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4 Commits
Author SHA1 Message Date
George HotzandGitHub 2fe45b0660 Merge branch 'master' into call_inline 2026-02-10 14:12:08 +08:00
George HotzandGitHub 1d88723aa0 Merge branch 'master' into call_inline 2026-02-10 14:02:43 +08:00
geohot b0dd3af093 inline all these calls 2026-02-10 13:25:29 +08:00
geohot e89221e9aa add inline flag for call 2026-02-10 12:19:51 +08:00
420 changed files with 17943 additions and 28724 deletions
+2 -2
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@@ -145,7 +145,7 @@ runs:
run: |
wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
sudo tee /etc/apt/sources.list.d/rocm.list <<EOF
deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/7.1 $(lsb_release -cs) main
deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/6.2 $(lsb_release -cs) main
EOF
echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
@@ -233,7 +233,7 @@ runs:
shell: bash
run: |
sudo mkdir -p /usr/local/lib
curl -s -H "Authorization: token $GH_TOKEN" curl -s https://api.github.com/repos/tinygrad/amdcomgr_dylib/releases/latest | \
curl -s -H "Authorization: token $GH_TOKEN" curl -s https://api.github.com/repos/nimlgen/amdcomgr_dylib/releases/latest | \
jq -r '.assets[] | select(.name == "libamd_comgr.dylib").browser_download_url' | \
sudo xargs curl -fL -o /usr/local/lib/libamd_comgr.dylib
cargo build --release --manifest-path ./extra/remu/Cargo.toml
+14 -21
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@@ -32,7 +32,6 @@ jobs:
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: 'autogen'
opencl: 'true'
amd: 'true'
cuda: 'true'
@@ -44,11 +43,11 @@ jobs:
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 -path "*/amd/*" -not -name "__init__.py" -not -name "comgr.py" -not -name "metal.py" -not -name "iokit.py" -not -name "corefoundation.py" -not -name "libclang.py" -delete
find tinygrad/runtime/autogen -type f -name "*.py" -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_3, 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_v13_0_12, smu_v14_0_2"
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"
python3 -c "from tinygrad.runtime.autogen import webgpu"
@@ -60,9 +59,8 @@ jobs:
- name: Check for differences
run: |
if ! git diff --quiet; then
git diff
git diff > autogen-ubuntu.patch
echo "Autogen mismatch detected. Patch available at: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
echo "Autogen files out of date. Apply patch from: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
exit 1
fi
- name: Upload patch artifact
@@ -82,7 +80,6 @@ jobs:
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: 'autogen-mac'
llvm: 'true'
- name: Regenerate autogen files
run: |
@@ -91,9 +88,8 @@ jobs:
- name: Check for differences
run: |
if ! git diff --quiet; then
git diff
git diff > autogen-macos.patch
echo "Autogen mismatch detected. Patch available at: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
echo "Autogen files out of date. Apply patch from: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
exit 1
fi
- name: Upload patch artifact
@@ -103,8 +99,8 @@ jobs:
name: autogen-macos-patch
path: autogen-macos.patch
autogen-comgr-2:
name: In-tree Autogen (comgr 2)
autogen-comgr-3:
name: In-tree Autogen (comgr 3)
runs-on: ubuntu-24.04
timeout-minutes: 15
steps:
@@ -112,32 +108,29 @@ jobs:
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: 'autogen-comgr'
- name: Install autogen support packages
run: |
wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
sudo tee /etc/apt/sources.list.d/rocm.list <<EOF
deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/6.2 $(lsb_release -cs) main
deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/6.4 $(lsb_release -cs) main
EOF
echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
sudo apt -qq update || true
sudo apt-get install -y --no-install-recommends libclang-20-dev comgr
- name: Regenerate autogen files
run: |
rm tinygrad/runtime/autogen/comgr.py
python3 -c "from tinygrad.runtime.autogen import comgr"
rm tinygrad/runtime/autogen/comgr_3.py
python3 -c "from tinygrad.runtime.autogen import comgr_3"
- name: Check for differences
run: |
if ! git diff --quiet; then
git diff
git diff > autogen-comgr2.patch
echo "Autogen mismatch detected. Patch available at: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
git diff > autogen-comgr3.patch
echo "Autogen files out of date. Apply patch from: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}#artifacts"
exit 1
fi
- name: Upload patch artifact
if: failure()
uses: actions/upload-artifact@v4
with:
name: autogen-comgr2-patch
path: autogen-comgr2.patch
name: autogen-comgr3-patch
path: autogen-comgr3.patch
+17 -34
View File
@@ -21,9 +21,6 @@ jobs:
# the 3 minute timeout should not be raised
testmacpytest:
name: Mac pytest
env:
CI: ""
CAPTURE_PROCESS_REPLAY: "0"
runs-on: [self-hosted, macOS]
timeout-minutes: 3
defaults:
@@ -44,14 +41,22 @@ jobs:
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
- name: openpilot compile3 0.10.1 driving_vision
run: FLOAT16=1 CL=1 IMAGE=2 python3.11 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/driving_vision.onnx
- name: IMAGE=1 openpilot compile3 0.10.1 driving_vision
run: FLOAT16=1 CL=1 IMAGE=1 python3.11 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/driving_vision.onnx
testmacbenchmark:
name: Mac Benchmark
@@ -332,13 +337,13 @@ jobs:
# - name: Fuzz Padded Tensor Core GEMM (PTX)
# run: NV=1 NV_PTX=1 M_START=12 M_STOP=20 M_STEP=1 N_START=6 N_STOP=10 N_STEP=1 K_START=28 K_STOP=36 K_STEP=1 HALF=1 TC_OPT=2 python3 ./extra/gemm/fuzz_matmul.py
- name: HEVC Decode Benchmark
run: VALIDATE=1 MAX_FRAMES=100 ASSERT_FPS=1400 JITBEAM=1 NV=1 PYTHONPATH=. python3 extra/hevc/decode.py
run: VALIDATE=1 MAX_FRAMES=100 JITBEAM=1 NV=1 PYTHONPATH=. python3 extra/hevc/decode.py
- name: Train MNIST
run: time PYTHONPATH=. NV=1 TARGET_EVAL_ACC_PCT=96.0 python3 examples/beautiful_mnist.py
- name: Run 10 CIFAR training steps
run: BENCHMARK_LOG=cifar_10steps ASSERT_MIN_STEP_TIME=120 NV=1 STEPS=10 python3 examples/hlb_cifar10.py
- name: Run 10 CIFAR training steps w HALF
run: BENCHMARK_LOG=cifar_10steps_half ASSERT_MIN_STEP_TIME=120 NV=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py
run: BENCHMARK_LOG=cifar_10steps_half ASSERT_MIN_STEP_TIME=110 NV=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py
- name: Run 10 CIFAR training steps w BF16
run: BENCHMARK_LOG=cifar_10steps_bf16 ASSERT_MIN_STEP_TIME=120 NV=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py
# - name: Run 10 CIFAR training steps w winograd
@@ -510,7 +515,7 @@ jobs:
- name: Run 10 CIFAR training steps
run: BENCHMARK_LOG=cifar_10steps ASSERT_MIN_STEP_TIME=200 AMD=1 STEPS=10 python3 examples/hlb_cifar10.py
- name: Run 10 CIFAR training steps w HALF
run: BENCHMARK_LOG=cifar_10steps_half ASSERT_MIN_STEP_TIME=230 AMD=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py
run: BENCHMARK_LOG=cifar_10steps_half ASSERT_MIN_STEP_TIME=200 AMD=1 STEPS=10 DEFAULT_FLOAT=HALF python3 examples/hlb_cifar10.py
# - name: Run 10 CIFAR training steps w BF16
# run: BENCHMARK_LOG=cifar_10steps_bf16 ASSERT_MIN_STEP_TIME=288 AMD=1 STEPS=10 DEFAULT_FLOAT=BFLOAT16 python3 examples/hlb_cifar10.py
# TODO: too slow
@@ -520,9 +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
# TODO: broken on some of the machines
#- 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: 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
@@ -617,27 +621,6 @@ jobs:
- 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
testcommausbgpubenchmark:
name: UsbGPU Benchmark (comma)
runs-on: [self-hosted, Linux, comma4]
timeout-minutes: 20
defaults:
run:
shell: bash -e -o pipefail {0}
if: github.repository_owner == 'tinygrad'
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: setup staging db
if: github.ref == 'refs/heads/update_benchmark_staging'
run: |
echo "CACHEDB=/tmp/staging.db" >> $GITHUB_ENV
rm -f /tmp/staging.db /tmp/staging.db-shm /tmp/staging.db-wal
- name: openpilot compile3 0.10.1 driving_vision
run: BENCHMARK_LOG=usbgpu_openpilot_0_10_1_vision PYTHONPATH="." DEV=AMD AMD_LLVM=1 AMD_IFACE=USB ASSERT_MIN_STEP_TIME=50 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/driving_vision.onnx
- name: openpilot load_pickle 0.10.1 driving_vision
run: BENCHMARK_LOG=usbgpu_openpilot_0_10_1_vision_load_pickle PYTHONPATH="." DEV=AMD AMD_IFACE=USB ASSERT_MIN_LOAD_TIME=15 python3 examples/openpilot/load_pickle.py
testreddriverbenchmark:
name: AM Benchmark
runs-on: [self-hosted, Linux, tinyboxrandom]
+126 -162
View File
@@ -1,7 +1,7 @@
name: Unit Tests
env:
# increment this when downloads substantially change to avoid the internet
CACHE_VERSION: '17'
CACHE_VERSION: '16'
CAPTURE_PROCESS_REPLAY: 1
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PYTHONPATH: ${{ github.workspace }}
@@ -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_tiny.py TestTiny.test_plus
run: FORWARD_ONLY=1 TINY_BACKEND=1 python3 test/test_ops.py TestOps.test_add
- 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/backend/test_ops.py --durations=20
run: CPU=1 CPU_LLVM=1 LLVMOPT=0 TINY_BACKEND=1 python3 -m pytest -n auto test/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
@@ -158,25 +158,25 @@ jobs:
key: be-minimal
deps: testing_unit
- name: Test dtype with Python emulator
run: DEBUG=1 PYTHON=1 python3 -m pytest -n=auto test/backend/test_dtype.py test/backend/test_dtype_alu.py
run: DEBUG=1 PYTHON=1 python3 -m pytest -n=auto test/test_dtype.py test/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/backend/test_ops.py --durations=20
run: DEBUG=2 SKIP_SLOW_TEST=1 PYTHON=1 python3 -m pytest -n=auto test/test_ops.py --durations=20
- name: Test uops with Python emulator
run: PYTHON=1 python3 -m pytest test/backend/test_uops.py --durations=20
run: PYTHON=1 python3 -m pytest test/test_uops.py --durations=20
- name: Test symbolic with Python emulator
run: PYTHON=1 python3 test/backend/test_symbolic_ops.py
run: PYTHON=1 python3 test/test_symbolic_ops.py
- name: test_renderer_failures with Python emulator
run: PYTHON=1 python3 -m pytest -rA test/backend/test_renderer_failures.py::TestRendererFailures
run: PYTHON=1 python3 -m pytest -rA test/test_renderer_failures.py::TestRendererFailures
- name: Test IMAGE=2 support
run: |
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
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
- name: Test emulated METAL tensor cores
run: |
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/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/backend/test_ops.py TestOps.test_gemm
run: DEBUG=2 AMX=1 EMULATE=AMX FORWARD_ONLY=1 PYTHON=1 python3 test/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/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 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_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
@@ -244,37 +244,6 @@ jobs:
- name: Run TYPED=1
run: CHECK_OOB=0 DEV=CPU TYPED=1 python test/test_tiny.py
nulltest:
name: Null Tests
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: unittest-13
pydeps: "pillow ftfy regex pre-commit"
deps: testing_unit
llvm: 'true'
amd: 'true'
- 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.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 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
unittest:
name: Unit Tests
runs-on: ubuntu-latest
@@ -299,6 +268,20 @@ jobs:
run: |
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
# 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 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
- name: Run GC tests
run: python test/external/external_uop_gc.py
- name: External Benchmark Schedule
@@ -312,8 +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 < 24000 lines
run: MAX_LINE_COUNT=24000 python sz.py
- name: Repo line count < 20000 lines
run: MAX_LINE_COUNT=20000 python sz.py
spec:
strategy:
@@ -333,7 +316,7 @@ jobs:
deps: testing_unit
python-version: '3.14'
- name: Test SPEC=2
run: SPEC=2 pytest --maxfail=10 -n auto --durations=30 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 }}
run: SPEC=2 pytest --maxfail=10 -n auto --durations=30 --ignore=test/models --ignore=test/null --ignore test/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
@@ -371,7 +354,7 @@ jobs:
opencl: 'true'
- name: Test CL IMAGE=2 ops
run: |
CL=1 IMAGE=2 python -m pytest -n=auto test/backend/test_ops.py --durations=20
CL=1 IMAGE=2 python -m pytest -n=auto test/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
@@ -395,7 +378,7 @@ jobs:
- 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/backend/test_optim.py -k "not muon"
run: CL=1 FUSE_OPTIM=1 python -m pytest -n=auto test/models/test_mnist.py test/test_optim.py -k "not muon"
- name: Upload artifact
uses: actions/upload-artifact@v4
with:
@@ -454,7 +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/backend/test_quantize_onnx.py
run: CPU=1 CPU_LLVM=0 python3 test/test_quantize_onnx.py
- name: Run process replay tests
uses: ./.github/actions/process-replay
@@ -568,11 +551,11 @@ jobs:
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/backend/test_ops.py
run: CPU=1 CPU_LLVM=1 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/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/backend/test_ops.py
run: CPU=1 CPU_LLVM=0 DEVECTORIZE=0 python3 -m pytest -n auto test/test_tiny.py test/test_ops.py
testdsp:
name: Linux (DSP)
@@ -604,9 +587,9 @@ jobs:
- 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/backend/test_transcendental.py TestTranscendentalVectorized
run: CC=clang-20 DEBUG=2 DSP=1 python test/test_transcendental.py TestTranscendentalVectorized
- name: Test quantize onnx
run: DEBUG=2 DSP=1 python3 test/backend/test_quantize_onnx.py
run: DEBUG=2 DSP=1 python3 test/test_quantize_onnx.py
testwebgpu:
name: Linux (WebGPU)
@@ -625,13 +608,61 @@ jobs:
- 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_tiny.py TestTiny.test_plus
WEBGPU=1 DEBUG=4 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
- name: Run selected webgpu tests
run: |
WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Vulkan" python3 -m pytest -n=auto test/backend --durations=20
WEBGPU=1 WEBGPU_BACKEND="WGPUBackendType_Vulkan" python3 -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --ignore=test/null --durations=20
- name: Run process replay tests
uses: ./.github/actions/process-replay
testamd:
strategy:
fail-fast: false
matrix:
backend: [amd, amdllvm]
name: Linux (${{ matrix.backend }})
runs-on: ubuntu-22.04
timeout-minutes: 20
env:
AMD: 1
MOCKGPU: 1
FORWARD_ONLY: 1
AMD_LLVM: ${{ matrix.backend == 'amdllvm' && '1' || matrix.backend != 'amdllvm' && '0' }}
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: ${{ matrix.backend }}-minimal
deps: testing_unit
amd: 'true'
llvm: ${{ matrix.backend == 'amdllvm' && 'true' }}
- name: Check Device.DEFAULT and print some source
run: |
python3 -c "from tinygrad import Device; assert Device.DEFAULT in ['AMD'], Device.DEFAULT"
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
- name: Run LLVM test
if: matrix.backend=='amdllvm'
run: python test/device/test_amd_llvm.py
- name: Run pytest (amd)
run: python -m pytest -n=auto test/test_ops.py test/test_dtype.py test/test_dtype_alu.py test/test_linearizer.py test/test_randomness.py test/test_jit.py test/test_graph.py test/test_multitensor.py test/device/test_hcq.py test/testextra/test_cfg_viz.py --durations=20
- name: Run pytest (amd)
run: python -m pytest test/external/external_test_am.py --durations=20
- name: Run TRANSCENDENTAL math
run: TRANSCENDENTAL=2 python -m pytest -n=auto test/test_ops.py::TestOps::test_sin test/test_ops.py::TestOps::test_cos test/test_ops.py::TestOps::test_tan test/test_ops.py::TestOps::test_exp test/test_ops.py::TestOps::test_log --durations=20
- name: Run TestOps.test_add with SQTT
run: |
VIZ=-2 DEBUG=5 python3 test/test_ops.py TestOps.test_add
extra/sqtt/rgptool.py create "/tmp/profile.pkl.$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
@@ -652,94 +683,31 @@ jobs:
python-version: '3.14'
- name: Verify AMD autogen is up to date
run: |
python -m tinygrad.renderer.amd.generate
git diff --exit-code tinygrad/runtime/autogen/amd/
python -m extra.assembly.amd.generate
git diff --exit-code extra/assembly/amd/autogen/
- 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
echo "deb http://apt.llvm.org/$(lsb_release -cs)/ llvm-toolchain-$(lsb_release -cs)-21 main" | sudo tee /etc/apt/sources.list.d/llvm.list
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
- name: Install rocprof-trace-decoder
run: sudo PYTHONPATH="." ./extra/sqtt/install_rocprof_decoder.py
- name: Run AMD renderer tests
run: AMD_LLVM=0 python -m pytest -n=auto test/amd/ --durations 20
- name: Run AMD renderer tests (AMD_LLVM=1)
run: AMD_LLVM=1 python -m pytest -n=auto test/amd/ --durations 20
- name: Run SQTT profiling tests
run: PROFILE=1 SQTT=1 python3 -m pytest -n=auto test/amd/test_sqtt_profiler.py
- name: Run AMD emulated tests on NULL backend
env:
AMD: 0
run: |
PYTHONPATH=. NULL=1 EMULATE=AMD python extra/mmapeak/mmapeak.py
PYTHONPATH=. NULL=1 EMULATE=AMD_CDNA4 python3 -m pytest -n=auto test/testextra/test_tk.py test/backend/test_asm_gemm.py
- name: Run ASM matmul on MOCKGPU
run: PYTHONPATH="." AMD=1 MOCKGPU=1 N=256 python3 extra/gemm/amd_asm_matmul.py
- name: Run LLVM test
run: AMD_LLVM=1 python test/device/test_amd_llvm.py
testmockam:
name: Linux (am)
runs-on: ubuntu-24.04
timeout-minutes: 15
env:
AMD: 1
MOCKGPU: 1
AMD_IFACE: PCI
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: mockam
deps: testing_unit
amd: 'true'
- name: Run test_tiny on MOCKAM
run: python test/test_tiny.py
- name: Run test_tiny on MOCKAM USB
run: AMD_IFACE=USB python test/test_tiny.py
- name: Run test_hcq on MOCKAM
run: python -m pytest test/device/test_hcq.py
testamd:
strategy:
fail-fast: false
matrix:
backend: [amd, amdllvm]
arch: [rdna3, rdna4]
#arch: [rdna3, rdna4, cdna4]
name: Linux (${{ matrix.backend }} ${{ matrix.arch }})
runs-on: ubuntu-22.04
timeout-minutes: 15
env:
AMD: 1
MOCKGPU: 1
MOCKGPU_ARCH: ${{ matrix.arch }}
SKIP_SLOW_TEST: 1
AMD_LLVM: ${{ matrix.backend == 'amdllvm' && '1' || matrix.backend != 'amdllvm' && '0' }}
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: ${{ matrix.backend }}-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_tiny.py TestTiny.test_plus
- name: Run pytest (amd)
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 test/external/external_test_am.py --durations=20
- name: Run TRANSCENDENTAL math
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
run: sudo PYTHONPATH="." ./extra/sqtt/install_sqtt_decoder.py
- name: Run RDNA3 emulator tests
run: AMD_LLVM=0 python -m pytest -n=auto extra/assembly/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
- name: Run RDNA3 dtype tests
run: AMD_LLVM=0 pytest -n=auto test/test_dtype_alu.py test/test_dtype.py --durations 20
- name: Run RDNA3 dtype tests (AMD_LLVM=1)
run: AMD_LLVM=1 pytest -n=auto test/test_dtype_alu.py test/test_dtype.py --durations 20
# TODO: run all once emulator is faster
- name: Run RDNA3 ops tests
run: SKIP_SLOW_TEST=1 AMD_LLVM=0 pytest -n=auto test/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
testnvidia:
strategy:
@@ -768,12 +736,12 @@ 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_tiny.py TestTiny.test_plus
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
- name: Run pytest (cuda)
# skip multitensor because it's slow
run: python -m pytest -n=auto test/backend --ignore test/backend/test_multitensor.py --durations=20
run: python -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --ignore=test/null --ignore test/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
run: VIZ=-1 PMA=1 DEBUG=5 python3 test/test_ops.py TestOps.test_add
- name: Run process replay tests
uses: ./.github/actions/process-replay
@@ -802,11 +770,11 @@ 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_tiny.py TestTiny.test_plus
DEBUG=5 FORWARD_ONLY=1 python3 test/test_ops.py TestOps.test_add
- name: Run pytest (${{ matrix.backend }})
run: python -m pytest -n=auto test/backend --durations=20
run: python -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --ignore=test/null --durations=20
- name: Run TRANSCENDENTAL math
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
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
- name: Run process replay tests
uses: ./.github/actions/process-replay
@@ -836,17 +804,15 @@ jobs:
- 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/backend/test_ops.py TestOps.test_gemm
run: METAL=1 DEBUG=3 TC=2 python test/test_ops.py TestOps.test_gemm
- name: Test tensor core ops (real)
run: METAL=1 DEBUG=3 python test/backend/test_ops.py TestOps.test_big_gemm
run: METAL=1 DEBUG=3 python test/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: Test Device Specific
run: METAL=1 python3 -m pytest test/device/test_metal.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/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
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
- name: Run pytest (amd)
env:
MOCKGPU: 1
@@ -869,8 +835,6 @@ jobs:
NV_PTX: 1
NV: 1
FORWARD_ONLY: 1
# TODO: failing due to library loading error
CAPTURE_PROCESS_REPLAY: 0
run: |
python3 -m pytest -n=auto test/device/test_hcq.py test/test_tiny.py --durations=20
- name: Run process replay tests
@@ -889,14 +853,14 @@ 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: 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
- 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
@@ -938,7 +902,7 @@ 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/backend --durations=20
run: python3 -m pytest -n=auto test/ --ignore=test/models --ignore=test/unit --ignore=test/null --durations=20
- name: Run process replay tests
uses: ./.github/actions/process-replay
- name: Run macOS-specific unit test
@@ -980,7 +944,7 @@ jobs:
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/backend/test_ops.py --durations=20
python -m pytest -n=auto test/test_tiny.py test/test_ops.py --durations=20
# ****** Compile-only Tests ******
@@ -1009,5 +973,5 @@ jobs:
shell: bash
run: |
python -c "from tinygrad import Device; assert Device.DEFAULT == 'NULL'"
DEBUG=4 python3 test/backend/test_ops.py TestOps.test_add
python -m pytest -n=auto test/backend/test_ops.py --durations=20
DEBUG=4 python3 test/test_ops.py TestOps.test_add
python -m pytest -n=auto test/test_ops.py --durations=20
-2
View File
@@ -66,5 +66,3 @@ target
.mypy_cache
mutants
.mutmut-cache
dagre/
graphlib/
+1 -1
View File
@@ -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/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
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/unit/test_assign.py test/test_tensor.py test/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
+17
View File
@@ -0,0 +1,17 @@
# 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.
+227
View File
@@ -0,0 +1,227 @@
# 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.
+1 -1
View File
@@ -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/backend/test_ops.py # just the ops tests
python3 test/test_ops.py # just the ops tests
python3 -m pytest test/ # whole test suite
```
+1 -1
View File
@@ -10,7 +10,7 @@ Directories are listed in order of how they are processed.
Group UOps into kernels.
