choice(ast_strs))
|
||||
rawbufs = bufs_from_lin(lin)
|
||||
tm = last_tm = base_tm = time_linearizer(lin, rawbufs)
|
||||
|
||||
# take actions
|
||||
feats, acts, rews = [], [], []
|
||||
while 1:
|
||||
feat = lin_to_feats(lin)
|
||||
feats.append(feat)
|
||||
probs = net(Tensor([feat])).exp()[0].numpy()
|
||||
|
||||
# mask valid actions
|
||||
valid_action_mask = np.zeros((len(actions)+1), dtype=np.float32)
|
||||
for x in get_kernel_actions(lin): valid_action_mask[x] = 1
|
||||
probs *= valid_action_mask
|
||||
probs /= sum(probs)
|
||||
|
||||
act = np.random.choice(len(probs), p=probs)
|
||||
acts.append(act)
|
||||
if act == 0:
|
||||
rews.append(0)
|
||||
break
|
||||
try:
|
||||
lin.apply_opt(actions[act-1])
|
||||
tm = time_linearizer(lin, rawbufs)
|
||||
if math.isinf(tm): raise Exception("failed")
|
||||
rews.append(((last_tm-tm)/base_tm))
|
||||
last_tm = tm
|
||||
except Exception:
|
||||
rews.append(-0.5)
|
||||
break
|
||||
#print(f"{tm*1e6:10.2f}", lin.colored_shape())
|
||||
|
||||
assert len(feats) == len(acts) and len(acts) == len(rews)
|
||||
#print(rews)
|
||||
print(f"***** EPISODE {len(rews)} steps, {sum(rews):5.2f} reward, {base_tm*1e6:12.2f} -> {tm*1e6:12.2f} : {lin.colored_shape()}")
|
||||
all_feats += feats
|
||||
all_acts += acts
|
||||
# rewards to go
|
||||
for i in range(len(rews)-2, -1, -1): rews[i] += rews[i+1]
|
||||
all_rews += rews
|
||||
|
||||
BS = 32
|
||||
if len(all_feats) >= BS:
|
||||
Tensor.training = True
|
||||
x = Tensor(all_feats[:BS])
|
||||
mask = np.zeros((BS, len(actions)+1), dtype=np.float32)
|
||||
mask[range(BS), all_acts[:BS]] = all_rews[:BS]
|
||||
loss = -(net(x) * Tensor(mask)).mean()
|
||||
optim.zero_grad()
|
||||
loss.backward()
|
||||
optim.step()
|
||||
all_feats = all_feats[BS:]
|
||||
all_acts = all_acts[BS:]
|
||||
all_rews = all_rews[BS:]
|
||||
@@ -1,32 +0,0 @@
|
||||
from typing import List, Tuple
|
||||
from tinygrad.codegen.opt.kernel import Kernel
|
||||
from tinygrad.codegen.opt.search import get_kernel_actions, actions
|
||||
|
||||
_net = None
|
||||
def beam_q_estimate(beam:List[Tuple[Kernel, float]]) -> List[Tuple[Kernel, float]]:
|
||||
global _net
|
||||
if _net is None:
|
||||
from tinygrad.nn.state import load_state_dict, safe_load
|
||||
from extra.optimization.pretrain_valuenet import ValueNet
|
||||
_net = ValueNet(1021+len(actions), 2)
|
||||
load_state_dict(_net, safe_load("/tmp/qnet.safetensors"), verbose=False)
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.helpers import Context
|
||||
from extra.optimization.helpers import lin_to_feats
|
||||
import numpy as np
|
||||
feats = []
|
||||
lins = []
|
||||
base_tms = []
|
||||
for lin,tm in beam:
|
||||
lin_feats = lin_to_feats(lin)
|
||||
for a,v in get_kernel_actions(lin, include_0=False).items():
|
||||
acts = np.zeros(len(actions))
|
||||
acts[a-1] = 1.0
|
||||
feats.append(np.concatenate([lin_feats, acts]))
|
||||
lins.append(v)
|
||||
base_tms.append(tm)
|
||||
with Context(BEAM=0):
|
||||
with Tensor.train(False):
|
||||
preds = _net(Tensor(feats)).numpy()
|
||||