::: tinygrad.schedule.rangeify.get_kernel_graph
::: tinygrad.schedule.rangeify.get_rangeify_map
options:
members: false
show_labels: false
+2 -2
View File
@@ -19,8 +19,8 @@ cifar_std = [0.24703225141799082, 0.24348516474564, 0.26158783926049628]
BS, STEPS = getenv("BS", 512), getenv("STEPS", 1000)
EVAL_BS = getenv("EVAL_BS", BS)
GPUS = [f'{Device.DEFAULT}:{i}' for i in range(getenv("GPUS", 1))]
assert BS % len(GPUS) == 0, f"{BS=} is not a multiple of {len(GPUS)=}"
assert EVAL_BS % len(GPUS) == 0, f"{EVAL_BS=} is not a multiple of {len(GPUS)=}"
assert BS % len(GPUS) == 0, f"{BS=} is not a multiple of {len(GPUS)=}, uneven multi GPU is slow"
assert EVAL_BS % len(GPUS) == 0, f"{EVAL_BS=} is not a multiple of {len(GPUS)=}, uneven multi GPU is slow"
class UnsyncedBatchNorm:
def __init__(self, sz:int, eps=1e-5, affine=True, track_running_stats=True, momentum=0.1, num_devices=len(GPUS)):
+23 -15
View File
@@ -65,7 +65,17 @@ def loader_process(q_in, q_out, X:Tensor, seed):
else:
# pad data with training mean
img = np.tile(np.array([[[123.68, 116.78, 103.94]]], dtype=np.uint8), (224, 224, 1))
X[idx].flatten().assign(img.tobytes())
# broken out
#img_tensor = Tensor(img.tobytes(), device='CPU')
#storage_tensor = X[idx].contiguous().realize().lazydata.base.realized
#storage_tensor._copyin(img_tensor.numpy())
# faster
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!
q_out.put(idx)
q_out.put(None)
@@ -254,8 +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].flatten().assign(x.tobytes())
Y[idx].flatten().assign(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)
@@ -369,12 +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].flatten().assign(clipped_boxes.tobytes())
labels[idx].flatten().assign(clipped_labels.tobytes())
matches[idx].flatten().assign(match_idxs.tobytes())
anchors[idx].flatten().assign(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].flatten().assign(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)
@@ -396,7 +406,6 @@ def batch_load_retinanet(dataset, val:bool, base_dir:Path, batch_size:int=32, sh
queue_in.put((idx, img, tgt))
def _setup_shared_mem(shm_name:str, size:tuple[int, ...], dtype:dtypes) -> tuple[shared_memory.SharedMemory, Tensor]:
shm_name = f"{shm_name}_{os.getpid()}"
if os.path.exists(f"/dev/shm/{shm_name}"): os.unlink(f"/dev/shm/{shm_name}")
shm = shared_memory.SharedMemory(name=shm_name, create=True, size=prod(size))
shm_tensor = Tensor.empty(*size, dtype=dtype, device=f"disk:/dev/shm/{shm_name}")
@@ -543,7 +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: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.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.count, = struct.unpack("<Q", self.idx.read(8))
doc_count, = struct.unpack("<Q", self.idx.read(8))
@@ -560,7 +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")).numpy()
self.bin_t = Tensor(base_path.with_name(f"{base_path.name}.bin"))
def _index(self, idx) -> tuple[int, int]:
return int(self.pointers[idx]), int(self.sizes[idx])
@@ -569,7 +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].view(self.dtype)
return self.bin_t[ptr:ptr+length*self.dtype.itemsize].bitcast(self.dtype).to(None)
# https://docs.nvidia.com/megatron-core/developer-guide/latest/api-guide/datasets.html
class GPTDataset:
@@ -628,7 +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 = np.concatenate(sample_parts, axis=0)
text = Tensor.cat(*sample_parts)
return text
@@ -771,8 +780,7 @@ 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)]
stacked = np.stack(batch, axis=0)
yield Tensor(stacked, device="NPY")
yield Tensor.stack(batch, dim=0)
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)
+47 -56
View File
@@ -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, profile_marker, DEBUG
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
@@ -1285,7 +1285,6 @@ def train_llama3():
from extra.models.llama import Transformer
from examples.llama3 import MODEL_PARAMS
from examples.mlperf.lr_schedulers import CosineAnnealingLRWithWarmup
from examples.mlperf.optim import GradAccClipAdamW
BENCHMARK = getenv("BENCHMARK")
@@ -1295,7 +1294,6 @@ def train_llama3():
grad_acc = config["GRADIENT_ACC_STEPS"] = getenv("GRADIENT_ACC_STEPS", 1)
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)
@@ -1335,14 +1333,9 @@ def train_llama3():
model_params = MODEL_PARAMS[getenv("LLAMA3_SIZE", "8B")]["args"]
# vocab_size from the mixtral tokenizer
if not SMALL: model_params |= {"vocab_size": 32000}
real_vocab_size = model_params['vocab_size']
if (llama_layers:=getenv("LLAMA_LAYERS")) != 0: model_params['n_layers'] = llama_layers
print(f"model parameters: {model_params}")
# pad vocab
if (MP := getenv("MP", 1)) > 1: model_params['vocab_size'] = round_up(model_params['vocab_size'], 256 * MP)
vocab_mask:Tensor = Tensor.arange(model_params['vocab_size']).reshape(1, 1, -1) >= real_vocab_size
model = Transformer(**model_params, max_context=SEQLEN, jit=False, disable_kv_cache=True)
params = get_parameters(model)
# weights are all bfloat16 for now
@@ -1357,8 +1350,6 @@ def train_llama3():
for v in get_parameters(model):
v.shard_(device, axis=None)
vocab_mask.shard_(device, axis=None)
if (MP := getenv("MP", 1)) > 1:
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(MP))
for k,v in get_state_dict(model).items():
@@ -1366,7 +1357,6 @@ def train_llama3():
elif '.attention.wq' in k: v.shard_(device, axis=0)
elif '.attention.wk' in k: v.shard_(device, axis=0)
elif '.attention.wv' in k: v.shard_(device, axis=0)
elif '.attention.wqkv' in k: v.shard_(device, axis=0)
elif '.attention.wo' in k: v.shard_(device, axis=1)
elif '.feed_forward.w1.' in k: v.shard_(device, axis=0)
elif '.feed_forward.w2.' in k: v.shard_(device, axis=1)
@@ -1379,18 +1369,13 @@ def train_llama3():
# prevents memory spike on device 0
v.realize()
vocab_mask.shard_(device, axis=2).realize()
optim_device = "CPU" if getenv("OFFLOAD_OPTIM") else None
optim = GradAccClipAdamW(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, grad_acc=grad_acc, device=optim_device)
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.empty_like().realize()
grads: list[Tensor] = [p.grad for p in optim.params]
for p in optim.params:
p.grad.assign(p.grad.zeros_like()).realize()
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)
@@ -1407,58 +1392,68 @@ def train_llama3():
def minibatch(tokens:Tensor):
if (DP := getenv("DP", 1)) > 1:
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(DP))
tokens = tokens.to(None).shard(device, 0)
tokens = tokens.shard(device, 0)
if (MP := getenv("MP", 1)) > 1:
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(MP))
tokens = tokens.shard(device)
if DP == 1 and MP == 1: tokens = tokens.to(None)
logits:Tensor = model(tokens[:, :-1], start_pos=0, temperature=math.nan)
loss = vocab_mask.where(-1e9, logits).sparse_categorical_crossentropy(tokens[:, 1:])
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")
return loss
@TinyJit
def optim_step():
grad_norm = optim.fstep(grads)
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 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()).realize()
g.assign(g.zeros_like().contiguous()).realize()
lr = optim.lr
Tensor.realize(lr, *grads)
return lr.float().to("CPU"), grad_norm.float().to("CPU")
return lr
@TinyJit
@Tensor.train(False)
def eval_step(tokens:Tensor):
if (DP := getenv("DP", 1)) > 1:
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(DP))
tokens = tokens.to(None).shard(device, 0)
tokens = tokens.shard(device, 0)
if (MP := getenv("MP", 1)) > 1:
device = tuple(f"{Device.DEFAULT}:{i}" for i in range(MP))
tokens = tokens.shard(device)
if DP == 1 and MP == 1: tokens = tokens.to(None)
logits:Tensor = model(tokens[:, :-1], start_pos=0, temperature=math.nan)
loss = vocab_mask.where(-1e9, logits).sparse_categorical_crossentropy(tokens[:, 1:])
return loss.flatten().float().to("CPU")
loss = logits.sparse_categorical_crossentropy(tokens[:, 1:])
return loss.flatten().float()
# ** data iters **
def fake_data(bs, samples):
import numpy as np
for _ in range(samples // bs):
fake_data_np = np.random.randint(0, model_params["vocab_size"], size=(bs, SEQLEN + 1), dtype=np.int32)
yield Tensor(fake_data_np, device="NPY")
yield Tensor.randint(bs, SEQLEN + 1, low=0, high=model_params["vocab_size"], dtype=dtypes.int32, device=Device.DEFAULT)
def get_train_iter():
if getenv("FAKEDATA", 0):
return fake_data(BS, SAMPLES)
else:
from examples.mlperf.dataloader import batch_load_llama3
return batch_load_llama3(BS, SAMPLES, SEQLEN, BASEDIR, seed=DATA_SEED, val=bool(TRAIN_ON_VAL), small=bool(SMALL))
return batch_load_llama3(BS, SAMPLES, SEQLEN, BASEDIR, seed=SEED, val=bool(TRAIN_ON_VAL), small=bool(SMALL))
if getenv("FAKEDATA", 0):
eval_dataset = None
@@ -1478,53 +1473,49 @@ def train_llama3():
step_times = []
while i < MAX_STEPS:
GlobalCounters.reset()
actual_gbs = GBS if i >= 2 else BS
if getenv("TRAIN", 1):
profile_marker(f"train @ {i}")
st = time.perf_counter()
stopped = False
losses, data_time, dev_time = [], 0, 0
for _ in range(grad_acc if i >= 2 else 1):
for _ in range(grad_acc):
ist = time.perf_counter()
try: tokens = next(train_iter)
except StopIteration:
stopped = True
break
mst = time.perf_counter()
data_time += mst - ist
losses.append(minibatch(tokens).item())
dev_time += time.perf_counter() - mst
dt = time.perf_counter()
loss = minibatch(tokens)
if stopped: break
gt = time.perf_counter()
ret = optim_step()
lr, grad_norm = ret[0].item(), ret[1].item()
et = time.perf_counter()
lr = optim_step()
ot = time.perf_counter()
loss = sum(losses) / len(losses)
optim_time = et - gt
dev_time += optim_time
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 += actual_gbs
sequences_seen += GBS
mem_gb = GlobalCounters.mem_used / 1e9
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} {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, {grad_norm:.6f} grad_norm, {mem_gb:.2f} GB used, {gflops:9.2f} GFLOPS, {mfu:5.2f}% MFU")
if DEBUG >= 1: tqdm.write(" mem per device: " + ', '.join(f"{dev}: {mem/1e9:.2f} GB" for dev, mem in sorted(GlobalCounters.mem_used_per_device.items())))
f"{lr:.12f} LR, {mem_gb:.2f} GB used, {gflops:9.2f} GFLOPS, {mfu:5.2f}% MFU")
if WANDB:
wandb.log({
"train/loss": loss,
"train/lr": lr,
"train/grad_norm": grad_norm,
"lr": lr, "train/loss": loss,
"train/step_time": step_time,
"train/gbs_time": gbs_time,
"train/optim_time": optim_time,
@@ -1553,7 +1544,7 @@ def train_llama3():
print(f"epoch global_ops: {GlobalCounters.global_ops:_}, "
f"epoch global_mem: {GlobalCounters.global_mem:_}")
if (sequences_seen // EVAL_FREQ != (sequences_seen - actual_gbs) // EVAL_FREQ and (i != 1 or EVAL_FREQ == 1)) or (BENCHMARK and i == BENCHMARK):
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}")
@@ -1561,7 +1552,7 @@ def train_llama3():
# run eval
eval_losses = []
eval_iter = get_eval_iter()
tqdm.write(f"evaluating {EVAL_SAMPLES//EVAL_BS} batches of {EVAL_BS} sequences")
tqdm.write(f"evaluating {5760//EVAL_BS} batches of {EVAL_BS} sequences")
for j,tokens in tqdm(enumerate(eval_iter), total=EVAL_SAMPLES//EVAL_BS):
eval_losses += eval_step(tokens).tolist()
-57
View File
@@ -1,57 +0,0 @@
from tinygrad.tensor import Tensor
from tinygrad.dtype import dtypes
from tinygrad.nn.optim import Optimizer
from tinygrad.helpers import FUSE_OPTIM
class GradAccClipAdamW(Optimizer):
def __init__(self, params:list[Tensor], lr=0.001, b1=0.9, b2=0.999, eps=1e-6, weight_decay=0.0, grad_acc=1, clip_norm=1.0, device=None, fused=FUSE_OPTIM):
super().__init__(params, lr, device, fused)
self.b1, self.b2, self.eps, self.wd = b1, b2, eps, weight_decay
self.b1_t, self.b2_t = (Tensor.ones((1,), dtype=dtypes.float32, device=self.device, requires_grad=False) for _ in [b1, b2])
self.m = self._new_optim_param()
self.v = self._new_optim_param()
self.grad_acc, self.clip_norm = grad_acc, clip_norm
def fstep(self, grads:list[Tensor]):
if self.fused:
out, extra = self._step([], grads)
updates = [out[0][self.pos_params[i]:self.pos_params[i+1]].reshape(tt.shape) for i, tt in enumerate(self.params)]
else:
updates, extra = self._step([], grads)
for i, tt in enumerate(self.params): tt.assign(self._apply_update(tt, updates[i]))
to_realize = extra+self.params+self.buffers
Tensor.realize(*to_realize)
return extra[-1]
def _step(self, params:list[Tensor], grads:list[Tensor]) -> tuple[list[Tensor], list[Tensor]]:
for i in range(len(grads)):
if grads[i].device != self.m[i].device: grads[i].assign(grads[i].to(self.m[i].device))
if self.fused:
grads[0].assign(grads[0] / self.grad_acc)
total_norm = grads[0].float().square().sum().sqrt()
grads[0].assign((grads[0] * (self.clip_norm / (total_norm + 1e-6)).clamp(max_=1.0)).cast(grads[0].dtype))
else:
for i in range(len(grads)):
grads[i].assign(grads[i] / self.grad_acc).realize()
total_norm = Tensor.stack(*[g.float().square().sum() for g in grads]).sum().sqrt().contiguous().realize()
for i in range(len(grads)):
grads[i].assign((grads[i] * (self.clip_norm / (total_norm + 1e-6)).clamp(max_=1.0)).cast(grads[i].dtype)).realize()
ret = []
self.b1_t *= self.b1
self.b2_t *= self.b2
for i, g in enumerate(grads):
self.m[i].assign((self.b1 * self.m[i] + (1.0 - self.b1) * g).cast(self.m[i].dtype))
self.v[i].assign((self.b2 * self.v[i] + (1.0 - self.b2) * (g * g)).cast(self.v[i].dtype))
m_hat = self.m[i] / (1.0 - self.b1_t)
v_hat = self.v[i] / (1.0 - self.b2_t)
up = m_hat / (v_hat.sqrt() + self.eps)
ret.append((self.lr * up).cast(g.dtype))
return ret, [self.b1_t, self.b2_t] + self.m + self.v + [total_norm]
def _apply_update(self, t:Tensor, up:Tensor) -> Tensor:
wd = self.wd if t.ndim >= 2 else 0.0
up = up.shard_like(t) + self.lr.to(t.device) * wd * t.detach()
return t.detach() - up.cast(t.dtype)
@@ -1,36 +0,0 @@
#!/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=${DEBUG:-2}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-0}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-1}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-1} MP=${MP:-8}
export BS=${BS:-1} EVAL_BS=${EVAL_BS:-1} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-2}
export MODEL="llama3"
export BASEDIR="/raid/datasets/c4/"
export LLAMA3_SIZE=${LLAMA3_SIZE:-"405B"}
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 BEAM_PADTO=1
export FAKEDATA=1 BENCHMARK=10
if [ -z "$FULL_LAYERS" ]; then
export LLAMA_LAYERS=2
fi
python3 examples/mlperf/model_train.py
@@ -1,31 +0,0 @@
#!/usr/bin/env bash
export PYTHONPATH="."
export DEV=${DEV:-AMD}
export EMULATE="AMD_CDNA4"
export CHECK_OOB=0
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
export DEBUG=${DEBUG:-0}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-0}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-1}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-1} MP=${MP:-8}
export BS=${BS:-1} EVAL_BS=${EVAL_BS:-1} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-1152}
export MODEL="llama3"
export BASEDIR="/raid/datasets/c4/"
export LLAMA3_SIZE=${LLAMA3_SIZE:-"405B"}
export SEQLEN=${SEQLEN:-8192}
export SEED=${SEED:-$RANDOM}
export DATA_SEED=${DATA_SEED:-5760}
export JITBEAM=${JITBEAM:-3}
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5 BEAM_PADTO=1
python3 examples/mlperf/model_train.py
@@ -5,17 +5,15 @@ export DEV=${DEV:-AMD}
export EMULATE="AMD_CDNA4"
export CHECK_OOB=0
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
export DEVICE_IN_FUNCTION_BUG=1
export DEBUG=${DEBUG:-2}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export FLASH_ATTENTION=${FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-1}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-0}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-8} MP=${MP:-1} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-2}
export DP=${DP:-8} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-1}
export GBS=$((BS * GRADIENT_ACC_STEPS))
export MODEL="llama3"
@@ -23,20 +21,16 @@ export BASEDIR="/raid/datasets/c4-8b/"
export SMALL=1
export LLAMA3_SIZE=${LLAMA3_SIZE:-"8B"}
export EVAL_TARGET=3.3 EVAL_FREQ=12288
export LR="1e-3" END_LR="1e-4" WARMUP_SAMPLES=4096 MAX_STEPS=1200000
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 BEAM_PADTO=1
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
export FAKEDATA=1 BENCHMARK=10
if [ -z "$FULL_LAYERS" ]; then
export LLAMA_LAYERS=2
fi
export FAKEDATA=1 BENCHMARK=10 LLAMA_LAYERS=2
python3 examples/mlperf/model_train.py
@@ -1,43 +0,0 @@
#!/usr/bin/env bash
export PYTHONPATH="."
export DEV=${DEV:-AMD}
export EMULATE="AMD_CDNA4"
export CHECK_OOB=0
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
export DEVICE_IN_FUNCTION_BUG=1
export DEBUG=${DEBUG:-2}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-0}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-1}
export OFFLOAD_OPTIM=${OFFLOAD_OPTIM:-1}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-1} MP=${MP:-8} BS=${BS:-1} EVAL_BS=${EVAL_BS:-1} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-2}
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="1e-3" END_LR="1e-4" WARMUP_SAMPLES=4096 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 BEAM_PADTO=1
export FAKEDATA=1 BENCHMARK=10
if [ -z "$FULL_LAYERS" ]; then
export LLAMA_LAYERS=2
fi
python3 examples/mlperf/model_train.py
@@ -5,17 +5,15 @@ export DEV=${DEV:-AMD}
export EMULATE="AMD_CDNA4"
export CHECK_OOB=0
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
export DEVICE_IN_FUNCTION_BUG=1
export DEBUG=${DEBUG:-0}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export FLASH_ATTENTION=${FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-1}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-0}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-8} MP=${MP:-1} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-4}
export DP=${DP:-8} BS=${BS:-8} EVAL_BS=${EVAL_BS:-8} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-1}
export GBS=$((BS * GRADIENT_ACC_STEPS))
export MODEL="llama3"
@@ -23,15 +21,14 @@ export BASEDIR="/raid/datasets/c4-8b/"
export SMALL=1
export LLAMA3_SIZE=${LLAMA3_SIZE:-"8B"}
export EVAL_TARGET=3.3 EVAL_FREQ=12288
export LR="1e-3" END_LR="1e-4" WARMUP_SAMPLES=4096 MAX_STEPS=1200000
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 SEED=${SEED:-5760}
export JITBEAM=${JITBEAM:-3}
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5 BEAM_PADTO=1
export BEAM_UOPS_MAX=6000 BEAM_UPCAST_MAX=256 BEAM_LOCAL_MAX=1024 BEAM_MIN_PROGRESS=5
python3 examples/mlperf/model_train.py
@@ -1,38 +0,0 @@
#!/usr/bin/env bash
export PYTHONPATH="."
export DEV=${DEV:-AMD}
export EMULATE="AMD_CDNA4"
export CHECK_OOB=0
export REWRITE_STACK_LIMIT=5000000 HCQDEV_WAIT_TIMEOUT_MS=240000
export DEVICE_IN_FUNCTION_BUG=1
export DEBUG=${DEBUG:-0}
export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
export ALL2ALL=${ALL2ALL:-1}
export USE_ATOMICS=${USE_ATOMICS:-0}
export ASM_GEMM=${ASM_GEMM:-1}
export WQKV=${WQKV:-1}
export OFFLOAD_OPTIM=${OFFLOAD_OPTIM:-1}
export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
export DP=${DP:-1} MP=${MP:-8} BS=${BS:-1} EVAL_BS=${EVAL_BS:-1} GRADIENT_ACC_STEPS=${GRADIENT_ACC_STEPS:-32}
export GBS=$((BS * GRADIENT_ACC_STEPS))
export MODEL="llama3"
export BASEDIR="/raid/datasets/c4-8b/"
export SMALL=1
export LLAMA3_SIZE=${LLAMA3_SIZE:-"8B"}
export EVAL_TARGET=3.3 EVAL_FREQ=12288
export LR="1e-3" END_LR="1e-4" WARMUP_SAMPLES=4096 MAX_STEPS=1200000
export WARMUP_STEPS=$((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 BEAM_PADTO=1
python3 examples/mlperf/model_train.py
@@ -3,4 +3,4 @@ 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
extra/viz/cli.py --profile --device "AMD" --top 20
PYTHONPATH="." extra/viz/cli.py --profile --device "AMD" --top 20
+1 -1
View File
@@ -31,7 +31,7 @@ def compile(onnx_file):
for i in range(3):
GlobalCounters.reset()
print(f"run {i}")
with Context(DEBUG=max(DEBUG.value, 2 if i == 2 else 1), OPENPILOT_HACKS=1):
with Context(DEBUG=max(DEBUG.value, 2 if i == 2 else 1)):
ret = run_onnx_jit(**inputs).numpy()
# copy i == 1 so use of JITBEAM is okay
if i == 1: test_val = np.copy(ret)
-16
View File
@@ -1,16 +0,0 @@
import sys, pickle
from extra.bench_log import WallTimeEvent, BenchEvent
from tinygrad.helpers import getenv
PKL = sys.argv[1] if len(sys.argv) > 1 else "/tmp/openpilot.pkl"
load_times = []
for _ in range(10):
with WallTimeEvent(BenchEvent.STEP) as wte: pickle.load(open(PKL, 'rb'))
load_times.append(wte.time)
print(f"pickle load: {wte.time:6.2f} s")
if (assert_time:=getenv("ASSERT_MIN_LOAD_TIME")):
min_time = min(load_times)
assert min_time < assert_time, f"Speed regression, expected min load time of < {assert_time} s but took: {min_time} s"
+6 -5
View File
@@ -154,7 +154,7 @@ class SMICtx:
for dev in self.devs:
match dev.ip_ver[am.MP1_HWIP]:
case (13,0,6): table_t = dev.smu.smu_mod.MetricsTableV0_t
case (13,0,12): table_t = dev.smu.smu_mod.MetricsTable_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
@@ -231,11 +231,12 @@ class SMICtx:
def get_power(self, dev, metrics):
match dev.ip_ver[am.MP1_HWIP]:
case (13,0,6): return self._smuq10_round(metrics.SocketPower), self._smuq10_round(metrics.MaxSocketPowerLimit)
case (13,0,12): return self._smuq10_round(metrics.SocketPower), self._smuq10_round(metrics.SocketPowerLimit)
case (13,0,6)|(13,0,12): return self._smuq10_round(metrics.SocketPower), self._smuq10_round(metrics.MaxSocketPowerLimit)
case _: return metrics.SmuMetrics.AverageSocketPower, metrics.SmuMetrics.dGPU_W_MAX
def get_mem_usage(self, dev):
return 0
usage = 0
pt_stack = [dev.mm.root_page_table]
while len(pt_stack) > 0:
@@ -244,8 +245,8 @@ class SMICtx:
entry = pt.entries[i]
if (entry & am.AMDGPU_PTE_VALID) == 0: continue
if pt.lv < am.AMDGPU_VM_PDB0 and not dev.gmc.is_pte_huge_page(pt.lv, entry):
pt_stack.append(AMPageTableEntry(dev, dev.xgmi2paddr(entry & 0x0000FFFFFFFFF000), lv=pt.lv+1))
if pt.lv!=am.AMDGPU_VM_PTB and not dev.gmc.is_pte_huge_page(pt.lv, entry):
pt_stack.append(AMPageTableEntry(dev, entry & 0x0000FFFFFFFFF000, lv=pt.lv+1))
continue
if (entry & am.AMDGPU_PTE_SYSTEM) != 0: continue
usage += (1 << ((9 * (3-pt.lv)) + 12))
@@ -1,17 +1,17 @@
An integrated environment for AMD GPU assembly and emulation
Test with `pytest -n12 test/amd/`
`AMD_LLVM=1 pytest -n12 test/amd/`
Test with `PYTHONPATH="." pytest -n12 extra/assembly/amd/`
`AMD_LLVM=1 PYTHONPATH="." pytest -n12 extra/assembly/amd/`
* pdf.py -- extract assembly format + instruction pseudocode from AMD PDF
* dsl.py -- helpers for the autogen instruction classes in `__init__.py`. should be standalone with init
* test/mockgpu/amd/emu.py -- an emulator for RDNA that runs in tinygrad with `AMD=1 MOCKGPU=1 PYTHON_REMU=1`
* generate.py -- extract assembly format + instruction pseudocode from AMD XML + PDF
* test/mockgpu/amd/pcode.py -- pseudocode to UOp transformation
* sqtt.py -- SQTT parser
* pcode.py -- pseudocode execution environment. pseudocode should be transformed as little as possible.