pred_time = np.array(base_tms) / np.exp(preds[:, 0])
|
||||
return sorted(zip(lins, pred_time), key=lambda x: x[1])
|
||||
@@ -1,34 +0,0 @@
|
||||
import argparse
|
||||
from extra.optimization.helpers import ast_str_to_lin, time_linearizer
|
||||
|
||||
from tinygrad import dtypes
|
||||
from tinygrad.helpers import BEAM, getenv
|
||||
from tinygrad.device import Device, Compiled
|
||||
from tinygrad.codegen.opt.kernel import Kernel
|
||||
from tinygrad.codegen.opt.search import beam_search, bufs_from_lin
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
parser = argparse.ArgumentParser(description="Run a search for the optimal opts for a kernel", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
||||
parser.add_argument("--ast", type=str, default=None, help="the ast for the kernel to be optimized")
|
||||
parser.add_argument("--file", type=str, default=None, help="a file containing asts to be optimized, one per line")
|
||||
args = parser.parse_args()
|
||||
|
||||
device: Compiled = Device[Device.DEFAULT]
|
||||
print(f"optimizing for {Device.DEFAULT}")
|
||||
|
||||
if args.ast is not None:
|
||||
ast_strs = [args.ast]
|
||||
elif args.file is not None:
|
||||
with open(args.file, 'r') as file:
|
||||
ast_strs = file.readlines()
|
||||
|
||||
for i, ast_str in enumerate(ast_strs):
|
||||
print(f"optimizing {i}/{len(ast_strs)}\nast={ast_str}")
|
||||
lin = ast_str_to_lin(ast_str, opts=device.renderer)
|
||||
rawbufs = bufs_from_lin(lin)
|
||||
lin = beam_search(lin, rawbufs, getenv("BEAM", 8), bool(getenv("BEAM_ESTIMATE", 1)))
|
||||
|
||||
tm = time_linearizer(lin, rawbufs, allow_test_size=False, cnt=10)
|
||||
print(f"final time {tm*1e6:9.0f} us: {lin.colored_shape()}")
|
||||
print(lin.applied_opts)
|
||||
@@ -1,19 +0,0 @@
|
||||
import unittest
|
||||
|
||||
from extra.optimization.helpers import load_worlds
|
||||
|
||||
class TestKernelDataset(unittest.TestCase):
|
||||
def test_load_worlds_filters(self):
|
||||
all_kernels = load_worlds(filter_reduce=False, filter_noimage=False, filter_novariable=False)
|
||||
|
||||
reduce_kernels = load_worlds(filter_reduce=True, filter_noimage=False, filter_novariable=False)
|
||||
self.assertGreater(len(all_kernels), len(reduce_kernels))
|
||||
|
||||
image_kernels = load_worlds(filter_reduce=False, filter_noimage=True, filter_novariable=False)
|
||||
self.assertGreater(len(all_kernels), len(image_kernels))
|
||||
|
||||
variable_kernels = load_worlds(filter_reduce=False, filter_noimage=False, filter_novariable=True)
|
||||
self.assertGreater(len(all_kernels), len(variable_kernels))
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -1,67 +0,0 @@
|
||||
import numpy as np
|
||||
import math
|
||||
import random
|
||||
np.set_printoptions(suppress=True)
|
||||
from copy import deepcopy
|
||||
from tinygrad.helpers import getenv, colored
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.nn.state import get_parameters, get_state_dict, safe_save, safe_load, load_state_dict
|
||||
from tinygrad.codegen.opt.search import bufs_from_lin, actions, get_kernel_actions
|
||||
from tinygrad.codegen.opt.heuristic import hand_coded_optimizations
|
||||
from extra.optimization.helpers import load_worlds, ast_str_to_lin, lin_to_feats, time_linearizer
|
||||
from extra.optimization.extract_policynet import PolicyNet
|
||||
from extra.optimization.pretrain_valuenet import ValueNet
|
||||
|
||||
VALUE = getenv("VALUE")
|
||||
|
||||
if __name__ == "__main__":
|
||||
if VALUE:
|
||||
net = ValueNet()
|
||||
load_state_dict(net, safe_load("/tmp/valuenet.safetensors"))
|
||||
else:
|
||||
net = PolicyNet()
|
||||
load_state_dict(net, safe_load("/tmp/policynet.safetensors"))
|
||||
|
||||
ast_strs = load_worlds()
|
||||
|
||||
# real randomness
|
||||
random.seed()
|
||||
random.shuffle(ast_strs)
|
||||
|
||||
wins = 0
|
||||
for ep_num,ast_str in enumerate(ast_strs):
|
||||
print("\nEPISODE", ep_num, f"win {wins*100/max(1,ep_num):.2f}%")
|
||||
lin = ast_str_to_lin(ast_str)
|
||||
rawbufs = bufs_from_lin(lin)
|
||||
|
||||
linhc = deepcopy(lin)
|
||||
linhc.applied_opts(hand_coded_optimizations(linhc))
|
||||
tmhc = time_linearizer(linhc, rawbufs)
|
||||
print(f"{tmhc*1e6:10.2f} HC ", linhc.colored_shape())
|
||||
|
||||
pred_time = float('nan')
|
||||
tm = float('inf')
|
||||
while 1:
|
||||
if VALUE:
|
||||
acts,feats = [], []
|
||||
for k,v in get_kernel_actions(lin).items():
|
||||
acts.append(k)
|
||||
feats.append(lin_to_feats(v))
|
||||
preds = net(Tensor(feats))
|
||||
pred_time = math.exp(preds.numpy().min())
|
||||
act = acts[preds.numpy().argmin()]
|
||||
else:
|
||||
probs = net(Tensor([lin_to_feats(lin)]))
|
||||
dist = probs.exp().numpy()
|
||||
act = dist.argmax()
|
||||
if act == 0: break
|
||||
try:
|
||||
lin.apply_opt(actions[act-1])
|
||||
except Exception:
|
||||
print("FAILED")
|
||||
break
|
||||
tm = time_linearizer(lin, rawbufs)
|
||||
print(f"{tm*1e6:10.2f} {pred_time*1e6:10.2f}", lin.colored_shape())
|
||||
|
||||
print(f"{colored('BEAT', 'green') if tm < tmhc else colored('lost', 'red')} hand coded {tmhc/tm:5.2f}x")
|
||||
wins += int(tm < tmhc)
|
||||
@@ -1,21 +0,0 @@
|
||||
from extra.optimization.helpers import load_worlds, ast_str_to_lin, time_linearizer
|
||||
from tinygrad.codegen.opt.search import bufs_from_lin, get_kernel_actions
|
||||
|
||||
if __name__ == "__main__":
|
||||
ast_strs = load_worlds()
|
||||
for i, ast_str in enumerate(ast_strs):
|
||||
lin = ast_str_to_lin(ast_str)
|
||||
rawbufs = bufs_from_lin(lin)
|
||||
test_tm = time_linearizer(lin, rawbufs)
|
||||
if test_tm < 1e-2: continue
|
||||
print(f"EXAMPLE {i}")
|
||||
acted_lins = get_kernel_actions(lin)
|
||||
ok_avg, short_avg = 0, 0
|
||||
for k,v in acted_lins.items():
|
||||
tm1 = time_linearizer(v, rawbufs)
|
||||
tm2 = time_linearizer(v, rawbufs)
|
||||
tm3 = time_linearizer(v, rawbufs, False)
|
||||
print(v.colored_shape(50), f"{tm1*1e3:10.2f} {tm2*1e3:10.2f} {tm3*1e3:10.2f} : {((tm1-tm2)/tm1)*100:5.2f}% vs {((tm1-tm3)/tm1)*100:5.2f}%")
|
||||
ok_avg += (tm1-tm2)/tm1
|
||||
short_avg += (tm1-tm3)/tm1
|
||||
print(f"{ok_avg/len(acted_lins)*100:5.2f}% vs {short_avg/len(acted_lins)*100:5.2f}%")