* asm.py -- an asm/disasm function to transform to and from AMD assembly syntax
* emu.py -- an emulator for RDNA that runs in tinygrad with `AMD=1 MOCKGPU=1 PYTHON_REMU=1`
The code should be as readable and deduplicated as possible. emu (in test/mockgpu/amd/) shouldn't be required for dsl.
The code should be as readable and deduplicated as possible. asm and emu shouldn't be required for dsl.
The autogen folder is autogenerated from the AMD PDFs with `python3 -m tinygrad.renderer.amd.pdf --arch all`
The autogen folder is autogenerated from the AMD PDFs with `python3 -m extra.assembly.amd.pdf --arch all`
test_emu.py has a good set of instruction tests for the emulation, with USE_HW=1 it will compare to real hardware.
Whenever an instruction is fixed, regression tests should be added here and confirmed with real hardware.
@@ -20,20 +20,20 @@ test_llvm.py tests asm/disasm on the LLVM tests, confirming it behaves the same
tinygrad's dtype tests should pass with and without LLVM. they run in about 12 seconds.
`AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=12 test/backend/test_dtype_alu.py test/backend/test_dtype.py`
`AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=1 pytest -n=12 test/backend/test_dtype_alu.py test/backend/test_dtype.py`
`PYTHONPATH="." AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=12 test/test_dtype_alu.py test/test_dtype.py`
`PYTHONPATH="." AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=1 pytest -n=12 test/test_dtype_alu.py test/test_dtype.py`
The ops tests also pass, but they are very slow, so you should run them one at a time.
`SKIP_SLOW_TEST=1 AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=12 test/backend/test_ops.py`
`SKIP_SLOW_TEST=1 AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=1 pytest -n=12 test/backend/test_ops.py`
`SKIP_SLOW_TEST=1 PYTHONPATH="." AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=0 pytest -n=12 test/test_ops.py`
`SKIP_SLOW_TEST=1 PYTHONPATH="." AMD=1 PYTHON_REMU=1 MOCKGPU=1 AMD_LLVM=1 pytest -n=12 test/test_ops.py`
When something is caught by main tinygrad tests, a local regression test should be added to `test/amd`.
When something is caught by main tinygrad tests, a local regression test should be added to `extra/assembly/amd/test`.
While working with tinygrad, you can dump the assembly with `DEBUG=7`. These tests all pass on real hardware
If a test is failing with `AMD=1 PYTHON_REMU=1 MOCKGPU=1` it's because an instruction is emulated incorrectly.
You can test without `MOCKGPU=1` to test on real hardware, if it works on real hardware there's a bug in the emulator.
IMPORTANT: if a test is failing in the emulator, it's an instruction bug. Use DEBUG=7, get the instructions, and debug.
Currently, only RDNA3 is well supported, but when finished, this will support RDNA3+RDNA4+CDNA in ~3000 lines.
Get line count with `cloc --by-file tinygrad/renderer/amd/*.py`
Currently, only RDNA3 is well supported, but when finished, this will support RDNA3+RDNA4+CDNA in ~2000 lines.
Get line count with `cloc --by-file extra/assembly/amd/*.py`
+67
View File
@@ -0,0 +1,67 @@
# Instruction format detection and decoding
from __future__ import annotations
from extra.assembly.amd.dsl import Inst, FixedBitField, EnumBitField
# SDWA/DPP variant detection: src0 field (bits 0-8) encodes the variant
# 0xf9 (249) = SDWA, 0xfa (250) = DPP16 for CDNA (GFX9)
_VARIANT_SRC0 = {"_SDWA_SDST": 0xf9, "_SDWA": 0xf9, "_DPP16": 0xfa}
def _matches(data: bytes, cls: type[Inst]) -> bool:
"""Check if data matches all FixedBitFields and op is in allowed."""
for _, field in cls._fields:
dword_idx = field.lo // 32
if len(data) < (dword_idx + 1) * 4: return False
word = int.from_bytes(data[dword_idx*4:(dword_idx+1)*4], 'little')
field_lo = field.lo % 32
if isinstance(field, FixedBitField):
if ((word >> field_lo) & field.mask) != field.default: return False
if isinstance(field, EnumBitField) and field.allowed is not None:
try: opcode = field.decode((word >> field_lo) & field.mask)
except ValueError: return False # opcode not in enum
if opcode not in field.allowed: return False
# Check SDWA/DPP variant based on src0 field (bits 0-8) - only for variant classes
name = cls.__name__
word = int.from_bytes(data[:4], 'little')
for suffix, expected_src0 in _VARIANT_SRC0.items():
if name.endswith(suffix): return (word & 0x1ff) == expected_src0
return True
# Import instruction classes for each architecture
from extra.assembly.amd.autogen.rdna3.ins import (VOP1, VOP1_SDST, VOP1_LIT, VOP2, VOP2_LIT, VOP3, VOP3_SDST, VOP3SD, VOP3P, VOPC, VOPD, VINTERP,
SOP1, SOP1_LIT, SOP2, SOP2_LIT, SOPC, SOPK, SOPK_LIT, SOPP, SMEM, DS, FLAT, GLOBAL, SCRATCH)
from extra.assembly.amd.autogen.rdna4.ins import (VOP1 as R4_VOP1, VOP1_SDST as R4_VOP1_SDST, VOP1_LIT as R4_VOP1_LIT,
VOP2 as R4_VOP2, VOP2_LIT as R4_VOP2_LIT, 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, SOP1_LIT as R4_SOP1_LIT,
SOP2 as R4_SOP2, SOP2_LIT as R4_SOP2_LIT, SOPC as R4_SOPC, SOPC_LIT as R4_SOPC_LIT,
SOPK as R4_SOPK, SOPK_LIT as R4_SOPK_LIT, SOPP as R4_SOPP,
SMEM as R4_SMEM, DS as R4_DS, VFLAT as R4_FLAT, VGLOBAL as R4_GLOBAL, VSCRATCH as R4_SCRATCH)
from extra.assembly.amd.autogen.cdna.ins import (VOP1 as C_VOP1, VOP1_SDWA as C_VOP1_SDWA, VOP1_DPP16 as C_VOP1_DPP16,
VOP2 as C_VOP2, VOP2_LIT as C_VOP2_LIT, VOP2_SDWA as C_VOP2_SDWA, VOP2_DPP16 as C_VOP2_DPP16,
VOPC as C_VOPC, VOPC_SDWA_SDST as C_VOPC_SDWA_SDST,
VOP3 as C_VOP3, VOP3_SDST as C_VOP3_SDST, VOP3SD as C_VOP3SD, VOP3P as C_VOP3P, VOP3P_MFMA as C_VOP3P_MFMA, VOP3PX2 as C_VOP3PX2,
SOP1 as C_SOP1, SOP2 as C_SOP2, SOPC as C_SOPC, SOPK as C_SOPK, SOPK_LIT as C_SOPK_LIT, SOPP as C_SOPP, SMEM as C_SMEM, DS as C_DS,
FLAT as C_FLAT, GLOBAL as C_GLOBAL, SCRATCH as C_SCRATCH, MUBUF as C_MUBUF)
# Order matters: more specific encodings first, catch-alls (SOP2, VOP2) last
# Order: base before _LIT (base matches regular ops, _LIT catches lit-only ops excluded from base)
_FORMATS = {
"rdna3": [VOPD, VOP3P, VINTERP, VOP3SD, VOP3_SDST, VOP3, DS, GLOBAL, SCRATCH, FLAT, SMEM,
SOP1, SOP1_LIT, SOP2, SOP2_LIT, SOPC, SOPK, SOPK_LIT, SOPP, VOPC, VOP1_SDST, VOP1, VOP1_LIT, VOP2, VOP2_LIT],
"rdna4": [R4_VOPD, R4_VOP3P, R4_VINTERP, R4_VOP3SD, R4_VOP3_SDST, R4_VOP3, R4_DS, R4_GLOBAL, R4_SCRATCH, R4_FLAT, R4_SMEM,
R4_SOP1, R4_SOP1_LIT, R4_SOPC, R4_SOPC_LIT, R4_SOPP, R4_SOPK, R4_SOPK_LIT, R4_VOPC, R4_VOP1_SDST, R4_VOP1, R4_VOP1_LIT,
R4_SOP2, R4_SOP2_LIT, R4_VOP2, R4_VOP2_LIT],
"cdna": [C_VOP3PX2, C_VOP3P_MFMA, C_VOP3P, C_VOP3SD, C_VOP3_SDST, C_VOP3, C_DS, C_GLOBAL, C_SCRATCH, C_FLAT, C_MUBUF, C_SMEM,
C_SOP1, C_SOPC, C_SOPP, C_SOPK, C_SOPK_LIT, C_VOPC_SDWA_SDST, C_VOPC,
C_VOP1_DPP16, C_VOP1_SDWA, C_VOP1, C_VOP2_DPP16, C_VOP2_SDWA, C_SOP2, C_VOP2, C_VOP2_LIT],
}
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)}"
for cls in _FORMATS[arch]:
if _matches(data, cls): return cls
raise ValueError(f"unknown {arch} format word={int.from_bytes(data[:4], 'little'):#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)
@@ -1,5 +1,5 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
from extra.assembly.amd.autogen.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
class DSOp(ReprEnum):
DS_ADD_U32 = 0
@@ -1,7 +1,7 @@
# autogenerated from AMD ISA XML - do not edit
# ruff: noqa: E501,F401
from tinygrad.renderer.amd.dsl import BitField, DPP, DPP16, EXEC, EXECZ, EXEC_HI, EXEC_LO, EnumBitField, FixedBitField, INV_2PI, Inst, LIT, M0, NULL, OFF, SBaseField, SCC, SDWA, SGPRField, SRC_LDS_DIRECT, SRsrcField, SSrcField, SrcField, VCC, VCCZ, VCC_HI, VCC_LO, VGPRField, s, src, ttmp, v
from tinygrad.runtime.autogen.amd.cdna.enum import DSOp, FLATOp, GLOBALOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3PX2Op, VOP3SDOp, VOPCOp, HWREG
# ruff: noqa: F401,F403
from extra.assembly.amd.dsl import *
from extra.assembly.amd.autogen.cdna.enum import *
import functools
class DS(Inst):
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import Fmt, OpType
from tinygrad.runtime.autogen.amd.cdna.enum import DSOp, FLATOp, GLOBALOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3PX2Op, VOP3SDOp, VOPCOp
from extra.assembly.amd.autogen.common import Fmt, OpType
from extra.assembly.amd.autogen.cdna.enum import *
# instruction operand info: {Op: {field: (Fmt, size_bits, OpType)}}
OPERANDS = {
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA PDF - do not edit
# ruff: noqa: E501
from tinygrad.runtime.autogen.amd.cdna.enum import DSOp, FLATOp, GLOBALOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp
from extra.assembly.amd.autogen.cdna.enum import DSOp, FLATOp, GLOBALOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp
PCODE = {
DSOp.DS_ADD_U32: 'addr = CalcDsAddr(ADDR.b32, OFFSET0.b32, OFFSET1.b32);\ntmp = MEM[addr].u32;\nMEM[addr].u32 += DATA.u32;\nRETURN_DATA.u32 = tmp',
@@ -1,5 +1,5 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
from extra.assembly.amd.autogen.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
class DSOp(ReprEnum):
DS_ADD_U32 = 0
@@ -1,7 +1,7 @@
# autogenerated from AMD ISA XML - do not edit
# ruff: noqa: E501,F401
from tinygrad.renderer.amd.dsl import BitField, DPP, DPP16, EXEC, EXECZ, EXEC_HI, EXEC_LO, EnumBitField, FixedBitField, INV_2PI, Inst, LIT, M0, NULL, OFF, SBaseField, SCC, SDWA, SGPRField, SRC_LDS_DIRECT, SRsrcField, SSrcField, SrcField, VCC, VCCZ, VCC_HI, VCC_LO, VDSTYField, VGPRField, s, src, ttmp, v
from tinygrad.runtime.autogen.amd.rdna3.enum import DSOp, EXPOp, FLATOp, GLOBALOp, LDSDIROp, MIMGOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp, HWREG, MSG
# ruff: noqa: F401,F403
from extra.assembly.amd.dsl import *
from extra.assembly.amd.autogen.rdna3.enum import *
import functools
class DS(Inst):
@@ -593,6 +593,9 @@ flat_load_d16_hi_i8 = functools.partial(FLAT, FLATOp.FLAT_LOAD_D16_HI_I8)
flat_load_d16_hi_b16 = functools.partial(FLAT, FLATOp.FLAT_LOAD_D16_HI_B16)
flat_store_d16_hi_b8 = functools.partial(FLAT, FLATOp.FLAT_STORE_D16_HI_B8)
flat_store_d16_hi_b16 = functools.partial(FLAT, FLATOp.FLAT_STORE_D16_HI_B16)
global_load_addtid_b32 = functools.partial(FLAT, FLATOp.GLOBAL_LOAD_ADDTID_B32)
global_store_addtid_b32 = functools.partial(FLAT, FLATOp.GLOBAL_STORE_ADDTID_B32)
global_load_lds_addtid_b32 = functools.partial(FLAT, FLATOp.GLOBAL_LOAD_LDS_ADDTID_B32)
flat_atomic_swap_b32 = functools.partial(FLAT, FLATOp.FLAT_ATOMIC_SWAP_B32)
flat_atomic_cmpswap_b32 = functools.partial(FLAT, FLATOp.FLAT_ATOMIC_CMPSWAP_B32)
flat_atomic_add_u32 = functools.partial(FLAT, FLATOp.FLAT_ATOMIC_ADD_U32)
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import Fmt, OpType
from tinygrad.runtime.autogen.amd.rdna3.enum import DSOp, EXPOp, FLATOp, GLOBALOp, LDSDIROp, MIMGOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp
from extra.assembly.amd.autogen.common import Fmt, OpType
from extra.assembly.amd.autogen.rdna3.enum import *
# instruction operand info: {Op: {field: (Fmt, size_bits, OpType)}}
OPERANDS = {
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA PDF - do not edit
# ruff: noqa: E501
from tinygrad.runtime.autogen.amd.rdna3.enum import DSOp, FLATOp, GLOBALOp, LDSDIROp, MIMGOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp
from extra.assembly.amd.autogen.rdna3.enum import DSOp, FLATOp, GLOBALOp, LDSDIROp, MIMGOp, MTBUFOp, MUBUFOp, SCRATCHOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp
PCODE = {
DSOp.DS_ADD_U32: 'tmp = MEM[ADDR].u32;\nMEM[ADDR].u32 += DATA.u32;\nRETURN_DATA.u32 = tmp',
@@ -1,5 +1,5 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
from extra.assembly.amd.autogen.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401
class DSOp(ReprEnum):
DS_ADD_U32 = 0
@@ -1,7 +1,7 @@
# autogenerated from AMD ISA XML - do not edit
# ruff: noqa: E501,F401
from tinygrad.renderer.amd.dsl import BitField, DPP, DPP16, EXEC, EXECZ, EXEC_HI, EXEC_LO, EnumBitField, FixedBitField, INV_2PI, Inst, LIT, M0, NULL, OFF, SBaseField, SCC, SDWA, SGPRField, SRC_LDS_DIRECT, SSrcField, SrcField, VCC, VCCZ, VCC_HI, VCC_LO, VDSTYField, VGPRField, s, src, ttmp, v
from tinygrad.runtime.autogen.amd.rdna4.enum import DSOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VBUFFEROp, VDSDIROp, VEXPORTOp, VFLATOp, VGLOBALOp, VIMAGEOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp, VSAMPLEOp, VSCRATCHOp, HWREG, MSG
# ruff: noqa: F401,F403
from extra.assembly.amd.dsl import *
from extra.assembly.amd.autogen.rdna4.enum import *
import functools
class DS(Inst):
@@ -973,6 +973,8 @@ flat_load_d16_hi_i8 = functools.partial(VFLAT, VFLATOp.FLAT_LOAD_D16_HI_I8)
flat_load_d16_hi_b16 = functools.partial(VFLAT, VFLATOp.FLAT_LOAD_D16_HI_B16)
flat_store_d16_hi_b8 = functools.partial(VFLAT, VFLATOp.FLAT_STORE_D16_HI_B8)
flat_store_d16_hi_b16 = functools.partial(VFLAT, VFLATOp.FLAT_STORE_D16_HI_B16)
global_load_addtid_b32 = functools.partial(VFLAT, VFLATOp.GLOBAL_LOAD_ADDTID_B32)
global_store_addtid_b32 = functools.partial(VFLAT, VFLATOp.GLOBAL_STORE_ADDTID_B32)
flat_atomic_swap_b32 = functools.partial(VFLAT, VFLATOp.FLAT_ATOMIC_SWAP_B32)
flat_atomic_cmpswap_b32 = functools.partial(VFLAT, VFLATOp.FLAT_ATOMIC_CMPSWAP_B32)
flat_atomic_add_u32 = functools.partial(VFLAT, VFLATOp.FLAT_ATOMIC_ADD_U32)
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA XML - do not edit
from tinygrad.runtime.autogen.amd.common import Fmt, OpType
from tinygrad.runtime.autogen.amd.rdna4.enum import DSOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VBUFFEROp, VDSDIROp, VEXPORTOp, VFLATOp, VGLOBALOp, VIMAGEOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp, VSAMPLEOp, VSCRATCHOp
from extra.assembly.amd.autogen.common import Fmt, OpType
from extra.assembly.amd.autogen.rdna4.enum import *
# instruction operand info: {Op: {field: (Fmt, size_bits, OpType)}}
OPERANDS = {
@@ -1,6 +1,6 @@
# autogenerated from AMD ISA PDF - do not edit
# ruff: noqa: E501
from tinygrad.runtime.autogen.amd.rdna4.enum import DSOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VBUFFEROp, VFLATOp, VGLOBALOp, VIMAGEOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp, VSAMPLEOp, VSCRATCHOp
from extra.assembly.amd.autogen.rdna4.enum import DSOp, SMEMOp, SOP1Op, SOP2Op, SOPCOp, SOPKOp, SOPPOp, VBUFFEROp, VFLATOp, VGLOBALOp, VIMAGEOp, VINTERPOp, VOP1Op, VOP2Op, VOP3Op, VOP3POp, VOP3SDOp, VOPCOp, VOPDOp, VSAMPLEOp, VSCRATCHOp
PCODE = {
DSOp.DS_ADD_U32: 'addr = CalcDsAddr(vgpr_a.b32, offset.b32);\ntmp = MEM[addr].u32;\nMEM[addr].u32 += DATA.u32;\nRETURN_DATA.u32 = tmp',
@@ -1,16 +1,14 @@
# RDNA3/RDNA4/CDNA disassembler
from __future__ import annotations
import re
import re, struct
from typing import Callable
from tinygrad.renderer.amd.dsl import Inst, Reg
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'}
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: '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',
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',
251: 'src_vccz', 252: 'src_execz'}
SPECIAL_PAIRS = {106: 'vcc', 126: 'exec'}
@@ -72,26 +70,23 @@ def _num_srcs(inst) -> int:
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
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
# ═══════════════════════════════════════════════════════════════════════════════
# IMPORTS
# ═══════════════════════════════════════════════════════════════════════════════
from tinygrad.runtime.autogen.amd.rdna3.ins import (VOP1, VOP1_SDST, VOP1_SDST_LIT, VOP1_LIT, VOP2, VOP2_LIT, VOP3, VOP3_SDST, VOP3_SDST_LIT,
from extra.assembly.amd.autogen.rdna3.ins import (VOP1, VOP1_SDST, VOP1_SDST_LIT, VOP1_LIT, VOP2, VOP2_LIT, VOP3, VOP3_SDST, VOP3_SDST_LIT,
VOP3_LIT, VOP3SD, VOP3SD_LIT, VOP3P, VOP3P_LIT, VOPC, VOPC_LIT, VOPD, VOPD_LIT, VINTERP, SOP1, SOP1_LIT, SOP2, SOP2_LIT, SOPC, SOPC_LIT,
SOPK, SOPK_LIT, SOPP, SMEM, DS, FLAT, GLOBAL, SCRATCH, VOP2Op, VOPDOp, SOPPOp, HWREG, MSG)
from tinygrad.runtime.autogen.amd.rdna4.ins import (VOP1 as R4_VOP1, VOP1_SDST as R4_VOP1_SDST,
VOP1_SDST_LIT as R4_VOP1_SDST_LIT, VOP1_LIT as R4_VOP1_LIT,
from extra.assembly.amd.autogen.rdna4.ins import (VOP1 as R4_VOP1, VOP1_SDST as R4_VOP1_SDST, VOP1_SDST_LIT as R4_VOP1_SDST_LIT, VOP1_LIT as R4_VOP1_LIT,
VOP2 as R4_VOP2, VOP2_LIT as R4_VOP2_LIT, VOP3 as R4_VOP3, VOP3_SDST as R4_VOP3_SDST, VOP3_SDST_LIT as R4_VOP3_SDST_LIT, VOP3_LIT as R4_VOP3_LIT,
VOP3SD as R4_VOP3SD, VOP3SD_LIT as R4_VOP3SD_LIT, VOP3P as R4_VOP3P, VOP3P_LIT as R4_VOP3P_LIT, VOPC as R4_VOPC, VOPC_LIT as R4_VOPC_LIT,
VOPD as R4_VOPD, VOPD_LIT as R4_VOPD_LIT, VINTERP as R4_VINTERP, SOP1 as R4_SOP1, SOP1_LIT as R4_SOP1_LIT, SOP2 as R4_SOP2, SOP2_LIT as R4_SOP2_LIT,
SOPC as R4_SOPC, SOPC_LIT as R4_SOPC_LIT, SOPK as R4_SOPK, SOPK_LIT as R4_SOPK_LIT, SOPP as R4_SOPP, SMEM as R4_SMEM, DS as R4_DS,
VOPDOp as R4_VOPDOp, HWREG as HWREG_RDNA4, VFLAT as R4_FLAT, VGLOBAL as R4_GLOBAL, VSCRATCH as R4_SCRATCH)
from tinygrad.runtime.autogen.amd.cdna.ins import HWREG as HWREG_CDNA
from extra.assembly.amd.autogen.cdna.ins import FLAT as C_FLAT, HWREG as HWREG_CDNA
def _is_cdna(inst: Inst) -> bool: return 'cdna' in inst.__class__.__module__
def _is_r4(inst: Inst) -> bool: return 'rdna4' in inst.__class__.__module__
@@ -105,15 +100,9 @@ _CDNA_DISASM_ALIASES = {'v_fmac_f64': 'v_mul_legacy_f32', 'v_dot2c_f32_bf16': 'v
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 | None:
b = _unwrap(b)
return _reg("ttmp", b - 108, n) if 108 <= b <= 123 else None
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 | None: b = _unwrap(b); return _reg("ttmp", b - 108, n) if 108 <= b <= 123 else None
def _fmt_sdst(v, n: int = 1, cdna: bool = False) -> str:
v = _unwrap(v)
@@ -141,9 +130,7 @@ def _fmt_v16(v, base: int = 256, hi_thresh: int = 384) -> str:
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 _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))}]"
@@ -214,8 +201,7 @@ def _disasm_vop2(inst: VOP2) -> str:
basename = name.replace('_e32', '')
if cdna and basename in _VOP2_CARRY_OUT: return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}"
if cdna and basename in _VOP2_CARRY_INOUT: return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}, {vcc}"
if not cdna and basename in _VOP2_CARRY_INOUT_RDNA:
return f"{name}{suf} {inst.vdst.fmt()}, {vcc}, {_lit(inst, inst.src0)}, {inst.vsrc1.fmt()}, {vcc}"
if not cdna and basename 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)
@@ -231,10 +217,7 @@ def _disasm_vopc(inst: VOPC) -> str:
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
if inst.src0.offset == 255: s0 = _lit(inst, inst.src0)
elif inst.src0.sz > 1: s0 = inst.src0.fmt()
elif is16: s0 = _src16(inst, inst.src0.offset)
else: s0 = _lit(inst, inst.src0)
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}"
@@ -270,11 +253,10 @@ def _disasm_sopp(inst: SOPP) -> str:
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']
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
def dep(v): return deps[v-1] if 0 < v <= len(deps) else str(v)
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} {inst.simm16}"
@@ -285,7 +267,7 @@ def _disasm_smem(inst: SMEM) -> str:
if name in ('s_gl1_inv', 's_dcache_inv', 's_dcache_inv_vol', 's_dcache_wb', 's_dcache_wb_vol', 's_icache_inv'): return name
soe, imm = getattr(inst, 'soe', 0) or getattr(inst, 'soffset_en', 0), getattr(inst, 'imm', 1)
is_rdna4 = _is_r4(inst)
offset = inst.ioffset if is_rdna4 else getattr(inst, 'offset', 0) # type: ignore[attr-defined]
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}"
@@ -296,9 +278,7 @@ def _disasm_smem(inst: SMEM) -> str:
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
if sbase_count == 2: sbase_str = _fmt_src(sbase_idx, sbase_count, cdna)
elif sbase_idx <= 105: sbase_str = _sreg(sbase_idx, sbase_count)
else: sbase_str = _reg("ttmp", sbase_idx - 108, sbase_count)
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))
@@ -324,12 +304,6 @@ def _disasm_smem(inst: SMEM) -> str:
if name in ('s_memrealtime', 's_memtime'): return f"{name} {_fmt_sdst(inst.sdata, dst_n, cdna)}"
return f"{name} {_fmt_sdst(inst.sdata, dst_n, cdna)}, {sbase_str}, {off_s}" + _mods((inst.glc, " glc"), (getattr(inst, 'dlc', 0), " dlc"))
R4_TH_LOAD = {1: 'TH_LOAD_NT', 2: 'TH_LOAD_HT', 3: 'TH_LOAD_LU', 4: 'TH_LOAD_RT_WB', 5: 'TH_LOAD_NT_WB'}
R4_TH_STORE = {1: 'TH_STORE_NT', 2: 'TH_STORE_HT', 3: 'TH_STORE_ST', 4: 'TH_STORE_RT_WB', 5: 'TH_STORE_NT_WB'}
R4_TH_ATOMIC = {1: 'TH_ATOMIC_RETURN', 2: 'TH_ATOMIC_NT', 3: 'TH_ATOMIC_RETURN_NT',
4: 'TH_ATOMIC_CASCADE_RT', 5: 'TH_ATOMIC_CASCADE_RETURN', 6: 'TH_ATOMIC_CASCADE_NT', 7: 'TH_ATOMIC_CASCADE_RETURN_NT'}
R4_SCOPE = {1: 'SCOPE_SE', 2: 'SCOPE_DEV', 3: 'SCOPE_SYS'}
def _disasm_flat(inst: FLAT) -> str:
name, cdna, r4 = inst.op_name.lower(), _is_cdna(inst), _is_r4(inst)
acc = getattr(inst, 'acc', 0)
@@ -337,10 +311,9 @@ def _disasm_flat(inst: FLAT) -> str:
if r4: seg = 'flat' if (cls_name:=inst.__class__.__name__) == 'VFLAT' else ('global' if cls_name == 'VGLOBAL' else 'scratch')
else: seg = ['flat', 'scratch', 'global'][inst.seg] if inst.seg < 3 else 'flat'
instr = f"{seg}_{name.split('_', 1)[1] if '_' in name else name}"
# Global/scratch uses 13-bit signed offset (RDNA3/CDNA), 24-bit signed offset (RDNA4)
offset = inst.ioffset if r4 else inst.offset # type: ignore[attr-defined]
if r4: off_val = offset if offset < (1 << 23) else offset - (1 << 24) # sign extend 24-bit
elif seg != 'flat':
# Global/scratch uses 13-bit signed offset
offset = inst.ioffset if r4 else inst.offset
if seg != 'flat':
if cdna:
# CDNA: bit 12 is sign bit but not in offset field
raw = int.from_bytes(inst.to_bytes(), 'little')
@@ -354,22 +327,19 @@ def _disasm_flat(inst: FLAT) -> str:
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}{' sc0' if inst.sc0 else ''}{' nt' if inst.nt else ''}{' sc1' if getattr(inst, 'sc1', 0) else ''}" # type: ignore[attr-defined]
elif r4:
th_names = R4_TH_ATOMIC if 'atomic' in name else (R4_TH_STORE if 'store' in name else R4_TH_LOAD)
mods = off_s + (f" th:{th_names[inst.th]}" if inst.th in th_names else "") + (f" scope:{R4_SCOPE[inst.scope]}" if inst.scope in R4_SCOPE else "")
if cdna: mods = f"{off_s}{' sc0' if inst.sc0 else ''}{' nt' if inst.nt else ''}{' sc1' if getattr(inst, 'sc1', 0) else ''}"
elif r4: mods = f"{off_s}{' scope' if inst.scope else ''}{' th' if inst.th else ''}"
else: mods = f"{off_s}{' glc' if inst.glc else ''}{' slc' if inst.slc else ''}{' dlc' if inst.dlc else ''}"
if seg == 'flat': saddr_s = ""
elif _unwrap(inst.saddr) in (0x7F, 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 _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.vsrc if r4 else inst.data) if 'store' in name else inst.vdst)}{saddr_s}{mods}"
# RDNA4: vaddr instead of addr, vsrc instead of data
addr = inst.vaddr if r4 else inst.addr # type: ignore[attr-defined]
data = inst.vsrc if r4 else inst.data # type: ignore[attr-defined]
if 'addtid' in name: return f"{instr} {reg_fn(inst.data if 'store' in name else inst.vdst)}{saddr_s}{mods}"
# RDNA4: vaddr instead of addr, vsrc instead of data
addr = inst.vaddr if r4 else inst.addr
data = inst.vsrc if r4 else inst.data
# load_lds_* instructions: vaddr, saddr (no vdst, data goes to LDS)
if 'load_lds' in name:
addr_w = 1 if seg == 'scratch' or (_unwrap(inst.saddr) not in (0x7F, 124)) else 2
@@ -381,14 +351,13 @@ def _disasm_flat(inst: FLAT) -> str:
addr_s = "off" if not inst.sve and seg == 'scratch' else _vreg(addr, addr_w)
data_s, vdst_s = reg_fn(data, w), reg_fn(inst.vdst, w // 2 if 'cmpswap' in name else w)
if 'atomic' in name:
glc_or_sc0 = inst.sc0 if cdna else (inst.th & 1 if r4 else inst.glc) # type: ignore[attr-defined]
sfx = f"{saddr_s if seg != 'flat' else ''}{mods}"
return f"{instr} {vdst_s}, {addr_s}, {data_s}{sfx}" if glc_or_sc0 else f"{instr} {addr_s}, {data_s}{sfx}"
glc_or_sc0 = inst.sc0 if cdna else inst.glc
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:
name = inst.op_name.lower()
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 ""
@@ -417,8 +386,7 @@ def _disasm_ds(inst: DS) -> str:
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 'xchg2' in name: return f"{name} {reg_fn(inst.vdst, regs.get('d', 1))}, {addr}, {d0}, {d1}{off2}{gds}"
if 'load' in name or ('read' in name and 'read2' not in name):
return f"{name} {reg_fn(inst.vdst)}{off}{gds}" if 'addtid' in name else f"{name} {dst}, {addr}{off}{gds}"
if 'load' in name or ('read' in name and 'read2' not 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 or 'write' in name) and not _has(name, 'cmp', 'xchg', 'write2'):
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}"
@@ -429,15 +397,13 @@ def _disasm_ds(inst: DS) -> str:
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:
name = inst.op_name.lower()
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_'):
s0v = _unwrap(inst.src0)
if s0v == 255: src = _lit(inst, inst.src0)
elif s0v == 253: src = "src_scc"
else: src = _fmt_src(inst.src0, max(1, bits['s0'] // 32))
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)
@@ -446,6 +412,7 @@ def _disasm_vop3(inst: VOP3) -> str:
# 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)
@@ -461,8 +428,7 @@ def _disasm_vop3(inst: VOP3) -> str:
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)))
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
@@ -512,7 +478,7 @@ def _disasm_vopd(inst: VOPD) -> str:
def _disasm_vop3p(inst: VOP3P) -> str:
name = inst.op_name.lower()
is_swmmac, n, is_fma_mix = 'swmmac' in name, inst.num_srcs() or 2, 'fma_mix' in name
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()
@@ -521,22 +487,18 @@ def _disasm_vop3p(inst: VOP3P) -> str:
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 []))
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 []))
mod_s = ' ' + ' '.join(mods) if mods else ''
return f"{name} {dst}, {src0}, {src1}, {src2}{mod_s}" if n == 3 else f"{name} {dst}, {src0}, {src1}{mod_s}"
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:
name, cdna = inst.op_name.lower(), _is_cdna(inst)
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)
@@ -550,8 +512,8 @@ def _disasm_sop1(inst: SOP1) -> str:
try: msg_str = MSG(v).name if v != 255 else None # MSG_RTN_ILLEGAL_MSG (255) not supported by LLVM
except ValueError: msg_str = None
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', 'S_SET_GPR_IDX_IDX', 'S_CBRANCH_JOIN')
sop1_src_only = ('S_ALLOC_VGPR', 'S_SLEEP_VAR', 'S_BARRIER_SIGNAL', 'S_BARRIER_SIGNAL_ISFIRST', 'S_BARRIER_INIT', 'S_BARRIER_JOIN', 'S_SET_GPR_IDX_IDX',
'S_CBRANCH_JOIN')
if inst.op_name in sop1_src_only: return f"{name} {src}"
if cdna:
if 'getpc_b64' in name: return f"{name} {_fmt_sdst(inst.sdst, 2, cdna)}"
@@ -589,7 +551,7 @@ _HWREG_BLACKLIST_CDNA = {'HW_REG_PC_LO', 'HW_REG_PC_HI', 'HW_REG_IB_DBG1', 'HW_R
'HW_REG_SQ_SHADER_TMA_LO', 'HW_REG_SQ_SHADER_TMA_HI', 'HW_REG_SQ_PERF_SNAPSHOT_DATA', 'HW_REG_SQ_PERF_SNAPSHOT_DATA1',
'HW_REG_SQ_PERF_SNAPSHOT_PC_LO', 'HW_REG_SQ_PERF_SNAPSHOT_PC_HI', 'HW_REG_XCC_ID'}
def _disasm_sopk(inst: SOPK) -> str:
name, cdna = inst.op_name.lower(), _is_cdna(inst)
op, name, cdna = inst.op, inst.op_name.lower(), _is_cdna(inst)
is_rdna4 = _is_r4(inst)
hw = HWREG_CDNA if cdna else (HWREG_RDNA4 if is_rdna4 else HWREG)
blacklist = _HWREG_BLACKLIST_CDNA if cdna else _HWREG_BLACKLIST
@@ -612,14 +574,12 @@ def _disasm_sopk(inst: SOPK) -> str:
def _disasm_vinterp(inst: VINTERP) -> str:
mods = _mods((inst.waitexp, f"wait_exp:{inst.waitexp}"), (inst.clmp, "clamp"))
s0, s1, s2 = _lit(inst, inst.src0, inst.neg & 1), _lit(inst, inst.src1, inst.neg & 2), _lit(inst, inst.src2, inst.neg & 4)
return f"{inst.op_name.lower()} {inst.vdst.fmt()}, {s0}, {s1}, {s2}" + (" " + mods if mods else "")
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[..., str]] = {
VOP1: _disasm_vop1, VOP1_SDST: _disasm_vop1, VOP1_SDST_LIT: _disasm_vop1, VOP1_LIT: _disasm_vop1,
VOP2: _disasm_vop2, VOP2_LIT: _disasm_vop2, VOPC: _disasm_vopc, VOPC_LIT: _disasm_vopc,
VOP3: _disasm_vop3, VOP3_SDST: _disasm_vop3, VOP3_SDST_LIT: _disasm_vop3, VOP3_LIT: _disasm_vop3,
VOP3SD: _disasm_vop3sd, VOP3SD_LIT: _disasm_vop3sd,
VOP3: _disasm_vop3, VOP3_SDST: _disasm_vop3, VOP3_SDST_LIT: _disasm_vop3, VOP3_LIT: _disasm_vop3, VOP3SD: _disasm_vop3sd, VOP3SD_LIT: _disasm_vop3sd,
VOPD: _disasm_vopd, VOPD_LIT: _disasm_vopd, VOP3P: _disasm_vop3p, VOP3P_LIT: _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, SOP1_LIT: _disasm_sop1, SOP2: _disasm_sop2, SOP2_LIT: _disasm_sop2,
@@ -640,7 +600,7 @@ def disasm(inst: Inst) -> str: return DISASM_HANDLERS[type(inst)](inst)
# CDNA DISASSEMBLER SUPPORT
# ═══════════════════════════════════════════════════════════════════════════════
from tinygrad.runtime.autogen.amd.cdna.ins import (VOP1 as CDNA_VOP1, VOP1_LIT as CDNA_VOP1_LIT,
from extra.assembly.amd.autogen.cdna.ins import (VOP1 as CDNA_VOP1, VOP1_LIT as CDNA_VOP1_LIT,
VOP1_SDWA as CDNA_VOP1_SDWA, VOP1_DPP16 as CDNA_VOP1_DPP16,
VOP2 as CDNA_VOP2, VOP2_LIT as CDNA_VOP2_LIT, VOP2_SDWA as CDNA_VOP2_SDWA, VOP2_DPP16 as CDNA_VOP2_DPP16,
VOPC as CDNA_VOPC, VOPC_LIT as CDNA_VOPC_LIT, VOPC_SDWA_SDST as CDNA_VOPC_SDWA_SDST,
@@ -674,9 +634,7 @@ def _disasm_vop3a(inst) -> str:
else:
regs = inst.canonical_op_regs
dregs, r0, r1, r2 = regs['d'], regs['s0'], regs['s1'], regs['s2']
s0 = _cdna_src(inst, inst.src0, inst.neg&1, inst.abs&1, r0)
s1 = _cdna_src(inst, inst.src1, inst.neg&2, inst.abs&2, r1)
s2 = _cdna_src(inst, inst.src2, inst.neg&4, inst.abs&4, r2)
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}{opsel}{cl}{om}" if n == 3 else f"{name} {dst}, {s0}, {s1}{opsel}{cl}{om}"
@@ -700,9 +658,7 @@ def _disasm_vop3b(inst) -> str:
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 = _cdna_src(inst, inst.src0, inst.neg&1, n=r0)
s1 = _cdna_src(inst, inst.src1, inst.neg&2, n=r1)
s2 = _cdna_src(inst, inst.src2, inst.neg&4, n=r2)
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)
# CDNA VOP3_SDST uses vdst field for sdst (but vdst adds 256), RDNA uses separate sdst field
sdst_val = getattr(inst, 'sdst', None)
if sdst_val is None and hasattr(inst, 'vdst'):
@@ -724,7 +680,7 @@ 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
def get_src(v, sc): return _lit(inst, v) if v == 255 else _fmt_src(v, sc, cdna=True)
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:
@@ -786,12 +742,9 @@ def _disasm_cdna_vop3p(inst) -> str:
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 []))
mod_s = ' ' + ' '.join(mods) if mods else ''
return f"{name} {dst}, {src0}, {src1}, {src2}{mod_s}" if n == 3 else f"{name} {dst}, {src0}, {src1}{mod_s}"
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 ''}"
def _disasm_mubuf(inst) -> str:
name = inst.op_name.lower()
@@ -950,6 +903,5 @@ DISASM_HANDLERS.update({CDNA_VOP1: _disasm_vop1, CDNA_VOP1_LIT: _disasm_vop1,
CDNA_SOP1: _disasm_sop1, CDNA_SOP1_LIT: _disasm_sop1, CDNA_SOP2: _disasm_sop2, CDNA_SOP2_LIT: _disasm_sop2,
CDNA_SOPC: _disasm_sopc, CDNA_SOPC_LIT: _disasm_sopc, CDNA_SOPK: _disasm_sopk, CDNA_SOPK_LIT: _disasm_sopk, CDNA_SOPP: _disasm_sopp,
CDNA_SMEM: _disasm_smem, CDNA_DS: _disasm_ds, CDNA_FLAT: _disasm_flat, CDNA_GLOBAL: _disasm_flat, CDNA_SCRATCH: _disasm_flat,
CDNA_VOP3: _disasm_vop3a, CDNA_VOP3_SDST: _disasm_vop3b, CDNA_VOP3SD: _disasm_vop3b,
CDNA_VOP3P: _disasm_cdna_vop3p, CDNA_VOP3P_MFMA: _disasm_cdna_vop3p,
CDNA_VOP3: _disasm_vop3a, CDNA_VOP3_SDST: _disasm_vop3b, CDNA_VOP3SD: _disasm_vop3b, CDNA_VOP3P: _disasm_cdna_vop3p, CDNA_VOP3P_MFMA: _disasm_cdna_vop3p,
CDNA_MUBUF: _disasm_mubuf, CDNA_VOP3PX2: _disasm_vop3px2})
@@ -44,15 +44,11 @@ class Reg:
def fmt(self, sz=None, parens=False, upper=False) -> str:
o, sz = self.offset, sz or self.sz
l, r = ("[", "]") if parens or sz > 1 else ("", "") # brackets for multi-reg or when parens=True
if 256 <= o < 512:
idx = o - 256
base = f"v{l}{idx}{r}" if sz == 1 else f"v[{idx}:{idx + sz - 1}]"
if 256 <= o < 512: idx = o - 256; base = f"v{l}{idx}{r}" if sz == 1 else f"v[{idx}:{idx + sz - 1}]"
elif o < 106: base = f"s{l}{o}{r}" if sz == 1 else f"s[{o}:{o + sz - 1}]"
elif sz == 2 and o in self._PAIRS: base = self._PAIRS[o] if upper else self._PAIRS[o].lower()
elif o in self._NAMES: base = self._NAMES[o] if upper else self._NAMES[o].lower() # special regs (any sz)
elif 108 <= o < 124:
idx = o - 108
base = f"ttmp{l}{idx}{r}" if sz == 1 else f"ttmp[{idx}:{idx + sz - 1}]"
elif 108 <= o < 124: idx = o - 108; base = f"ttmp{l}{idx}{r}" if sz == 1 else f"ttmp[{idx}:{idx + sz - 1}]"
elif 128 <= o <= 192: base = str(o - 128) # inline int constants (0-64)
elif 193 <= o <= 208: base = str(-(o - 192)) # inline negative int constants (-1 to -16)
else: raise RuntimeError(f"unknown register: offset={o}, sz={sz}")
@@ -99,7 +95,7 @@ bits = _Bits()
class BitField:
name: str | None
def __init__(self, hi: int, lo: int, default = 0):
def __init__(self, hi: int, lo: int, default: int = 0):
self.hi, self.lo, self.default, self.name, self.mask = hi, lo, default, None, (1 << (hi - lo + 1)) - 1
def __set_name__(self, owner, name: str): self.name = name
def __eq__(self, other) -> 'FixedBitField': # type: ignore[override]
@@ -155,8 +151,7 @@ class SrcField(BitField):
expected_size = self._valid_range[1] - self._valid_range[0] + 1
actual_size = 1 << (hi - lo + 1)
if actual_size != expected_size:
raise RuntimeError(f"{self.__class__.__name__}: field size {hi - lo + 1} bits ({actual_size}) "
f"doesn't match range {self._valid_range} ({expected_size})")
raise RuntimeError(f"{self.__class__.__name__}: field size {hi - lo + 1} bits ({actual_size}) doesn't match range {self._valid_range} ({expected_size})")
def encode(self, val) -> int:
"""Encode value. Returns 255 (literal marker) for out-of-range values."""