|
||||
@@ -2,27 +2,26 @@ import sys, pickle, decimal, json
|
||||
from tinygrad.device import ProfileDeviceEvent, ProfileGraphEvent
|
||||
from tinygrad.helpers import tqdm, temp, ProfileEvent, ProfileRangeEvent, TracingKey
|
||||
|
||||
devices:dict[str, tuple[decimal.Decimal, decimal.Decimal, int]] = {}
|
||||
def prep_ts(device:str, ts:decimal.Decimal, is_copy): return int(decimal.Decimal(ts) + devices[device][is_copy])
|
||||
def dev_to_pid(device:str, is_copy=False): return {"pid": devices[device][2], "tid": int(is_copy)}
|
||||
devices:dict[str, tuple[decimal.Decimal, int]] = {}
|
||||
def prep_ts(device:str, ts:decimal.Decimal): return int(decimal.Decimal(ts) + devices[device][0])
|
||||
def dev_to_pid(device:str): return {"pid": devices[device][1], "tid": 0}
|
||||
def dev_ev_to_perfetto_json(ev:ProfileDeviceEvent):
|
||||
devices[ev.device] = (ev.comp_tdiff, ev.copy_tdiff if ev.copy_tdiff is not None else ev.comp_tdiff, len(devices))
|
||||
devices[ev.device] = (ev.tdiff, len(devices))
|
||||
return [{"name": "process_name", "ph": "M", "pid": dev_to_pid(ev.device)['pid'], "args": {"name": ev.device}},
|
||||
{"name": "thread_name", "ph": "M", "pid": dev_to_pid(ev.device)['pid'], "tid": 0, "args": {"name": "COMPUTE"}},
|
||||
{"name": "thread_name", "ph": "M", "pid": dev_to_pid(ev.device)['pid'], "tid": 1, "args": {"name": "COPY"}}]
|
||||
{"name": "thread_name", "ph": "M", "pid": dev_to_pid(ev.device)['pid'], "tid": 0, "args": {"name": ev.device}}]
|
||||
def range_ev_to_perfetto_json(ev:ProfileRangeEvent):
|
||||
name = ev.name.display_name if isinstance(ev.name, TracingKey) else ev.name
|
||||
return [{"name": name, "ph": "X", "ts": prep_ts(ev.device, ev.st, ev.is_copy), "dur": float(ev.en-ev.st), **dev_to_pid(ev.device, ev.is_copy)}]
|
||||
return [{"name": name, "ph": "X", "ts": prep_ts(ev.device, ev.st), "dur": float(ev.en-ev.st), **dev_to_pid(ev.device)}]
|
||||
def graph_ev_to_perfetto_json(ev:ProfileGraphEvent, reccnt):
|
||||
ret = []
|
||||
for i,e in enumerate(ev.ents):
|
||||
st, en = ev.sigs[e.st_id], ev.sigs[e.en_id]
|
||||
name = e.name.display_name if isinstance(e.name, TracingKey) else e.name
|
||||
ret += [{"name": name, "ph": "X", "ts": prep_ts(e.device, st, e.is_copy), "dur": float(en-st), **dev_to_pid(e.device, e.is_copy)}]
|
||||
ret += [{"name": name, "ph": "X", "ts": prep_ts(e.device, st), "dur": float(en-st), **dev_to_pid(e.device)}]
|
||||
for dep in ev.deps[i]:
|
||||
d = ev.ents[dep]
|
||||
ret += [{"ph": "s", **dev_to_pid(d.device, d.is_copy), "id": reccnt+len(ret), "ts": prep_ts(d.device, ev.sigs[d.en_id], d.is_copy), "bp": "e"}]
|
||||
ret += [{"ph": "f", **dev_to_pid(e.device, e.is_copy), "id": reccnt+len(ret)-1, "ts": prep_ts(e.device, st, e.is_copy), "bp": "e"}]
|
||||
ret += [{"ph": "s", **dev_to_pid(d.device), "id": reccnt+len(ret), "ts": prep_ts(d.device, ev.sigs[d.en_id]), "bp": "e"}]
|
||||
ret += [{"ph": "f", **dev_to_pid(e.device), "id": reccnt+len(ret)-1, "ts": prep_ts(e.device, st), "bp": "e"}]
|
||||
return ret
|
||||
def to_perfetto(profile:list[ProfileEvent]):