@@ -236,9 +231,9 @@ class VDSTYField(BitField):
# ══════════════════════════════════════════════════════════════
import functools
from tinygrad.runtime.autogen.amd.rdna3.operands import OPERANDS as OPERANDS_RDNA3
from tinygrad.runtime.autogen.amd.rdna4.operands import OPERANDS as OPERANDS_RDNA4
from tinygrad.runtime.autogen.amd.cdna.operands import OPERANDS as OPERANDS_CDNA
from extra.assembly.amd.autogen.rdna3.operands import OPERANDS as OPERANDS_RDNA3
from extra.assembly.amd.autogen.rdna4.operands import OPERANDS as OPERANDS_RDNA4
from extra.assembly.amd.autogen.cdna.operands import OPERANDS as OPERANDS_CDNA
OPERANDS = {**OPERANDS_CDNA, **OPERANDS_RDNA3, **OPERANDS_RDNA4}
# ══════════════════════════════════════════════════════════════
@@ -276,7 +271,7 @@ class Inst:
inherited = {}
for base in reversed(cls.__mro__[1:]):
if hasattr(base, '_fields'):
inherited.update(dict(base._fields))
inherited.update({name: field for name, field in base._fields})
inherited.update({name: val for name, val in cls.__dict__.items() if isinstance(val, BitField)})
cls._fields = list(inherited.items())
cls._base_size = (max(f.hi for _, f in cls._fields) + 8) // 8
@@ -408,7 +403,9 @@ class Inst:
@classmethod
def _size(cls) -> int: return cls._base_size
def size(self) -> int: return self._base_size
def disasm(self) -> str: raise NotImplementedError("disasm is no longer supported")
def disasm(self) -> str:
from extra.assembly.amd.disasm import disasm
return disasm(self)
def to_bytes(self) -> bytes: return self._raw.to_bytes(self._base_size, 'little')
File diff suppressed because it is too large Load Diff
@@ -1,7 +1,7 @@
# AMD ISA code generator - generates enum.py, ins.py, operands.py, str_pcode.py
# Sources: XML from https://gpuopen.com/download/machine-readable-isa/latest/
# PDF manuals from AMD documentation
import re, zlib, xml.etree.ElementTree as ET, zipfile, pathlib
import re, zlib, xml.etree.ElementTree as ET, zipfile
from tinygrad.helpers import fetch
# ═══════════════════════════════════════════════════════════════════════════════
@@ -77,13 +77,8 @@ def parse_xml(filename: str):
for ot in root.findall(".//OperandTypes/OperandType"):
ot_name = ot.findtext("OperandTypeName")
for field in ot.findall(".//Field"):
key = (ot_name, field.findtext("FieldName"))
if (enum_name := op_enum_map.get(key)): # type: ignore[arg-type]
def _pv_val(pv: ET.Element) -> tuple[int, str]:
v, n = pv.findtext("Value"), pv.findtext("Name")
assert v is not None and n is not None
return int(v), n.upper()
enums[enum_name] = dict(_pv_val(pv) for pv in field.findall(".//PredefinedValue"))
if (enum_name := op_enum_map.get((ot_name, field.findtext("FieldName")))):
enums[enum_name] = {int(pv.findtext("Value")): pv.findtext("Name").upper() for pv in field.findall(".//PredefinedValue")}
# Extract DataFormats with BitCount
for df in root.findall("ISA/DataFormats/DataFormat"):
name, bits = df.findtext("DataFormatName"), df.findtext("BitCount")
@@ -91,26 +86,17 @@ def parse_xml(filename: str):
# Extract encoding definitions
for enc in root.findall("ISA/Encodings/Encoding"):
name = enc.findtext("EncodingName")
assert name is not None
is_base = name.startswith("ENC_") or name in ("VOP3_SDST_ENC", "VOPDXY")
is_variant = any(sfx in name for sfx in _ENC_SUFFIX_MAP)
if not is_base and not is_variant: continue
if any(s in name for s in _SKIP_ENCODINGS): continue
fields: list[tuple[str, int, int]] = []
for f in enc.findall(".//MicrocodeFormat/BitMap/Field"):
br = f.find("BitLayout/Range")
if br is None: continue
fn = f.findtext("FieldName")
assert fn is not None
fields.append((_norm_field(fn.lower()),
int(br.findtext("BitOffset") or 0) + int(br.findtext("BitCount") or 0) - 1, int(br.findtext("BitOffset") or 0)))
ident_list = enc.findall("EncodingIdentifiers/EncodingIdentifier")
ident = ident_list[0] if ident_list else None
fields = [(_norm_field(f.findtext("FieldName").lower()), int(f.find("BitLayout/Range").findtext("BitOffset") or 0) + int(f.find("BitLayout/Range").findtext("BitCount") or 0) - 1,
int(f.find("BitLayout/Range").findtext("BitOffset") or 0))
for f in enc.findall(".//MicrocodeFormat/BitMap/Field") if f.find("BitLayout/Range") is not None]
ident = (enc.findall("EncodingIdentifiers/EncodingIdentifier") or [None])[0]
enc_field = next((f for f in fields if f[0] == "encoding"), None)
# For multi-dword formats, encoding field may be in higher dword but identifier is always in dword0; use % 32
enc_bits: str | None = None
if ident is not None and ident.text is not None and enc_field:
enc_bits = "".join(ident.text[len(ident.text)-1-b] for b in range(enc_field[1] % 32, (enc_field[2] % 32)-1, -1))
# For multi-dword formats, encoding field may be in higher dword but identifier pattern is always in dword0; use % 32
enc_bits = "".join(ident.text[len(ident.text)-1-b] for b in range(enc_field[1] % 32, (enc_field[2] % 32)-1, -1)) if ident is not None and enc_field else None
base_name = _strip_enc(name)
encodings[NAME_MAP.get(base_name, base_name)] = (fields, enc_bits)
# Extract instruction opcodes and operand info
@@ -118,12 +104,9 @@ def parse_xml(filename: str):
opcode_encs: dict[str, dict[int, set[str]]] = {} # {base_fmt: {opcode: {enc_names}}}
for instr in root.findall("ISA/Instructions/Instruction"):
name = instr.findtext("InstructionName")
assert name is not None
for enc in instr.findall("InstructionEncodings/InstructionEncoding"):
if enc.findtext("EncodingCondition") != "default": continue
enc_enc_name = enc.findtext("EncodingName")
assert enc_enc_name is not None
base, opcode = _map_flat(_strip_enc(enc_enc_name), name), int(enc.findtext("Opcode") or 0)
base, opcode = _map_flat(_strip_enc(enc.findtext("EncodingName")), name), int(enc.findtext("Opcode") or 0)
enc_name = NAME_MAP.get(base, base)
# Encoding variants use the same Op enum as the base format
base_enum = enc_name
@@ -137,10 +120,8 @@ def parse_xml(filename: str):
elif base == "VGLOBAL": enums.setdefault("VFLAT", {})[opcode] = name
enums.setdefault(base_enum, {})[opcode] = name
# Extract operand info
op_info: dict[str, tuple[str | None, int, str | None]] = {}
for op in enc.findall("Operands/Operand"):
fn = op.findtext("FieldName")
if fn: op_info[fn.lower()] = (op.findtext("DataFormatName"), int(op.findtext("OperandSize") or 0), op.findtext("OperandType"))
op_info = {op.findtext("FieldName").lower(): (op.findtext("DataFormatName"), int(op.findtext("OperandSize") or 0), op.findtext("OperandType"))
for op in enc.findall("Operands/Operand") if op.findtext("FieldName")}
for fmt, _, otype in op_info.values():
if fmt and fmt not in fmts: fmts[fmt] = 0
if otype: op_types_set.add(otype)
@@ -162,9 +143,7 @@ def extract_pdf_text(url: str) -> list[list[tuple[float, float, str, str]]]:
data = fetch(url).read_bytes()
# Parse xref table to locate objects
xref: dict[int, int] = {}
xref_match = re.search(rb'startxref\s+(\d+)', data)
assert xref_match is not None
pos = int(xref_match.group(1)) + 4
pos = int(re.search(rb'startxref\s+(\d+)', data).group(1)) + 4
while data[pos:pos+7] != b'trailer':
while data[pos:pos+1] in b' \r\n': pos += 1
line_end = data.find(b'\n', pos)
@@ -185,19 +164,14 @@ def extract_pdf_text(url: str) -> list[list[tuple[float, float, str, str]]]:
if not (m := re.search(rb'/Contents (\d+) 0 R', data[xref[n]:xref[n]+500])): continue
stream = get_stream(int(m.group(1))).decode('latin-1')
elements, font = [], ''
_RE_BT = (r'(/F[\d.]+) [\d.]+ Tf|([\d.+-]+) ([\d.+-]+) Td|[\d.+-]+ [\d.+-]+ [\d.+-]+ [\d.+-]+ ([\d.+-]+) ([\d.+-]+) Tm'
r'|<([0-9A-Fa-f]+)>.*?Tj|\[([^\]]+)\] TJ')
for bt in re.finditer(r'BT(.*?)ET', stream, re.S):
x, y = 0.0, 0.0
for sm in re.finditer(_RE_BT, bt.group(1)):
if sm.group(1): font = sm.group(1)
elif sm.group(2): x, y = x + float(sm.group(2)), y + float(sm.group(3))
elif sm.group(4): x, y = float(sm.group(4)), float(sm.group(5))
elif sm.group(6) and (t := bytes.fromhex(sm.group(6)).decode('latin-1')).strip():
elements.append((x, y, t, font))
elif sm.group(7):
t = ''.join(bytes.fromhex(h).decode('latin-1') for h in re.findall(r'<([0-9A-Fa-f]+)>', sm.group(7)))
if t.strip(): elements.append((x, y, t, font))
for m in re.finditer(r'(/F[\d.]+) [\d.]+ Tf|([\d.+-]+) ([\d.+-]+) Td|[\d.+-]+ [\d.+-]+ [\d.+-]+ [\d.+-]+ ([\d.+-]+) ([\d.+-]+) Tm|<([0-9A-Fa-f]+)>.*?Tj|\[([^\]]+)\] TJ', bt.group(1)):
if m.group(1): font = m.group(1)
elif m.group(2): x, y = x + float(m.group(2)), y + float(m.group(3))
elif m.group(4): x, y = float(m.group(4)), float(m.group(5))
elif m.group(6) and (t := bytes.fromhex(m.group(6)).decode('latin-1')).strip(): elements.append((x, y, t, font))
elif m.group(7) and (t := ''.join(bytes.fromhex(h).decode('latin-1') for h in re.findall(r'<([0-9A-Fa-f]+)>', m.group(7)))).strip(): elements.append((x, y, t, font))
pages.append(sorted(elements, key=lambda e: (-e[1], e[0])))
return pages
@@ -223,7 +197,7 @@ def extract_pcode(pages: list[list[tuple[float, float, str, str]]], name_to_op:
else:
next_page, next_y = page_idx, 0
# Collect F6 text from current position to next instruction (pseudocode is at x ≈ 69)
lines: list[tuple[int, float, str]] = []
lines = []
for p in range(page_idx, next_page + 1):
start_y = y if p == page_idx else 800
end_y = next_y if p == next_page else 0
@@ -246,8 +220,8 @@ def extract_pcode(pages: list[list[tuple[float, float, str, str]]], name_to_op:
# Code generation
# ═══════════════════════════════════════════════════════════════════════════════
def write_common(all_fmts: dict[str, int], all_op_types: set[str], path: pathlib.Path) -> None:
lines: list[str] = ["# autogenerated from AMD ISA XML - do not edit", "from enum import Enum, auto", ""]
def write_common(all_fmts, all_op_types, path):
lines = ["# autogenerated from AMD ISA XML - do not edit", "from enum import Enum, auto", ""]
lines.append("class ReprEnum(Enum):")
lines.append(' """Enum with clean repr that roundtrips with eval()."""')
lines.append(' def __repr__(self): return f"{type(self).__name__}.{self.name}"')
@@ -264,8 +238,7 @@ def write_common(all_fmts: dict[str, int], all_op_types: set[str], path: pathlib
with open(path, "w") as f: f.write("\n".join(lines))
def write_enum(enums, path):
lines: list[str] = ["# autogenerated from AMD ISA XML - do not edit",
"from tinygrad.runtime.autogen.amd.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401", ""]
lines = ["# autogenerated from AMD ISA XML - do not edit", "from extra.assembly.amd.autogen.common import ReprEnum, Fmt, FMT_BITS, OpType # noqa: F401", ""]
for name, ops in sorted(enums.items()):
if not ops: continue
suffix = "_E32" if name in ("VOP1", "VOP2", "VOPC") else "_E64" if name == "VOP3" else ""
@@ -313,7 +286,7 @@ def write_ins(encodings, enums, suffix_only_ops, types, arch, path):
'dpp', 'fi', 'bc', 'row_mask', 'bank_mask', 'src0_neg', 'src0_abs', 'src1_neg', 'src1_abs',
'cbsz', 'abid', 'acc_cd', 'acc', 'blgp', 'lane_sel_0', 'lane_sel_1', 'lane_sel_2', 'lane_sel_3',
'lane_sel_4', 'lane_sel_5', 'lane_sel_6', 'lane_sel_7', 'dst_sel', 'dst_unused', 'src0_sel', 'src1_sel']
def sort_fields(fields): return sorted(fields, key=lambda f: (ORDER.index(f[0]) if f[0] in ORDER else 999, f[2]))
sort_fields = lambda fields: sorted(fields, key=lambda f: (ORDER.index(f[0]) if f[0] in ORDER else 999, f[2]))
# Separate base encodings from variants
base_encodings, variant_encodings = {}, {}
@@ -323,29 +296,15 @@ def write_ins(encodings, enums, suffix_only_ops, types, arch, path):
else: variant_encodings[enc_name] = data
# Build sets of ops by their vdst type from operand metadata
sdst_opcodes: dict[str, set[int]] = {} # ops where vdst is OPR_SREG (writes to SGPR)
sdst_opcodes = {} # ops where vdst is OPR_SREG (writes to SGPR)
for fmt, ops in enums.items():
for op, name in ops.items():
op_types = types.get((name, fmt), {})
vdst_type = op_types.get("vdst", (None, None, None))[2]
if vdst_type == "OPR_SREG": sdst_opcodes.setdefault(fmt, set()).add(op)
# collect only the XxxOp enums that are actually referenced in this arch's instruction definitions
enum_names = sorted(f"{k}Op" for k in enums if enums[k] and k not in ("HWREG", "MSG"))
# also re-export HWREG/MSG enums (plain enums, not instruction format ops)
enum_names += sorted(k for k in enums if k in ("HWREG", "MSG") and enums[k])
# collect DSL field types actually used by scanning generated field definitions
all_field_defs = " ".join(field_def(fn, hi, lo, enc, eb) for enc, (flds, eb) in encodings.items() for fn, hi, lo in flds)
_ALL_DSL = ["BitField", "EnumBitField", "FixedBitField", "NULL", "SBaseField", "SGPRField", "SRsrcField",
"SSrcField", "SrcField", "VDSTYField", "VGPRField"]
dsl_names = ["Inst"] + [n for n in _ALL_DSL if n in all_field_defs]
# also re-export register names so `from ins import *` still provides them to downstream users
_DSL_REGS = ["s", "v", "src", "VCC_LO", "VCC_HI", "VCC", "EXEC_LO", "EXEC_HI", "EXEC", "NULL", "OFF", "M0",
"SCC", "VCCZ", "EXECZ", "ttmp", "INV_2PI", "SDWA", "DPP", "DPP16", "LIT", "SRC_LDS_DIRECT"]
dsl_reexport = sorted(set(dsl_names + _DSL_REGS))
lines: list[str] = ["# autogenerated from AMD ISA XML - do not edit", "# ruff: noqa: E501,F401",
f"from tinygrad.renderer.amd.dsl import {', '.join(dsl_reexport)}",
f"from tinygrad.runtime.autogen.amd.{arch}.enum import {', '.join(enum_names)}", "import functools", ""]
lines = ["# autogenerated from AMD ISA XML - do not edit", "# ruff: noqa: F401,F403",
"from extra.assembly.amd.dsl import *", f"from extra.assembly.amd.autogen.{arch}.enum import *", "import functools", ""]
def fmt_allowed(op_enum: str, ops: set[int]) -> str:
"""Format allowed ops as {EnumName.MEMBER, ...}."""
@@ -364,9 +323,7 @@ def write_ins(encodings, enums, suffix_only_ops, types, arch, path):
has_seg_field = any(fn == "seg" for fn, _, _ in fields)
if enc_name in ("FLAT", "VFLAT") and has_seg_field:
prefix = "V" if enc_name == "VFLAT" else ""
flat_variants = [(f"{prefix}FLAT", 0, f"{prefix}FLATOp"), (f"{prefix}GLOBAL", 2, f"{prefix}GLOBALOp"),
(f"{prefix}SCRATCH", 1, f"{prefix}SCRATCHOp")]
for cls, seg, op_enum in flat_variants:
for cls, seg, op_enum in [(f"{prefix}FLAT", 0, f"{prefix}FLATOp"), (f"{prefix}GLOBAL", 2, f"{prefix}GLOBALOp"), (f"{prefix}SCRATCH", 1, f"{prefix}SCRATCHOp")]:
cls_ops = set(enums.get(cls, {}).keys())
lines.append(f"class {cls}(Inst):")
for fn, hi, lo in sort_fields(fields):
@@ -439,8 +396,6 @@ def write_ins(encodings, enums, suffix_only_ops, types, arch, path):
op_to_suffix = {op:suffix for suffix,ops in suffix_only_ops.items() for op in ops.get(fmt, set())}
fmt_sdst_ops = sdst_opcodes.get(fmt, set())
for op, name in sorted(ops.items()):
# ADDTID ops are in both FLAT and GLOBAL enums (for pcode); only generate helper for GLOBAL/VGLOBAL
if "ADDTID" in name and fmt in ("FLAT", "VFLAT"): continue
msuf = suffix if fmt != "VOP3" or op < 512 else ""
# Determine class: SDST variants, suffix-specific variants (e.g., _MFMA, _LIT), or base
if fmt == "VOP1" and op in fmt_sdst_ops: cls = "VOP1_SDST"
@@ -450,14 +405,11 @@ def write_ins(encodings, enums, suffix_only_ops, types, arch, path):
lines.append(f"{name.lower()}{msuf.lower()} = functools.partial({cls}, {fmt}Op.{name}{msuf})")
with open(path, "w") as f: f.write("\n".join(lines))
def write_operands(types: dict, enums: dict, arch: str, path: pathlib.Path) -> None:
def write_operands(types, enums, arch, path):
valid = {(name, fmt) for fmt, ops in enums.items() for name in ops.values()}
# only import enums that are actually used as keys in OPERANDS
used_bases = {eb for (nm, eb) in types if (nm, eb) in valid}
enum_names = sorted(f"{k}Op" for k in used_bases)
lines: list[str] = ["# autogenerated from AMD ISA XML - do not edit",
"from tinygrad.runtime.autogen.amd.common import Fmt, OpType",
f"from tinygrad.runtime.autogen.amd.{arch}.enum import {', '.join(enum_names)}", ""]
lines = ["# autogenerated from AMD ISA XML - do not edit",
"from extra.assembly.amd.autogen.common import Fmt, OpType",
f"from extra.assembly.amd.autogen.{arch}.enum import *", ""]
lines.append("# instruction operand info: {Op: {field: (Fmt, size_bits, OpType)}}")
lines.append("OPERANDS = {")
def fmt_val(v):
@@ -470,7 +422,7 @@ def write_operands(types: dict, enums: dict, arch: str, path: pathlib.Path) -> N
lines.append("}")
with open(path, "w") as f: f.write("\n".join(lines))
def write_pcode(pcode: dict[tuple[str, int], str], enums: dict[str, dict[int, str]], arch: str, path: pathlib.Path) -> None:
def write_pcode(pcode: dict[tuple[str, int], str], enums: dict[str, dict[int, str]], arch: str, path: str):
"""Write str_pcode.py file from extracted pseudocode."""
entries: list[tuple[str, str, int, str]] = []
for fmt_name, ops in enums.items():
@@ -481,7 +433,7 @@ def write_pcode(pcode: dict[tuple[str, int], str], enums: dict[str, dict[int, st
entries.append((f"{fmt_name}Op", f"{name}{msuf}", opcode, pcode[(name, opcode)]))
enum_names = sorted(set(e[0] for e in entries))
lines = ["# autogenerated from AMD ISA PDF - do not edit", "# ruff: noqa: E501",
f"from tinygrad.runtime.autogen.amd.{arch}.enum import {', '.join(enum_names)}", "", "PCODE = {"]
f"from extra.assembly.amd.autogen.{arch}.enum import {', '.join(enum_names)}", "", "PCODE = {"]
for enum_name, name, opcode, code in sorted(entries, key=lambda x: (x[0], x[2])):
lines.append(f" {enum_name}.{name}: {code!r},")
lines.append("}")
@@ -492,9 +444,8 @@ def write_pcode(pcode: dict[tuple[str, int], str], enums: dict[str, dict[int, st
# ═══════════════════════════════════════════════════════════════════════════════
if __name__ == "__main__":
all_fmts: dict[str, int] = {}
all_op_types: set[str] = set()
arch_data: dict[str, dict] = {}
import pathlib
all_fmts, all_op_types, arch_data = {}, set(), {}
# First pass: parse XML for all architectures
for arch, cfg in ARCHS.items():
print(f"Parsing XML: {cfg['xml']} -> {arch}")
@@ -508,13 +459,12 @@ if __name__ == "__main__":
all_fmts[fmt] = bits
all_op_types.update(op_types_set)
# Write common.py
autogen_base = pathlib.Path(__file__).parents[2] / "runtime" / "autogen" / "amd"
common_path = autogen_base / "common.py"
common_path = pathlib.Path(__file__).parent / "autogen" / "common.py"
write_common(all_fmts, all_op_types, common_path)
print(f"Wrote common.py: {len(all_fmts)} formats, {len(all_op_types)} op types")
# Write per-arch files from XML
for arch, data in arch_data.items():
base = autogen_base / arch
base = pathlib.Path(__file__).parent / "autogen" / arch
write_enum(data["enums"], base / "enum.py")
write_ins(data["encodings"], data["enums"], data["suffix_only_ops"], data["types"], arch, base / "ins.py")
write_operands(data["types"], data["enums"], arch, base / "operands.py")
@@ -525,6 +475,6 @@ if __name__ == "__main__":
pages = extract_pdf_text(cfg["pdf"])
name_to_op = {name: op for ops in arch_data[arch]["enums"].values() for op, name in ops.items()}
pcode = extract_pcode(pages, name_to_op)
base = autogen_base / arch
base = pathlib.Path(__file__).parent / "autogen" / arch
write_pcode(pcode, arch_data[arch]["enums"], arch, base / "str_pcode.py")
print(f" {arch}: {len(pcode)} pcode entries")
@@ -40,10 +40,7 @@ def _bitreverse(v: UOp, bits: int) -> UOp:
def _extract_bits(val: UOp, hi: int, lo: int) -> UOp:
dt = dtypes.uint64 if val.dtype in (dtypes.uint64, dtypes.int64) else dtypes.uint32
result = ((val >> _const(dt, lo)) if lo > 0 else val) & _const(val.dtype, (1 << (hi - lo + 1)) - 1)
# Downcast to uint32 when extracting <=32 bits from a 64-bit value, so .f32 bitcast works correctly
if dt == dtypes.uint64 and (hi - lo + 1) <= 32: result = result.cast(dtypes.uint32)
return result
return ((val >> _const(dt, lo)) if lo > 0 else val) & _const(val.dtype, (1 << (hi - lo + 1)) - 1)
def _set_bit(old, pos, val):
mask = _u32(1) << pos
@@ -55,9 +52,7 @@ def _val_to_bits(val):
if val.dtype == dtypes.float64: return val.bitcast(dtypes.uint64)
return val if val.dtype == dtypes.uint32 else val.cast(dtypes.uint32)
def _floor(x):
t = UOp(Ops.TRUNC, x.dtype, (x,))
return ((x < _const(x.dtype, 0)) & x.ne(t)).where(t - _const(x.dtype, 1), t)
def _floor(x): t = UOp(Ops.TRUNC, x.dtype, (x,)); return ((x < _const(x.dtype, 0)) & x.ne(t)).where(t - _const(x.dtype, 1), t)
def _f16_extract(v): return (v & _u32(0xFFFF)).cast(dtypes.uint16).bitcast(dtypes.half) if v.dtype == dtypes.uint32 else v
def _check_nan(v: UOp, quiet: bool) -> UOp:
@@ -123,8 +118,7 @@ def _f_to_u(f, dt): return UOp(Ops.TRUNC, f.dtype, ((f < _const(f.dtype, 0.0)).w
def _cvt_quiet(val: UOp) -> UOp:
bits, _, _, qb, _ = _float_info(val)
bt, ft = (dtypes.uint64, dtypes.float64) if val.dtype == dtypes.float64 else \
(dtypes.uint16, dtypes.half) if val.dtype == dtypes.half else (dtypes.uint32, dtypes.float32)
bt, ft = (dtypes.uint64, dtypes.float64) if val.dtype == dtypes.float64 else (dtypes.uint16, dtypes.half) if val.dtype == dtypes.half else (dtypes.uint32, dtypes.float32)
return (val.bitcast(bt) | qb).bitcast(ft)
def _is_denorm(val: UOp) -> UOp:
@@ -169,18 +163,14 @@ def _ldexp(val: UOp, exp: UOp) -> UOp:
def _frexp_mant(val: UOp) -> UOp:
val = val.bitcast(dtypes.float32) if val.dtype == dtypes.uint32 else val.bitcast(dtypes.float64) if val.dtype == dtypes.uint64 else val
if val.dtype == dtypes.float32: return ((val.bitcast(dtypes.uint32) & _u32(0x807FFFFF)) | _u32(0x3f000000)).bitcast(dtypes.float32)
return ((val.bitcast(dtypes.uint64) & _const(dtypes.uint64, 0x800FFFFFFFFFFFFF)) |
_const(dtypes.uint64, 0x3fe0000000000000)).bitcast(dtypes.float64)
return ((val.bitcast(dtypes.uint64) & _const(dtypes.uint64, 0x800FFFFFFFFFFFFF)) | _const(dtypes.uint64, 0x3fe0000000000000)).bitcast(dtypes.float64)
def _frexp_exp(val: UOp) -> UOp:
val = val.bitcast(dtypes.float32) if val.dtype == dtypes.uint32 else val.bitcast(dtypes.float64) if val.dtype == dtypes.uint64 else val
if val.dtype == dtypes.float32: return ((val.bitcast(dtypes.uint32) >> _u32(23)) & _u32(0xFF)).cast(dtypes.int) - _const(dtypes.int, 126)
return ((val.bitcast(dtypes.uint64) >> _const(dtypes.uint64, 52)) & _const(dtypes.uint64, 0x7FF)).cast(dtypes.int) - _const(dtypes.int, 1022)
TWO_OVER_PI = int(
"0145f306dc9c882a53f84eafa3ea69bb81b6c52b3278872083fca2c757bd778ac36e48dc74849ba5c00c925dd413a32439fc3bd"
"63962534e7dd1046bea5d768909d338e04d68befc827323ac7306a673e93908bf177bf250763ff12fffbc0b301fde5e2316b414"
"da3eda6cfd9e4f96136e9e8c7ecd3cbfd45aea4f758fd7cbe2f67a0e73ef14a525d4d7f6bf623f1aba10ac06608df8f6", 16)
TWO_OVER_PI = 0x0145f306dc9c882a53f84eafa3ea69bb81b6c52b3278872083fca2c757bd778ac36e48dc74849ba5c00c925dd413a32439fc3bd63962534e7dd1046bea5d768909d338e04d68befc827323ac7306a673e93908bf177bf250763ff12fffbc0b301fde5e2316b414da3eda6cfd9e4f96136e9e8c7ecd3cbfd45aea4f758fd7cbe2f67a0e73ef14a525d4d7f6bf623f1aba10ac06608df8f6
# TWO_OVER_PI as 19 u64 words for trig_preop_result (word[0] = bits 0-63, word[18] = bits 1152-1200)
_PREOP_WORDS = tuple((TWO_OVER_PI >> (64 * i)) & 0xFFFFFFFFFFFFFFFF for i in range(19))
def _trig_preop(val: UOp) -> UOp:
@@ -257,14 +247,10 @@ _FUNCS: dict[str, Callable[..., UOp]] = {
# Normalization conversions: map [-1,1] or [0,1] to integer range
# Use floor(x + 0.5) for round-to-nearest
# SNORM: round(value * 32767), range is [-32767, 32767] (hardware behavior)
'f16_to_snorm': lambda a: _floor(
_f16_extract(a).cast(dtypes.float32) * _const(dtypes.float32, 32767) + _const(dtypes.float32, 0.5)).cast(dtypes.int).cast(dtypes.int16),
'f16_to_unorm': lambda a: _floor(
_f16_extract(a).cast(dtypes.float32) * _const(dtypes.float32, 65535) + _const(dtypes.float32, 0.5)).cast(dtypes.uint16),
'f32_to_snorm': lambda a: _floor(
a.bitcast(dtypes.float32) * _const(dtypes.float32, 32767) + _const(dtypes.float32, 0.5)).cast(dtypes.int).cast(dtypes.int16),
'f32_to_unorm': lambda a: _floor(
a.bitcast(dtypes.float32) * _const(dtypes.float32, 65535) + _const(dtypes.float32, 0.5)).cast(dtypes.uint16),
'f16_to_snorm': lambda a: _floor(_f16_extract(a).cast(dtypes.float32) * _const(dtypes.float32, 32767) + _const(dtypes.float32, 0.5)).cast(dtypes.int).cast(dtypes.int16),
'f16_to_unorm': lambda a: _floor(_f16_extract(a).cast(dtypes.float32) * _const(dtypes.float32, 65535) + _const(dtypes.float32, 0.5)).cast(dtypes.uint16),
'f32_to_snorm': lambda a: _floor(a.bitcast(dtypes.float32) * _const(dtypes.float32, 32767) + _const(dtypes.float32, 0.5)).cast(dtypes.int).cast(dtypes.int16),
'f32_to_unorm': lambda a: _floor(a.bitcast(dtypes.float32) * _const(dtypes.float32, 65535) + _const(dtypes.float32, 0.5)).cast(dtypes.uint16),
'f32_to_u8': lambda a: _f_to_u(a.bitcast(dtypes.float32), dtypes.uint8),
# Integer truncation conversions
'i32_to_i16': lambda a: a.cast(dtypes.int).cast(dtypes.int16),
@@ -288,7 +274,6 @@ _FUNCS: dict[str, Callable[..., UOp]] = {
# Address calculation for memory operations
'CalcDsAddr': lambda a, o, *r: a.cast(dtypes.uint32) + o.cast(dtypes.uint32),
'CalcGlobalAddr': lambda v, s, *r: v.cast(dtypes.uint64) + s.cast(dtypes.uint64),
'CalcScratchAddr': lambda v, s, *r: v.cast(dtypes.uint64) + s.cast(dtypes.uint64),
}
for is_max, name in [(False, 'min'), (True, 'max')]:
for dt, sfx in [(dtypes.float32, 'f32'), (dtypes.int, 'i32'), (dtypes.uint32, 'u32'), (dtypes.int16, 'i16'), (dtypes.uint16, 'u16')]:
@@ -325,35 +310,21 @@ _SINGLE_CHAR = {'(': 'LPAREN', ')': 'RPAREN', '[': 'LBRACKET', ']': 'RBRACKET',
class Token:
__slots__ = ('type', 'val')
def __init__(self, kind: str, val: str): self.type, self.val = kind, val
def __init__(self, type: str, val: str): self.type, self.val = type, val
def __repr__(self): return f'{self.type}:{self.val}'
def tokenize(s: str) -> list[Token]:
tokens, i, n = [], 0, len(s)
while i < n:
c = s[i]
if c.isspace():
i += 1
continue
if c.isspace(): i += 1; continue
if i + 1 < n and s[i:i+2] in ('+=', '-='):
tokens.append(Token('ASSIGN_OP', s[i:i+2]))
i += 2
continue
tokens.append(Token('ASSIGN_OP', s[i:i+2])); i += 2; continue
if i + 1 < n and s[i:i+2] in ('||', '&&', '>=', '<=', '==', '!=', '<>', '>>', '<<', '**', '+:', '-:'):
tokens.append(Token('OP', s[i:i+2]))
i += 2
continue
if c in '|^&><+-*/~!%':
tokens.append(Token('OP', c))
i += 1
continue
if (t := _SINGLE_CHAR.get(c)):
tokens.append(Token(t, c))
i += 1
continue
if c == ';':
i += 1
continue
tokens.append(Token('OP', s[i:i+2])); i += 2; continue
if c in '|^&><+-*/~!%': tokens.append(Token('OP', c)); i += 1; continue
if (t := _SINGLE_CHAR.get(c)): tokens.append(Token(t, c)); i += 1; continue
if c == ';': i += 1; continue
if c.isdigit() or (c == '-' and i + 1 < n and s[i+1].isdigit()):
start = i
if c == '-': i += 1
@@ -366,38 +337,31 @@ def tokenize(s: str) -> list[Token]:
i += 1
while i < n and s[i].isdigit(): i += 1
for sfx in ('ULL', 'LL', 'UL', 'U', 'L', 'F', 'f'):
if s[i:i+len(sfx)] == sfx:
i += len(sfx)
break
tokens.append(Token('NUM', s[start:i]))
continue
if s[i:i+len(sfx)] == sfx: i += len(sfx); break
tokens.append(Token('NUM', s[start:i])); continue
if c.isalpha() or c == '_':
start = i
while i < n and (s[i].isalnum() or s[i] == '_'): i += 1
tokens.append(Token('IDENT', s[start:i]))
continue
tokens.append(Token('IDENT', s[start:i])); continue
raise RuntimeError(f"unexpected char '{c}' at pos {i} in: {s}")
tokens.append(Token('EOF', ''))
return tokens
class Parser:
def __init__(self, tokens: list[Token], env: dict, funcs: dict | None = None):
self.tokens, self.vars, self.funcs, self.pos = tokens, env, funcs if funcs is not None else _FUNCS, 0
def __init__(self, tokens: list[Token], vars: dict, funcs: dict | None = None):
self.tokens, self.vars, self.funcs, self.pos = tokens, vars, funcs if funcs is not None else _FUNCS, 0
def peek(self, offset=0) -> Token: return self.tokens[min(self.pos + offset, len(self.tokens) - 1)]
def at(self, *types) -> bool: return self.peek().type in types
def _advance(self) -> Token:
tok = self.tokens[self.pos]
self.pos += 1
return tok
def eat(self, kind: str) -> Token:
if self.peek().type != kind: raise RuntimeError(f"expected {kind}, got {self.peek()}")
def _advance(self) -> Token: tok = self.tokens[self.pos]; self.pos += 1; return tok
def eat(self, type: str) -> Token:
if self.peek().type != type: raise RuntimeError(f"expected {type}, got {self.peek()}")
return self._advance()
def try_eat(self, kind: str) -> Token | None: return self._advance() if self.peek().type == kind else None
def try_eat_val(self, val: str, kind: str) -> Token | None:
return self._advance() if self.peek().type == kind and self.peek().val == val else None
def eat_val(self, val: str, kind: str) -> Token:
if self.peek().type != kind or self.peek().val != val: raise RuntimeError(f"expected {kind}:{val}, got {self.peek()}")
def try_eat(self, type: str) -> Token | None: return self._advance() if self.peek().type == type else None
def try_eat_val(self, val: str, type: str) -> Token | None:
return self._advance() if self.peek().type == type and self.peek().val == val else None
def eat_val(self, val: str, type: str) -> Token:
if self.peek().type != type or self.peek().val != val: raise RuntimeError(f"expected {type}:{val}, got {self.peek()}")
return self._advance()
def parse(self) -> UOp:
@@ -416,11 +380,9 @@ class Parser:
case '||' | '|': return left | right
case '&&' | '&': return left & right
case '^': return left ^ right
case '==': return left.eq(right)
case '!=': return left.ne(right)
case '>=' | '<=' | '>' | '<' | '<>':
ops = {'>=':(lambda a,b:a>=b),'<=':(lambda a,b:a<=b),'>':(lambda a,b:a>b),'<':(lambda a,b:a<b),'<>':(lambda a,b:a.ne(b))}
return self._cmp_nan(left, right, ops[op])
case '==' | '<>': return left.eq(right) if op == '==' else left.ne(right)
case '!=' : return left.ne(right)
case '>=' | '<=' | '>' | '<': return self._cmp_nan(left, right, {'>=':(lambda a,b:a>=b),'<=':(lambda a,b:a<=b),'>':(lambda a,b:a>b),'<':(lambda a,b:a<b)}[op])
case '>>' | '<<': return (left >> right) if op == '>>' else (left << right)
case '+' | '-':
if op == '-' and left.op == Ops.CONST and right.op == Ops.CONST: return _const(left.dtype, left.arg - right.arg)
@@ -558,9 +520,7 @@ class Parser:
self.eat('LBRACKET')
self.eat_val('laneId', 'IDENT')
self.eat('RBRACKET')
lane = self.vars['laneId']
shift = lane.cast(base.dtype) if base.dtype != dtypes.uint32 else _to_u32(lane)
result = (base >> shift) & _const(base.dtype, 1)
result = (base >> _to_u32(self.vars['laneId'])) & _u32(1)
if self.try_eat('DOT'):
dt_name = self.eat('IDENT').val
return result.cast(DTYPES.get(dt_name, dtypes.uint32))
@@ -569,8 +529,7 @@ class Parser:
if dt is None: return base
if dt == base.dtype: return base
if dt.itemsize == 2 and base.dtype.itemsize == 4:
if dt == dtypes.uint16: return (base & _const(base.dtype, 0xFFFF)).cast(dtypes.uint16)
return (base & _const(base.dtype, 0xFFFF)).cast(dtypes.uint16).bitcast(dt)
return (base & _const(base.dtype, 0xFFFF)).cast(dtypes.uint16) if dt == dtypes.uint16 else (base & _const(base.dtype, 0xFFFF)).cast(dtypes.uint16).bitcast(dt)
if field == 'i4': return _signext_4bit(base)
return _cast_to(base, dt)
@@ -580,7 +539,7 @@ class Parser:
def _handle_bracket_rest(self, first: UOp, base: UOp, var_name: str | None = None) -> UOp:
if self.at('OP') and self.peek().val in ('+:', '-:'):
self.eat('OP')
op = self.eat('OP').val
width = self.parse()
self.eat('RBRACKET')
if width.op == Ops.CONST:
@@ -666,8 +625,7 @@ class Parser:
inner = self.parse()
self.eat('RPAREN')
dt = {('U',32): dtypes.uint32, ('U',64): dtypes.uint64, ('I',32): dtypes.int, ('I',64): dtypes.int64,
('F',16): dtypes.half, ('F',32): dtypes.float32, ('F',64): dtypes.float64,
('B',32): dtypes.uint32, ('B',64): dtypes.uint64}.get((type_char, bits), dtypes.uint64 if bits > 32 else dtypes.uint32)
('F',16): dtypes.half, ('F',32): dtypes.float32, ('F',64): dtypes.float64, ('B',32): dtypes.uint32, ('B',64): dtypes.uint64}.get((type_char, bits), dtypes.uint64 if bits > 32 else dtypes.uint32)
if type_char == 'F' and inner.dtype in (dtypes.uint32, dtypes.uint64, dtypes.ulong, dtypes.int, dtypes.int64):
if inner.dtype.itemsize != dt.itemsize: inner = inner.cast(dtypes.uint32 if dt.itemsize == 4 else dtypes.uint64)
return inner.bitcast(dt)
@@ -728,7 +686,7 @@ class Parser:
def _call_func(self, name: str, args: list[UOp]) -> UOp:
if name in self.vars and isinstance(self.vars[name], tuple) and self.vars[name][0] == 'lambda':
_, params, body = self.vars[name]
lv = {**self.vars, **dict(zip(params, args))}
lv = {**self.vars, **{p: a for p, a in zip(params, args)}}
if ';' in body or '\n' in body or 'return' in body.lower():
lines = [l.strip() for l in body.replace(';', '\n').split('\n') if l.strip() and not l.strip().startswith('//')]
_, _, result = parse_block(lines, 0, lv, self.funcs)
@@ -754,9 +712,7 @@ class Parser:
elif dt in (dtypes.uint8, dtypes.int8):
val = mem.index(idx, *gate, ptr=True).load().cast(dt)
elif dt in (dtypes.uint16, dtypes.int16, dtypes.short):
lo = mem.index(idx, *gate, ptr=True).load().cast(dtypes.uint32)
hi = mem.index(idx + _const(dtypes.int, 1), *gate, ptr=True).load().cast(dtypes.uint32)
val = (lo | (hi << _u32(8))).cast(dt)
val = (mem.index(idx, *gate, ptr=True).load().cast(dtypes.uint32) | (mem.index(idx + _const(dtypes.int, 1), *gate, ptr=True).load().cast(dtypes.uint32) << _u32(8))).cast(dt)
else:
val = _u32(0)
for i in range(4): val = val | (mem.index(idx + _const(dtypes.int, i), *gate, ptr=True).load().cast(dtypes.uint32) << _u32(i * 8))
@@ -767,8 +723,7 @@ class Parser:
idx2 = ((addr + _const(adt, 4)) >> _const(adt, 2)).cast(dtypes.int)
val = val.cast(dtypes.uint64) | (mem.index(idx2, *gate).cast(dtypes.uint64) << _u64(32))
elif dt in (dtypes.uint8, dtypes.int8): val = (val >> ((addr & _const(adt, 3)).cast(dtypes.uint32) * _u32(8))) & _u32(0xFF)
elif dt in (dtypes.uint16, dtypes.int16):
val = (val >> (((addr >> _const(adt, 1)) & _const(adt, 1)).cast(dtypes.uint32) * _u32(16))) & _u32(0xFFFF)
elif dt in (dtypes.uint16, dtypes.int16): val = (val >> (((addr >> _const(adt, 1)) & _const(adt, 1)).cast(dtypes.uint32) * _u32(16))) & _u32(0xFFFF)
return val
def _coerce_cmp(self, l: UOp, r: UOp) -> tuple[UOp, UOp]:
@@ -801,8 +756,8 @@ def _match_bracket(toks: list[Token], start: int) -> tuple[int, list[Token]]:
return j, [t for t in toks[start+1:j-1] if t.type != 'EOF']
def _tok_str(toks: list[Token]) -> str: return ' '.join(t.val for t in toks if t.type != 'EOF')
def parse_tokens(toks: list[Token], env: dict[str, VarVal], funcs: dict | None = None) -> UOp:
return Parser(toks, env, funcs).parse()
def parse_tokens(toks: list[Token], vars: dict[str, VarVal], funcs: dict | None = None) -> UOp:
return Parser(toks, vars, funcs).parse()
# Unified block parser for pcode
def _subst_loop_var(line: str, loop_var: str, val: int) -> str:
@@ -812,13 +767,6 @@ def _subst_loop_var(line: str, loop_var: str, val: int) -> str:
def _set_bits(old: UOp, val: UOp, width: int, offset: int) -> UOp:
"""Set bits [offset:offset+width) in old to val, masking and shifting appropriately."""
if old.dtype in (dtypes.half, dtypes.float32): old = _val_to_bits(old)
is64 = old.dtype in (dtypes.uint64, dtypes.int64) or offset + width > 32
if is64:
old = old.cast(dtypes.uint64) if old.dtype != dtypes.uint64 else old
mask = _u64(((1 << width) - 1) << offset)
v = (val.cast(dtypes.uint64) if val.dtype != dtypes.uint64 else val) & _u64((1 << width) - 1)
return (old & (mask ^ _u64(0xFFFFFFFFFFFFFFFF))) | (v << _u64(offset))
mask = _u32(((1 << width) - 1) << offset)
v = (val.cast(dtypes.uint32) if val.dtype != dtypes.uint32 else val) & _u32((1 << width) - 1)
return (old & (mask ^ _u32(0xFFFFFFFF))) | (v << _u32(offset))
@@ -833,7 +781,7 @@ def _find_paren_end(s: str, start: int = 0, open_ch: str = '(', close_ch: str =
if depth == 0: return j
return len(s)
def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dict | None = None,
def parse_block(lines: list[str], start: int, vars: dict[str, VarVal], funcs: dict | None = None,
assigns: list | None = None) -> tuple[int, dict[str, VarVal], UOp | None]:
"""Parse a block of pcode. Returns (next_line, block_assigns, return_value).
If assigns list is provided, side effects (MEM/VGPR writes) are appended to it."""