|
||||
# Start json with devices.
|
||||
|
||||
@@ -42,7 +42,7 @@ def get_struct(argp, stype):
|
||||
|
||||
def format_struct(s):
|
||||
sdats = []
|
||||
for field_name, field_type in s._fields_:
|
||||
for field_name, *_ in s._real_fields_:
|
||||
if field_name in {"__pad", "PADDING_0"}: continue
|
||||
dat = getattr(s, field_name)
|
||||
if isinstance(dat, int): sdats.append(f"{field_name}:0x{dat:X}")
|
||||
|
||||
@@ -7,8 +7,8 @@ import subprocess, struct, math, functools
|
||||
from tinygrad import Tensor, dtypes, Device
|
||||
from tinygrad.helpers import getenv
|
||||
|
||||
from extra.assembly.amd.autogen.rdna3.ins import *
|
||||
from extra.assembly.amd.asm import waitcnt
|
||||
from tinygrad.runtime.autogen.amd.rdna3.ins import *
|
||||
from tinygrad.renderer.amd.asm import waitcnt
|
||||
|
||||
from test.testextra.test_cfg_viz import asm_kernel
|
||||
|
||||
|
||||
@@ -11,7 +11,7 @@ from tinygrad import Tensor
|
||||
from tinygrad.helpers import system, OSX
|
||||
from tinygrad.runtime.ops_amd import AMDProgram
|
||||
from extra.sqtt.roc import decode, WaveExec, ProfileSQTTEvent
|
||||
from tinygrad.device import Device, ProfileDeviceEvent
|
||||
from tinygrad.device import Device
|
||||
|
||||
from extra.sqtt.attempt_sqtt_parse import parse_sqtt_print_packets
|
||||
|
||||
@@ -23,7 +23,7 @@ def save_sqtt():
|
||||
dev.profile_events.clear()
|
||||
sqtt:dict[str, list[WaveExec]] = {}
|
||||
yield sqtt
|
||||
events = dev.profile_events+[ProfileDeviceEvent("AMD", props=dev.device_props())]
|
||||
events = dev.profile_events
|
||||
|
||||
#rctx = decode(events)
|
||||
#assert len(rctx.inst_execs) > 0, "empty sqtt output"
|
||||
@@ -45,6 +45,7 @@ matmul:
|
||||
.rodata
|
||||
.p2align 6
|
||||
.amdhsa_kernel matmul
|
||||
.amdhsa_kernarg_size 8
|
||||
.amdhsa_user_sgpr_kernarg_segment_ptr 1
|
||||
.amdhsa_next_free_vgpr .amdgcn.next_free_vgpr
|
||||
.amdhsa_next_free_sgpr .amdgcn.next_free_sgpr
|
||||
|
||||
@@ -0,0 +1,23 @@
|
||||
import os, subprocess
|
||||
from pathlib import Path
|
||||
from tinygrad.helpers import temp
|
||||
|
||||
EXAMPLES_DIR = Path(__file__).parent
|
||||
PROFILE_PATH = Path(temp("profile.pkl", append_user=True))
|
||||
|
||||
EXAMPLES = [
|
||||
"test.backend.test_custom_kernel.TestCustomKernel.test_empty",
|
||||
"test.test_tiny.TestTiny.test_plus",
|
||||
"test.test_tiny.TestTiny.test_gemm",
|
||||
]
|
||||
|
||||
if __name__ == "__main__":
|
||||
arch = subprocess.check_output(["python", "-c", "from tinygrad import Device; print(Device['AMD'].arch)"], text=True,
|
||||
env={**os.environ, "DEBUG":"0"}).rstrip()
|
||||
(EXAMPLES_DIR/arch).mkdir(exist_ok=True)
|
||||
for test in EXAMPLES:
|
||||
for i in range(2):
|
||||
subprocess.run(["python", "-m", "unittest", test], cwd=EXAMPLES_DIR.parent.parent.parent,
|
||||
env={**os.environ, "AMD":"1", "SQTT_LIMIT_SE":"-1", "VIZ":"-2"}, check=True)
|
||||
PROFILE_PATH.rename(dest:=EXAMPLES_DIR/arch/f"profile_{test.split('.')[-1].replace('test_', '')}_run_{i}.pkl")
|
||||
print(f"saved SQTT trace to {dest}")
|
||||
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Reference in New Issue
Block a user