@@ -844,9 +792,7 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
while i < len(lines):
line = lines[i]
toks = tokenize(line)
if toks[0].type != 'IDENT' and toks[0].type != 'LBRACE':
i += 1
continue
if toks[0].type != 'IDENT' and toks[0].type != 'LBRACE': i += 1; continue
first = toks[0].val.lower() if toks[0].type == 'IDENT' else '{'
# Block terminators
@@ -855,19 +801,17 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
# return expr (lambda bodies)
if first == 'return':
rest = line[line.lower().find('return') + 6:].strip()
return i + 1, block_assigns, parse_expr(rest, env, funcs)
return i + 1, block_assigns, parse_expr(rest, vars, funcs)
# for loop
if first == 'for':
# Parse: for VAR in [SIZE']START : [SIZE']END do
p = Parser(toks, env, funcs)
p = Parser(toks, vars, funcs)
p.eat_val('for', 'IDENT')
loop_var = p.eat('IDENT').val
p.eat_val('in', 'IDENT')
def parse_bound():
if p.at('NUM') and p.peek(1).type == 'QUOTE':
p.eat('NUM')
p.eat('QUOTE')
if p.at('NUM') and p.peek(1).type == 'QUOTE': p.eat('NUM'); p.eat('QUOTE')
if p.at('NUM'): return int(p.eat('NUM').val.rstrip('UuLl'))
expr = p.parse().simplify()
assert expr.op == Ops.CONST, f"loop bound must be constant, got {expr}"
@@ -889,41 +833,38 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
# Execute loop with break support
has_break = any('break' in bl.lower() for bl in body_lines)
found_var = f'_found_{id(body_lines)}' if has_break else None
if found_var: env[found_var] = block_assigns[found_var] = _const(dtypes.bool, False)
if found_var: vars[found_var] = block_assigns[found_var] = _const(dtypes.bool, False)
for loop_i in range(start_val, end_val + 1):
subst_lines = [_subst_loop_var(bl, loop_var, loop_i) for bl in body_lines if not (has_break and bl.strip().lower() == 'break')]
_, iter_assigns, _ = parse_block(subst_lines, 0, {**env, **block_assigns}, funcs, assigns)
_, iter_assigns, _ = parse_block(subst_lines, 0, {**vars, **block_assigns}, funcs, assigns)
if has_break:
assert found_var is not None
found = block_assigns.get(found_var, env.get(found_var))
found = block_assigns.get(found_var, vars.get(found_var))
assert isinstance(found, UOp)
not_found = found.eq(_const(dtypes.bool, False))
for var, val in iter_assigns.items():
if var != found_var and isinstance(val, UOp):
old = block_assigns.get(var, env.get(var, _u32(0)))
old = block_assigns.get(var, vars.get(var, _u32(0)))
if isinstance(old, UOp):
block_assigns[var] = env[var] = not_found.where(
val, old.cast(val.dtype) if val.dtype != old.dtype and val.dtype.itemsize == old.dtype.itemsize else old)
block_assigns[var] = vars[var] = not_found.where(val, old.cast(val.dtype) if val.dtype != old.dtype and val.dtype.itemsize == old.dtype.itemsize else old)
for j, bl in enumerate(body_lines):
bl_l = bl.strip().lower()
if bl_l.startswith('if ') and bl_l.endswith(' then'):
if any(body_lines[k].strip().lower() == 'break' for k in range(j+1, len(body_lines))):
cond_str = _subst_loop_var(bl.strip()[3:-5].strip(), loop_var, loop_i)
cond = _to_bool(parse_expr(cond_str, env, funcs))
block_assigns[found_var] = env[found_var] = not_found.where(cond, found)
cond = _to_bool(parse_expr(cond_str, vars, funcs))
block_assigns[found_var] = vars[found_var] = not_found.where(cond, found)
break
else:
block_assigns.update(iter_assigns)
env.update(iter_assigns)
block_assigns.update(iter_assigns); vars.update(iter_assigns)
continue
# declare
if first == 'declare':
# Initialize scalar declarations (skip arrays and env already passed as srcs)
# Initialize scalar declarations (skip arrays and vars already passed as srcs)
if '[' not in line and len(toks) >= 2 and toks[1].type == 'IDENT':
env.setdefault(toks[1].val, _u32(0))
i += 1
continue
vars.setdefault(toks[1].val, _u32(0))
i += 1; continue
# lambda definition
if first != '{' and '=' in line and 'lambda' in line and any(t.type == 'IDENT' and t.val == 'lambda' for t in toks):
@@ -945,30 +886,26 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
if ch == '(': depth += 1
elif ch == ')':
depth -= 1
if depth == 0:
body_lines_lst.append(lines[i][:j])
break
if depth == 0: body_lines_lst.append(lines[i][:j]); break
else: body_lines_lst.append(lines[i])
i += 1
body = '\n'.join(body_lines_lst).strip()
env[name] = ('lambda', params, body)
vars[name] = ('lambda', params, body)
continue
# MEM assignment: MEM[addr].type (+|-)?= value
if first == 'mem' and toks[1].type == 'LBRACKET':
j, addr_toks = _match_bracket(toks, 1)
addr = parse_tokens(addr_toks, env, funcs)
addr = parse_tokens(addr_toks, vars, funcs)
if j < len(toks) and toks[j].type == 'DOT': j += 1
dt_name = toks[j].val if j < len(toks) and toks[j].type == 'IDENT' else 'u32'
dt, j = DTYPES.get(dt_name, dtypes.uint32), j + 1
compound_op = None
if j < len(toks) and toks[j].type == 'ASSIGN_OP':
compound_op = toks[j].val
j += 1
if j < len(toks) and toks[j].type == 'ASSIGN_OP': compound_op = toks[j].val; j += 1
elif j < len(toks) and toks[j].type == 'EQUALS': j += 1
rhs = parse_tokens(toks[j:], env, funcs)
rhs = parse_tokens(toks[j:], vars, funcs)
if compound_op:
mem = env.get('_vmem') if '_vmem' in env else env.get('_lds')
mem = vars.get('_vmem') if '_vmem' in vars else vars.get('_lds')
if isinstance(mem, UOp):
adt = dtypes.uint64 if addr.dtype == dtypes.uint64 else dtypes.uint32
idx = (addr >> _const(adt, 2)).cast(dtypes.int)
@@ -977,8 +914,7 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
old = old.cast(dtypes.uint64) | (mem.index(((addr + _const(adt, 4)) >> _const(adt, 2)).cast(dtypes.int)).cast(dtypes.uint64) << _u64(32))
rhs = (old + rhs) if compound_op == '+=' else (old - rhs)
if assigns is not None: assigns.append((f'MEM[{_tok_str(addr_toks)}].{dt_name}', (addr, rhs)))
i += 1
continue
i += 1; continue
# VGPR assignment: VGPR[lane][reg] = value
if first == 'vgpr' and toks[1].type == 'LBRACKET':
@@ -987,12 +923,9 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
j, reg_toks = _match_bracket(toks, j)
if j < len(toks) and toks[j].type == 'DOT': j += 2 # skip .type suffix
if j < len(toks) and toks[j].type == 'EQUALS': j += 1
ln = parse_tokens(lane_toks, env, funcs)
rg, val = parse_tokens(reg_toks, env, funcs), parse_tokens(toks[j:], env, funcs)
if assigns is not None:
assigns.append((f'VGPR[{_tok_str(lane_toks)}][{_tok_str(reg_toks)}]', (_to_u32(rg) * _u32(32) + _to_u32(ln), val)))
i += 1
continue
ln, rg, val = parse_tokens(lane_toks, vars, funcs), parse_tokens(reg_toks, vars, funcs), parse_tokens(toks[j:], vars, funcs)
if assigns is not None: assigns.append((f'VGPR[{_tok_str(lane_toks)}][{_tok_str(reg_toks)}]', (_to_u32(rg) * _u32(32) + _to_u32(ln), val)))
i += 1; continue
# Compound destination: {hi.type, lo.type} = value
if first == '{':
@@ -1006,20 +939,18 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
j += 3
if j < len(toks) and toks[j].type == 'RBRACE': j += 1
if j < len(toks) and toks[j].type == 'EQUALS': j += 1
val = parse_tokens(toks[j:], env, funcs)
val = parse_tokens(toks[j:], vars, funcs)
lo_dt, hi_dt = DTYPES.get(lo_type, dtypes.uint64), DTYPES.get(hi_type, dtypes.uint32)
lo_bits = 64 if lo_dt in (dtypes.uint64, dtypes.int64) else 32
lo_val = val.cast(lo_dt) if val.dtype.itemsize * 8 <= lo_bits else (val & _const(val.dtype, (1 << lo_bits) - 1)).cast(lo_dt)
hi_val = (val >> _const(val.dtype, lo_bits)).cast(hi_dt)
block_assigns[lo_var] = env[lo_var] = lo_val
block_assigns[hi_var] = env[hi_var] = hi_val
block_assigns[lo_var] = vars[lo_var] = lo_val
block_assigns[hi_var] = vars[hi_var] = hi_val
if assigns is not None: assigns.extend([(f'{lo_var}.{lo_type}', lo_val), (f'{hi_var}.{hi_type}', hi_val)])
i += 1
continue
i += 1; continue
# Bit slice/index: var[hi:lo] = value, var.type[hi:lo] = value, or var[expr] = value
if len(toks) >= 5 and toks[0].type == 'IDENT' and \
(toks[1].type == 'LBRACKET' or (toks[1].type == 'DOT' and toks[3].type == 'LBRACKET')):
if len(toks) >= 5 and toks[0].type == 'IDENT' and (toks[1].type == 'LBRACKET' or (toks[1].type == 'DOT' and toks[3].type == 'LBRACKET')):
bracket_start = 2 if toks[1].type == 'LBRACKET' else 4
j = bracket_start
colon_pos = None
@@ -1036,28 +967,23 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
j += 1
if j < len(toks) and toks[j].type == 'DOT': j += 2
if j < len(toks) and toks[j].type == 'EQUALS': j += 1
val = parse_tokens(toks[j:], env, funcs)
val = parse_tokens(toks[j:], vars, funcs)
dt_suffix = toks[2].val if toks[1].type == 'DOT' else None
if assigns is not None: assigns.append((f'{var}[{hi}:{lo}]' + (f'.{dt_suffix}' if dt_suffix else ''), val))
if var not in env: env[var] = _const(dtypes.uint64 if hi >= 32 else dtypes.uint32, 0)
old = block_assigns.get(var, env.get(var))
assert isinstance(old, UOp)
block_assigns[var] = env[var] = _set_bits(old, _val_to_bits(val), hi - lo + 1, lo)
i += 1
continue
except Exception: pass
if var not in vars: vars[var] = _const(dtypes.uint64 if hi >= 32 else dtypes.uint32, 0)
old = block_assigns.get(var, vars.get(var))
block_assigns[var] = vars[var] = _set_bits(old, _val_to_bits(val), hi - lo + 1, lo)
i += 1; continue
except: pass
elif toks[1].type == 'LBRACKET': # bit index: var[expr] (only for var[...], not var.type[...])
existing = block_assigns.get(var, env.get(var))
if existing is not None and isinstance(existing, UOp) and \
not any(f'{var}{k}' in env or f'{var}{k}' in block_assigns for k in range(8)):
existing = block_assigns.get(var, vars.get(var))
if existing is not None and isinstance(existing, UOp) and not any(f'{var}{k}' in vars or f'{var}{k}' in block_assigns for k in range(8)):
bit_toks = toks[2:j]
j += 1
while j < len(toks) and toks[j].type != 'EQUALS': j += 1
if j < len(toks):
block_assigns[var] = env[var] = _set_bit(
existing, _to_u32(parse_tokens(bit_toks, env, funcs)), parse_tokens(toks[j+1:], env, funcs))
i += 1
continue
block_assigns[var] = vars[var] = _set_bit(existing, _to_u32(parse_tokens(bit_toks, vars, funcs)), parse_tokens(toks[j+1:], vars, funcs))
i += 1; continue
# Array element: var[idx] = value (static index) or var[expr] = value (dynamic)
if len(toks) >= 4 and toks[0].type == 'IDENT' and toks[1].type == 'LBRACKET':
@@ -1067,90 +993,80 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
# Static index: var[NUM] = value
if len(idx_toks) == 1 and idx_toks[0].type == 'NUM':
idx = int(idx_toks[0].val.rstrip('UuLl'))
val = parse_tokens(toks[j+1:], env, funcs)
existing = block_assigns.get(var, env.get(var))
val = parse_tokens(toks[j+1:], vars, funcs)
existing = block_assigns.get(var, vars.get(var))
if existing is not None and isinstance(existing, UOp):
block_assigns[var] = env[var] = _set_bit(existing, _u32(idx), val)
block_assigns[var] = vars[var] = _set_bit(existing, _u32(idx), val)
else:
block_assigns[f'{var}@{idx}'] = env[f'{var}@{idx}'] = val
i += 1
continue
block_assigns[f'{var}@{idx}'] = vars[f'{var}@{idx}'] = val
i += 1; continue
# Dynamic index: var[expr] = value where var has @-elements
elems = [(k.split('@')[1], v) for k, v in {**env, **block_assigns}.items() if k.startswith(f'{var}@') and isinstance(v, UOp)]
elems = [(k.split('@')[1], v) for k, v in {**vars, **block_assigns}.items() if k.startswith(f'{var}@') and isinstance(v, UOp)]
if elems:
idx_expr = parse_tokens(idx_toks, env, funcs)
val = parse_tokens(toks[j+1:], env, funcs)
idx_expr = parse_tokens(idx_toks, vars, funcs)
val = parse_tokens(toks[j+1:], vars, funcs)
for elem_idx_str, old_elem in elems:
elem_idx = int(elem_idx_str)
cond = _to_u32(idx_expr).eq(_u32(elem_idx))
new_val = cond.where(val.cast(old_elem.dtype) if val.dtype != old_elem.dtype else val, old_elem)
block_assigns[f'{var}@{elem_idx}'] = env[f'{var}@{elem_idx}'] = new_val
i += 1
continue
block_assigns[f'{var}@{elem_idx}'] = vars[f'{var}@{elem_idx}'] = new_val
i += 1; continue
# Compound assignment: var += or var -=
assign_op = next((j for j, t in enumerate(toks) if t.type == 'ASSIGN_OP'), None)
if assign_op is not None:
var = toks[0].val
old = block_assigns.get(var, env.get(var, _u32(0)))
rhs = parse_tokens(toks[assign_op+1:], env, funcs)
old = block_assigns.get(var, vars.get(var, _u32(0)))
rhs = parse_tokens(toks[assign_op+1:], vars, funcs)
if rhs.dtype != old.dtype: rhs = rhs.cast(old.dtype)
block_assigns[var] = env[var] = (old + rhs) if toks[assign_op].val == '+=' else (old - rhs)
i += 1
continue
block_assigns[var] = vars[var] = (old + rhs) if toks[assign_op].val == '+=' else (old - rhs)
i += 1; continue
# Typed element: var.type[idx] = value
if len(toks) >= 7 and toks[0].type == 'IDENT' and toks[1].type == 'DOT' and \
toks[2].type == 'IDENT' and toks[3].type == 'LBRACKET' and toks[4].type == 'NUM':
if len(toks) >= 7 and toks[0].type == 'IDENT' and toks[1].type == 'DOT' and toks[2].type == 'IDENT' and toks[3].type == 'LBRACKET' and toks[4].type == 'NUM':
var, dt_name, idx = toks[0].val, toks[2].val, int(toks[4].val)
dt = DTYPES.get(dt_name, dtypes.uint32)
j = 6
while j < len(toks) and toks[j].type != 'EQUALS': j += 1
if j < len(toks):
val, old = parse_tokens(toks[j+1:], env, funcs), block_assigns.get(var, env.get(var, _u32(0)))
val, old = parse_tokens(toks[j+1:], vars, funcs), block_assigns.get(var, vars.get(var, _u32(0)))
bw = dt.itemsize * 8
block_assigns[var] = env[var] = _set_bits(old, val, bw, idx * bw)
block_assigns[var] = vars[var] = _set_bits(old, val, bw, idx * bw)
if assigns is not None: assigns.append((f'{var}.{dt_name}[{idx}]', val))
i += 1
continue
i += 1; continue
# Dynamic bit: var.type[expr_with_brackets] = value
if len(toks) >= 5 and toks[0].type == 'IDENT' and toks[1].type == 'DOT' and \
toks[2].type == 'IDENT' and toks[3].type == 'LBRACKET':
if len(toks) >= 5 and toks[0].type == 'IDENT' and toks[1].type == 'DOT' and toks[2].type == 'IDENT' and toks[3].type == 'LBRACKET':
j, depth, has_inner = 4, 1, False
while j < len(toks) and depth > 0:
if toks[j].type == 'LBRACKET':
depth += 1
has_inner = True
if toks[j].type == 'LBRACKET': depth += 1; has_inner = True
elif toks[j].type == 'RBRACKET': depth -= 1
j += 1
if has_inner:
var = toks[0].val
bit_pos = _to_u32(parse_tokens(toks[4:j-1], env, funcs))
bit_pos = _to_u32(parse_tokens(toks[4:j-1], vars, funcs))
while j < len(toks) and toks[j].type != 'EQUALS': j += 1
if j < len(toks):
val = parse_tokens(toks[j+1:], env, funcs)
old = block_assigns.get(var, env.get(var, _u32(0)))
block_assigns[var] = env[var] = _set_bit(old, bit_pos, val)
i += 1
continue
val = parse_tokens(toks[j+1:], vars, funcs)
old = block_assigns.get(var, vars.get(var, _u32(0)))
block_assigns[var] = vars[var] = _set_bit(old, bit_pos, val)
i += 1; continue
# If/elsif/else - skip branches with statically false conditions (WAVE32/WAVE64)
if first == 'if':
def parse_cond(s, kw):
ll = s.lower()
return _to_bool(parse_expr(s[ll.find(kw) + len(kw):ll.rfind('then')].strip(), env, funcs))
return _to_bool(parse_expr(s[ll.find(kw) + len(kw):ll.rfind('then')].strip(), vars, funcs))
def is_const(c, v): return c.op == Ops.CONST and c.arg is v
cond = parse_cond(line, 'if')
conditions: list[tuple[UOp, UOp | dict[str, VarVal] | None]] = [(cond, None)] if not is_const(cond, False) else []
else_branch: tuple[UOp | None, dict[str, VarVal]] = (None, {})
env_snap = dict(env)
vars_snap = dict(vars)
static_true = is_const(cond, True) # track if any condition is statically true
i += 1
i, branch, ret = parse_block(lines, i, env, funcs, assigns if not is_const(cond, False) else None)
i, branch, ret = parse_block(lines, i, vars, funcs, assigns if not is_const(cond, False) else None)
if conditions: conditions[0] = (cond, ret if ret is not None else branch)
env.clear()
env.update(env_snap)
vars.clear(); vars.update(vars_snap)
while i < len(lines):
ltoks = tokenize(lines[i])
if ltoks[0].type != 'IDENT': break
@@ -1158,22 +1074,17 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
if lf == 'elsif':
c = parse_cond(lines[i], 'elsif')
take = not static_true and not is_const(c, False)
i += 1
i, branch, ret = parse_block(lines, i, env, funcs, assigns if take else None)
i += 1; i, branch, ret = parse_block(lines, i, vars, funcs, assigns if take else None)
if take:
conditions.append((c, ret if ret is not None else branch))
if is_const(c, True): static_true = True
env.clear()
env.update(env_snap)
vars.clear(); vars.update(vars_snap)
elif lf == 'else':
i += 1
i, branch, ret = parse_block(lines, i, env, funcs, assigns if not static_true else None)
i, branch, ret = parse_block(lines, i, vars, funcs, assigns if not static_true else None)
if not static_true: else_branch = (ret, branch)
env.clear()
env.update(env_snap)
elif lf == 'endif':
i += 1
break
vars.clear(); vars.update(vars_snap)
elif lf == 'endif': i += 1; break
else: break
# Check if any branch returned a value (lambda-style)
if any(isinstance(br, UOp) for _, br in conditions):
@@ -1186,19 +1097,18 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
# If statically true, use that branch directly; otherwise merge with WHERE
if static_true:
ba = next((b for c, b in conditions if is_const(c, True) and isinstance(b, dict)), {})
block_assigns.update(ba)
env.update(ba)
block_assigns.update(ba); vars.update(ba)
else:
else_assigns = else_branch[1]
all_vars = set().union(*[ba.keys() for _, ba in conditions if isinstance(ba, dict)], else_assigns.keys())
for var in all_vars:
res: Any = else_assigns.get(var, block_assigns.get(var, env.get(var, _u32(0))))
for cond, ba in reversed(conditions): # type: ignore[assignment]
res: Any = else_assigns.get(var, block_assigns.get(var, vars.get(var, _u32(0))))
for cond, ba in reversed(conditions):
if isinstance(ba, dict) and var in ba:
tv = ba[var]
if isinstance(tv, UOp) and isinstance(res, UOp):
res = cond.where(tv, res.cast(tv.dtype) if tv.dtype != res.dtype and tv.dtype.itemsize == res.dtype.itemsize else res)
block_assigns[var] = env[var] = res
block_assigns[var] = vars[var] = res
continue
# Regular assignment: var = value
@@ -1206,12 +1116,11 @@ def parse_block(lines: list[str], start: int, env: dict[str, VarVal], funcs: dic
if t.type == 'EQUALS':
if any(toks[k].type == 'OP' and toks[k].val in ('<', '>', '!', '=') for k in range(j)): break
base_var = toks[0].val
block_assigns[base_var] = env[base_var] = parse_tokens(toks[j+1:], env, funcs)
i += 1
break
block_assigns[base_var] = vars[base_var] = parse_tokens(toks[j+1:], vars, funcs)
i += 1; break
else: i += 1
return i, block_assigns, None
def parse_expr(expr: str, env: dict[str, VarVal], funcs: dict | None = None) -> UOp:
return parse_tokens(tokenize(expr.strip().rstrip(';')), env, funcs)
def parse_expr(expr: str, vars: dict[str, VarVal], funcs: dict | None = None) -> UOp:
return parse_tokens(tokenize(expr.strip().rstrip(';')), vars, funcs)
@@ -5,11 +5,9 @@ The format is nibble-based with variable-width packets determined by a state mac
Uses BitField infrastructure from dsl.py, similar to GPU instruction encoding.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Iterator
from enum import Enum
from tinygrad.renderer.amd.dsl import BitField, FixedBitField, Inst, bits
from tinygrad.runtime.autogen.amd.rdna3.ins import s_endpgm # same encoding as RDNA4
from extra.assembly.amd.dsl import BitField, FixedBitField, bits
# ═══════════════════════════════════════════════════════════════════════════════
# FIELD ENUMS
@@ -46,7 +44,6 @@ class InstOp(Enum):
SMEM = 0x1
JUMP = 0x3 # branch taken
JUMP_NO = 0x4 # branch not taken
CALL = 0x5 # s_call_b64
MESSAGE = 0x9
VALU_TRANS = 0xb # transcendental: exp, log, rcp, sqrt, sin, cos
VALU_64_SHIFT = 0xd # 64-bit shifts: lshl, lshr, ashr
@@ -73,10 +70,8 @@ class InstOp(Enum):
# LDS ops on traced SIMD
LDS_LOAD = 0x29
LDS_ATOMIC = 0x2a # ds_append, ds_consume, ds_store_addtid_b32
LDS_STORE = 0x2b
LDS_STORE_64 = 0x2c
LDS_STORE_96 = 0x2d
LDS_STORE_128 = 0x2e
# Memory ops on other SIMD (0x5x range)
@@ -100,41 +95,20 @@ class InstOp(Enum):
SALU_SAVEEXEC = 0x72 # s_*_saveexec_b32/b64
VALU_CMPX = 0x73 # v_cmpx_*
class InstOpRDNA4(Enum):
class InstOpL4(Enum):
"""SQTT instruction operation types for RDNA4 (gfx1200). Different encoding from RDNA3."""
# TODO: we need to do discovery of all of these from instructions
SALU = 0x0
SMEM = 0x1
JUMP = 0x3
UNK_02 = 0x2
JUMP_NO = 0x4
JUMP_UNCOND = 0x5
MESSAGE = 0x9
VALU_TRANS = 0xb
VALU_B2 = 0xd
VALU_B4 = 0xe
UNK_06 = 0x6
VMEM = 0x10
UNK_11 = 0x11
VINTERP = 0x12
VMEM_RD_1 = 0x21
VMEM_RD_2 = 0x22
VMEM_WR_1 = 0x23
VMEM_WR_2 = 0x24
VMEM_WR_3 = 0x25
VMEM_WR_4 = 0x26
VMEM_WR_5 = 0x27
VMEM_WR_6 = 0x28
LDS_RD = 0x29
LDS_WR_1 = 0x2a
LDS_WR_2 = 0x2b
LDS_WR_3 = 0x2c
LDS_WR_4 = 0x2d
LDS_WR_5 = 0x2e
WMMA_8 = 0x8c
WMMA_16 = 0x8d
VALU_DPFP = 0x92
SALU_FLOAT3 = 0x98
VALU_SCL_TRANS = 0x99
SALU_2 = 0x9b
SALU_5 = 0x9c
OTHER_VMEM = 0xbd
OTHER_VMEM_5 = 0xc1
UNK_14 = 0x14
OTHER_VMEM = 0x5e
UNK_60 = 0x60
# ═══════════════════════════════════════════════════════════════════════════════
# PACKET TYPE BASE CLASS
@@ -148,8 +122,8 @@ class PacketType:
def __init_subclass__(cls, **kwargs):
super().__init_subclass__(**kwargs)
cls._fields = {k: v for k, v in cls.__dict__.items() if isinstance(v, BitField)} # type: ignore[attr-defined]
cls._size_nibbles = ((max((f.hi for f in cls._fields.values()), default=0) + 4) // 4) # type: ignore[attr-defined]
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):
@@ -158,7 +132,7 @@ class PacketType:
return inst
def __repr__(self) -> str:
fields_str = ", ".join(f"{k}={getattr(self, k)}" for k in self._fields if not k.startswith('_') and k != 'encoding') # type: ignore[attr-defined]
fields_str = ", ".join(f"{k}={getattr(self, k)}" for k in self._fields if not k.startswith('_') and k != 'encoding')
return f"{self.__class__.__name__}({fields_str})"
# ═══════════════════════════════════════════════════════════════════════════════
@@ -170,12 +144,17 @@ class TS_DELTA_S8_W3(PacketType):
delta = bits[10:8]
_padding = bits[63:11]
class TS_DELTA_S8_W3_L4(PacketType): # Layout 4: 64->72 bits
encoding = bits[6:0] == 0b0100001
delta = bits[10:8]
_padding = bits[71:11]
class TS_DELTA_S5_W3(PacketType):
encoding = bits[4:0] == 0b00110
delta = bits[7:5]
_padding = bits[51:8]
class TS_DELTA_S5_W3_RDNA4(PacketType): # Layout 4: 52->56 bits
class TS_DELTA_S5_W3_L4(PacketType): # Layout 4: 52->56 bits
encoding = bits[4:0] == 0b00110
delta = bits[9:7]
_padding = bits[55:10]
@@ -192,7 +171,7 @@ class TS_DELTA_OR_MARK(PacketType):
@property
def is_marker(self) -> bool: return bool(self.bit9 and not self.bit8)
class TS_DELTA_OR_MARK_RDNA4(PacketType): # Layout 4: 48->64 bits
class TS_DELTA_OR_MARK_L4(PacketType): # Layout 4: 48->64 bits
encoding = bits[6:0] == 0b0000001
delta = bits[63:12]
bit7 = bits[7:7]
@@ -206,7 +185,7 @@ class TS_DELTA_S5_W2(PacketType):
delta = bits[6:5]
_padding = bits[47:7]
class TS_DELTA_S5_W2_RDNA4(PacketType): # Layout 4: 48->40 bits
class TS_DELTA_S5_W2_L4(PacketType): # Layout 4: 48->40 bits
encoding = bits[4:0] == 0b11100
delta = bits[6:5]
_padding = bits[39:7]
@@ -267,7 +246,7 @@ class WAVESTART(PacketType): # exclude: 1 << 4
@property
def cu(self) -> int: return self.cu_lo | (self.flag7 << 3)
class WAVESTART_RDNA4(PacketType): # Layout 4 has wave field at different position
class WAVESTART_L4(PacketType): # Layout 4 has wave field at different position
encoding = bits[4:0] == 0b01100
delta = bits[6:5]
flag7 = bits[7:7]
@@ -283,7 +262,7 @@ class WAVEALLOC(PacketType): # exclude: 1 << 10
delta = bits[7:5]
_padding = bits[19:8]
class WAVEALLOC_RDNA4(PacketType): # Layout 4: 20->24 bits
class WAVEALLOC_L4(PacketType): # Layout 4: 20->24 bits
encoding = bits[4:0] == 0b00101
delta = bits[7:5]
_padding = bits[23:8]
@@ -293,7 +272,7 @@ class PERF(PacketType): # exclude: 1 << 11
delta = bits[7:5]
arg = bits[27:8]
class PERF_RDNA4(PacketType): # Layout 4: 28->32 bits
class PERF_L4(PacketType): # Layout 4: 28->32 bits
encoding = bits[4:0] == 0b10110
delta = bits[9:7]
arg = bits[31:10]
@@ -356,12 +335,13 @@ class INST(PacketType):
wave = bits[12:8]
op = bits[19:13].enum(InstOp)
class INST_RDNA4(PacketType): # Layout 4: different delta position and InstOp encoding
class INST_L4(PacketType): # Layout 4: different delta position and InstOp encoding
encoding = bits[2:0] == 0b010
delta = bits[5:3]
w64h = bits[6:6]
wave = bits[11:7]
op = bits[19:12].enum(InstOpRDNA4)
flag1 = bits[6:6]
flag2 = bits[7:7]
wave = bits[12:8]
op = bits[19:13].enum(InstOpL4)
class UTILCTR(PacketType):
encoding = bits[6:0] == 0b0110001
@@ -369,179 +349,40 @@ class UTILCTR(PacketType):
ctr = bits[47:9]
# Packet types with rocprof type IDs as keys
PACKET_TYPES_RDNA3: dict[int, type[PacketType]] = {
PACKET_TYPES_L3: dict[int, type[PacketType]] = {
1: VALUINST, 2: VMEMEXEC, 3: ALUEXEC, 4: IMMEDIATE, 5: IMMEDIATE_MASK, 6: WAVERDY, 7: TS_DELTA_S8_W3, 8: WAVEEND,
9: WAVESTART, 10: TS_DELTA_S5_W2, 11: WAVEALLOC, 12: TS_DELTA_S5_W3, 13: PERF, 14: UTILCTR, 15: TS_DELTA_SHORT,
16: NOP, 17: TS_WAVE_STATE, 18: EVENT, 19: EVENT_BIG, 20: REG, 21: SNAPSHOT, 22: TS_DELTA_OR_MARK, 23: LAYOUT_HEADER, 24: INST,
}
PACKET_TYPES_RDNA4: dict[int, type[PacketType]] = {
**PACKET_TYPES_RDNA3,
9: WAVESTART_RDNA4, 10: TS_DELTA_S5_W2_RDNA4, 11: WAVEALLOC_RDNA4,
12: TS_DELTA_S5_W3_RDNA4, 13: PERF_RDNA4, 22: TS_DELTA_OR_MARK_RDNA4, 24: INST_RDNA4,
PACKET_TYPES_L4: dict[int, type[PacketType]] = {
**PACKET_TYPES_L3,
7: TS_DELTA_S8_W3_L4, 9: WAVESTART_L4, 10: TS_DELTA_S5_W2_L4, 11: WAVEALLOC_L4,
12: TS_DELTA_S5_W3_L4, 13: PERF_L4, 22: TS_DELTA_OR_MARK_L4, 24: INST_L4,
}
# ═══════════════════════════════════════════════════════════════════════════════
# CDNA PACKET TYPE DEFINITIONS
# ═══════════════════════════════════════════════════════════════════════════════
class CDNA_DELTA(PacketType):
"""pkt_fmt=0: 16-bit timestamp delta packet"""
encoding = bits[3:0] == 0
delta = bits[11:4] # (data >> 4) & 0xff
unk_0 = bits[12:12] # (data >> 0xc) & 1
unk_1 = bits[15:13] # (data >> 0xd)
class CDNA_TIMESTAMP(PacketType):
"""pkt_fmt=1: 64-bit timestamp packet (case 0x0)"""
encoding = bits[3:0] == 1
unk_0 = bits[15:4]
timestamp = bits[63:16] # stored as (data_word >> 0x10) in low 46 bits of local_58
class CDNA_PKT_2(PacketType):
"""pkt_fmt=2: 64-bit packet (case 0x4)"""
encoding = bits[3:0] == 2
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_padding = bits[63:8]
class CDNA_WAVESTART(PacketType):
"""pkt_fmt=3: 32-bit WAVESTART packet (case 0x8)"""
encoding = bits[3:0] == 3
unk_0 = bits[5:5] # (data >> 5) & 1
unk_1 = bits[9:6] # (data >> 6) & 0xf
wave = bits[13:10] # (data >> 10) & 0xf
simd = bits[15:14] # (data >> 0xe) & 3
cu = bits[17:16] # (data >> 0x10) & 3
unk_5 = bits[19:18] # (data >> 0x12) & 3
unk_6 = bits[28:22] # (data >> 0x16) & 0x7f
unk_padding = bits[31:29]
class CDNA_PKT_4(PacketType):
"""pkt_fmt=4: 16-bit packet (case 0xc, same as 0x8/0x14)"""
encoding = bits[3:0] == 4
unk_0 = bits[5:5] # (data_word >> 5) & 1
unk_1 = bits[9:6] # (data_word >> 6) & 0xf
unk_2 = bits[13:10] # (data_word >> 10) & 0xf
unk_3 = bits[15:14] # (data_word >> 0xe)
class CDNA_PKT_5(PacketType):
"""pkt_fmt=5: 48-bit packet (case 0x10)"""
encoding = bits[3:0] == 5
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_2 = bits[15:9] # (data >> 9) & 0x7f
unk_padding = bits[47:16]
class CDNA_WAVEEND(PacketType):
"""pkt_fmt=6: 16-bit WAVEEND packet (case 0x14, same as 0x8/0xc)"""
encoding = bits[3:0] == 6
unk_0 = bits[5:5] # (data_word >> 5) & 1
unk_1 = bits[9:6] # (data_word >> 6) & 0xf
wave = bits[13:10] # (data_word >> 10) & 0xf
simd = bits[15:14] # (data_word >> 0xe)
class CDNA_EXEC(PacketType):
"""pkt_fmt=10: 16-bit EXEC packet (case 0x24)"""
encoding = bits[3:0] == 10
unk_0 = bits[8:5] # (data_word >> 5) & 0xf
unk_1 = bits[10:9] # (data_word >> 9) & 3
unk_2 = bits[15:11] # (data_word >> 0xb)
class CDNA_PKT_11(PacketType):
"""pkt_fmt=11: 64-bit packet (case 0x28)"""
encoding = bits[3:0] == 11
unk_0 = bits[8:5] # (data_word >> 5) & 0xf
unk_1 = bits[10:9] # (data_word >> 9) & 3
unk_2 = bits[15:15] # (data_word >> 0xf) & 1
unk_padding = bits[63:16]
class CDNA_INST(PacketType):
"""pkt_fmt=13: 32-bit INST packet (case 0x30)"""
encoding = bits[3:0] == 13
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[9:8] # (data >> 8) & 3
unk_2 = bits[11:10] # (data >> 10) & 3
unk_3 = bits[13:12] # (data >> 0xc) & 3
unk_4 = bits[15:14] # (data >> 0xe) & 3
unk_5 = bits[19:18] # (data >> 0x12) & 3
unk_6 = bits[21:20] # (data >> 0x14) & 3
unk_7 = bits[23:22] # (data >> 0x16) & 3
unk_8 = bits[25:24] # (data >> 0x18) & 3
unk_9 = bits[27:26] # (data >> 0x1a) & 3
unk_padding = bits[31:28]
class CDNA_PKT_14(PacketType):
"""pkt_fmt=14: 64-bit packet (case 0x34)"""
encoding = bits[3:0] == 14
unk_0 = bits[5:5] # (data >> 5) & 1
unk_1 = bits[9:6] # (data >> 6) & 0xf
unk_2 = bits[11:10] # (data >> 10) & 3
unk_3 = bits[24:12] # (data >> 0xc) & 0x1fff
unk_4 = bits[37:25] # (data >> 0x19) & 0x1fff
unk_5 = bits[50:38] # (data >> 0x26) & 0x1fff
unk_6 = bits[51:51] # (data >> 0x33) & 1
unk_padding = bits[63:52]
class CDNA_PKT_7(PacketType):
"""pkt_fmt=7: 16-bit packet"""
encoding = bits[3:0] == 7
unk_padding = bits[15:4]
class CDNA_PKT_8(PacketType):
"""pkt_fmt=8: 16-bit packet"""
encoding = bits[3:0] == 8
unk_padding = bits[15:4]
class CDNA_PKT_9(PacketType):
"""pkt_fmt=9: 16-bit packet"""
encoding = bits[3:0] == 9
unk_padding = bits[15:4]
class CDNA_PKT_12(PacketType):
"""pkt_fmt=12: 48-bit packet"""
encoding = bits[3:0] == 12
unk_padding = bits[47:4]
class CDNA_PKT_15(PacketType):
"""pkt_fmt=15: 48-bit packet (case 0x38, same as 0x10)"""
encoding = bits[3:0] == 15
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_2 = bits[15:9] # (data >> 9) & 0x7f
unk_padding = bits[47:16]
PACKET_TYPES_CDNA: dict[int, type[PacketType]] = {
0: CDNA_DELTA, 1: CDNA_TIMESTAMP, 2: CDNA_PKT_2, 3: CDNA_WAVESTART, 4: CDNA_PKT_4, 5: CDNA_PKT_5, 6: CDNA_WAVEEND,
7: CDNA_PKT_7, 8: CDNA_PKT_8, 9: CDNA_PKT_9, 10: CDNA_EXEC, 11: CDNA_PKT_11, 12: CDNA_PKT_12,
13: CDNA_INST, 14: CDNA_PKT_14, 15: CDNA_PKT_15,
}
# ═══════════════════════════════════════════════════════════════════════════════
# DECODER
# ═══════════════════════════════════════════════════════════════════════════════
def _build_decode_tables(packet_types: dict[int, type[PacketType]]) -> tuple[dict[int, tuple], bytes]:
# Build state table: byte -> opcode. Sort by mask specificity (more bits first), NOP last
sorted_types = sorted(packet_types.items(), key=lambda x: (-bin(x[1].encoding.mask).count('1'), x[0] == 16))
state_table = bytes(next((op for op, cls in sorted_types if (b & cls.encoding.mask) == cls.encoding.default), 16) for b in range(256))
# Build decode info: opcode -> (pkt_cls, nib_count, delta_lo, delta_mask, special_case)
# special_case: 0=none, 1=TS_DELTA_OR_MARK (check is_marker), 2=TS_DELTA_SHORT (add 8), 3=CDNA_DELTA (*4), 4=CDNA_TIMESTAMP (absolute)
_special = {TS_DELTA_OR_MARK: 1, TS_DELTA_OR_MARK_RDNA4: 1, TS_DELTA_SHORT: 2, CDNA_DELTA: 3, CDNA_TIMESTAMP: 4}
# special_case: 0=none, 1=TS_DELTA_OR_MARK (check is_marker), 2=TS_DELTA_SHORT (add 8)
decode_info = {}
for opcode, pkt_cls in packet_types.items():
delta_field = getattr(pkt_cls, 'delta', None)
special = _special.get(pkt_cls, 0)
decode_info[opcode] = (pkt_cls, pkt_cls._size_nibbles, delta_field.lo if delta_field else 0, delta_field.mask if delta_field else 0, special) # type: ignore[attr-defined]
special = {22: 1, 15: 2}.get(opcode, 0) # TS_DELTA_OR_MARK=22, TS_DELTA_SHORT=15
decode_info[opcode] = (pkt_cls, pkt_cls._size_nibbles, delta_field.lo if delta_field else 0, delta_field.mask if delta_field else 0, special)
return decode_info, state_table
_DECODE_INFO_RDNA3, _STATE_TABLE_RDNA3 = _build_decode_tables(PACKET_TYPES_RDNA3)
_DECODE_INFO_RDNA4, _STATE_TABLE_RDNA4 = _build_decode_tables(PACKET_TYPES_RDNA4)
_DECODE_INFO_CDNA, _STATE_TABLE_CDNA = _build_decode_tables(PACKET_TYPES_CDNA)
_DECODE_INFO_L3, _STATE_TABLE_L3 = _build_decode_tables(PACKET_TYPES_L3)
_DECODE_INFO_L4, _STATE_TABLE_L4 = _build_decode_tables(PACKET_TYPES_L4)
# ═══════════════════════════════════════════════════════════════════════════════
# DECODER
# ═══════════════════════════════════════════════════════════════════════════════
def decode(data: bytes) -> Iterator[PacketType]:
"""Decode raw SQTT blob, yielding packet instances. Auto-detects RDNA (layout 3/4) vs CDNA."""
n, reg, pos, nib_off, nib_count, time, ts_offset = len(data), 0, 0, 0, 16, 0, None
decode_info, state_table = _DECODE_INFO_RDNA3, _STATE_TABLE_RDNA3 # start RDNA3, auto-detect switches if needed
"""Decode raw SQTT blob, yielding packet instances. Auto-detects layout from LAYOUT_HEADER."""
n, reg, pos, nib_off, nib_count, time = len(data), 0, 0, 0, 16, 0
decode_info, state_table = _DECODE_INFO_L3, _STATE_TABLE_L3 # default to layout 3, will update after seeing LAYOUT_HEADER
while pos + ((nib_count + nib_off + 1) >> 1) <= n:
need = nib_count - nib_off
@@ -549,9 +390,8 @@ def decode(data: bytes) -> Iterator[PacketType]:
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):
read_bytes = min(byte_count, 8)
chunk = int.from_bytes(data[pos:pos + read_bytes], 'little')
reg, pos = (reg >> (read_bytes * 8)) | (chunk << (64 - read_bytes * 8)), pos + byte_count
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)
@@ -562,83 +402,14 @@ def decode(data: bytes) -> Iterator[PacketType]:
pkt = pkt_cls.from_raw(reg, 0) # create packet to check is_marker
if pkt.is_marker: delta = 0
elif special == 2: delta += 8 # TS_DELTA_SHORT
elif special == 3: delta *= 4 # CDNA_DELTA
elif special == 4: # CDNA_TIMESTAMP (absolute timestamp anchoring)
if (reg >> 4) & 0xfff == 0: # unk_0 == 0 means absolute timestamp
abs_ts = reg >> 16
if ts_offset is None: ts_offset = abs_ts - time
else: time = ((abs_ts - ts_offset) & ~3) - 4
delta = 0
time += delta
pkt = pkt_cls.from_raw(reg, time)
# auto-detect: first packet is always LAYOUT_HEADER (RDNA layout 3/4) or misdetected (CDNA)
if pkt_cls is LAYOUT_HEADER:
if pkt.layout == 4: decode_info, state_table = _DECODE_INFO_RDNA4, _STATE_TABLE_RDNA4
elif pkt.layout != 3: # not a real LAYOUT_HEADER — switch to CDNA and re-decode first packet
decode_info, state_table = _DECODE_INFO_CDNA, _STATE_TABLE_CDNA
opcode = state_table[reg & 0xFF]
pkt_cls, nib_count, delta_lo, delta_mask, special = decode_info[opcode]
if special == 4 and (reg >> 4) & 0xfff == 0: # CDNA_TIMESTAMP absolute
ts_offset = (reg >> 16) - time
pkt = pkt_cls.from_raw(reg, time)
# detect layout from first LAYOUT_HEADER and switch decode tables if needed
# NOTE: CDNA uses a completely different 16-bit header format, not nibbles - not supported here
if pkt_cls is LAYOUT_HEADER and pkt.layout == 4:
decode_info, state_table = _DECODE_INFO_L4, _STATE_TABLE_L4
yield pkt
# ═══════════════════════════════════════════════════════════════════════════════
# MAPPER
# ═══════════════════════════════════════════════════════════════════════════════
@dataclass(frozen=True)
class InstructionInfo:
pc: int
wave: int
inst: Inst
def map_insts(data:bytes, lib:bytes, target:str) -> Iterator[tuple[PacketType, InstructionInfo|None]]:
"""maps SQTT packets to instructions, yields (packet, instruction_info or None)"""
# map pcs to insts
from tinygrad.viz.serve import amd_decode
pc_map = amd_decode(lib, target)
wave_pc:dict[int, int] = {}
# only processing packets on one [CU, SIMD] unit
def simd_select(p) -> bool: return getattr(p, "cu", 0) == 0 and getattr(p, "simd", 0) == 0
for p in decode(data):
if not simd_select(p): continue
if isinstance(p, (WAVESTART, WAVESTART_RDNA4)):
assert p.wave not in wave_pc, "only one inflight wave per unit"
wave_pc[p.wave] = next(iter(pc_map))
elif isinstance(p, WAVEEND):
pc = wave_pc.pop(p.wave)
yield (p, InstructionInfo(pc, p.wave, s_endpgm()))
# skip OTHER_ instructions, they don't belong to this unit
elif isinstance(p, (INST, INST_RDNA4)) and p.op.name.startswith("OTHER_"): pass
elif isinstance(p, IMMEDIATE_MASK):
# immediate mask may yield multiple times per packet
for wave in range(16):
if p.mask & (1 << wave):
inst = pc_map[pc:=wave_pc[wave]]
# can this assert be more strict?
assert type(inst).__name__ == "SOPP", f"IMMEDIATE_MASK packet must map to SOPP, got {inst}"
wave_pc[wave] += inst.size()
yield (p, InstructionInfo(pc, wave, inst))
elif isinstance(p, (VALUINST, INST, INST_RDNA4, IMMEDIATE)):
inst = pc_map[pc:=wave_pc[p.wave]]
# s_delay_alu and s_wait_alu instructions are skipped
while (inst_op:=getattr(inst, 'op_name', '')) in {"S_DELAY_ALU", "S_WAIT_ALU"}:
wave_pc[p.wave] += inst.size()
inst = pc_map[pc:=wave_pc[p.wave]]
# assert branch always has a JUMP packet
if "BRANCH" in inst_op and not (isinstance(p, (INST, INST_RDNA4)) and p.op.name.startswith("JUMP")):
raise AssertionError(f"{inst_op} can only be followed by JUMP, got {p}")
# JUMP handling
if isinstance(p, (INST, INST_RDNA4)) and p.op in {InstOp.JUMP, InstOpRDNA4.JUMP}:
x = getattr(inst, 'simm16') & 0xffff
wave_pc[p.wave] += inst.size() + (x - 0x10000 if x & 0x8000 else x)*4
else:
wave_pc[p.wave] += inst.size()
yield (p, InstructionInfo(pc, p.wave, inst))
# for all other packets (VMEMEXEC, ALUEXEC, etc.), yield with None
else: yield (p, None)
# ═══════════════════════════════════════════════════════════════════════════════
# PRINTER
# ═══════════════════════════════════════════════════════════════════════════════
@@ -653,37 +424,35 @@ PACKET_COLORS = {
def format_packet(p) -> str:
from tinygrad.helpers import colored
name = type(p).__name__
if isinstance(p, (INST, INST_RDNA4)):
op_name = p.op.name if isinstance(p.op, (InstOp, InstOpRDNA4)) else f"0x{p.op:02x}"
fields = f"wave={p.wave} op={op_name}" + ((" flag1" if p.flag1 else "") + (" flag2" if p.flag2 else "") if isinstance(p, INST) else "")
if isinstance(p, (INST, INST_L4)):
op_name = p.op.name if isinstance(p.op, (InstOp, InstOpL4)) 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, WAVESTART_RDNA4, WAVEEND)): fields = f"wave={p.wave} simd={p.simd} cu={p.cu}"
elif isinstance(p, (WAVESTART, WAVESTART_L4, WAVEEND)): fields = f"wave={p.wave} simd={p.simd} cu={p.cu}"
elif hasattr(p, '_fields'):
filt = {'delta', 'encoding'} if not isinstance(p, (TS_DELTA_OR_MARK, TS_DELTA_OR_MARK_RDNA4)) else {'encoding'}
filt = {'delta', 'encoding'} if not isinstance(p, (TS_DELTA_OR_MARK, TS_DELTA_OR_MARK_L4)) else {'encoding'}
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 filt)
else: fields = ""
return f"{p._time:8}: {colored(f'{name:18}', PACKET_COLORS.get(name.replace('_RDNA4', ''), 'white'))} {fields}"
return f"{p._time:8}: {colored(f'{name:18}', PACKET_COLORS.get(name.replace('_L4', ''), 'white'))} {fields}"
def print_packets(packets) -> None:
from tinygrad.helpers import getenv
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"} if not getenv("NOSKIP") else {"NOP"}
for data in packets:
p, inst = data if isinstance(data, tuple) else (data, None)
if type(p).__name__.replace("_RDNA4", "") not in skip: print(format_packet(p), f"inst={inst.inst}" if inst is not None else '')
for p in packets:
if type(p).__name__.replace("_L4", "") not in skip: print(format_packet(p))
if __name__ == "__main__":
import sys, pickle
from tinygrad.helpers import temp
with open(temp("profile.pkl", append_user=True) if len(sys.argv) < 2 else sys.argv[1], "rb") as f:
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)
prg_events = {e.tag: e for e in data if type(e).__name__ == "ProfileProgramEvent" and e.tag is not None}
sqtt_events = [e for e in data if type(e).__name__ == "ProfileSQTTEvent"]
dev_targets = {e.device:f"gfx{e.props['gfx_target_version']//1000}" for e in data if type(e).__name__ == "ProfileDeviceEvent" and e.props}
for i, event in enumerate(sqtt_events):
prg = prg_events.get(event.kern)
print(f"\n=== event {i} {prg.name if prg is not None else ''} ===")
print_packets(map_insts(event.blob, prg.lib, dev_targets[prg.device]) if prg is not None else decode(event.blob))
print(f"\n=== event {i} ===")
print_packets(decode(event.blob))
+161
View File
@@ -0,0 +1,161 @@
"""SQTT (SQ Thread Trace) packet decoder for CDNA/MI300 GPUs.
CDNA uses a completely different 16-bit header format from RDNA's nibble-based encoding.
"""
from __future__ import annotations
from typing import Iterator
from extra.assembly.amd.dsl import bits
from extra.assembly.amd.sqtt import PacketType
# CDNA pkt_fmt -> size in bytes (extracted from rocprof hash table)
CDNA_PKT_SIZES = {0: 2, 1: 8, 2: 8, 3: 4, 4: 2, 5: 6, 6: 2, 7: 2, 8: 2, 9: 2, 10: 2, 11: 8, 12: 6, 13: 4, 14: 8, 15: 6}
class CDNA_DELTA(PacketType):
"""pkt_fmt=0: 16-bit timestamp delta packet"""
encoding = bits[3:0] == 0
delta = bits[11:4] # (data >> 4) & 0xff
unk_0 = bits[12:12] # (data >> 0xc) & 1
unk_1 = bits[15:13] # (data >> 0xd)
class CDNA_TIMESTAMP(PacketType):
"""pkt_fmt=1: 64-bit timestamp packet (case 0x0)"""
encoding = bits[3:0] == 1
unk_0 = bits[15:4]
timestamp = bits[63:16] # stored as (data_word >> 0x10) in low 46 bits of local_58
class CDNA_PKT_2(PacketType):
"""pkt_fmt=2: 64-bit packet (case 0x4)"""
encoding = bits[3:0] == 2
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_padding = bits[63:8]
class CDNA_WAVESTART(PacketType):
"""pkt_fmt=3: 32-bit WAVESTART packet (case 0x8)"""
encoding = bits[3:0] == 3
unk_0 = bits[5:5] # (data >> 5) & 1
unk_1 = bits[9:6] # (data >> 6) & 0xf
wave = bits[13:10] # (data >> 10) & 0xf
simd = bits[15:14] # (data >> 0xe) & 3
cu = bits[17:16] # (data >> 0x10) & 3
unk_5 = bits[19:18] # (data >> 0x12) & 3
unk_6 = bits[28:22] # (data >> 0x16) & 0x7f
unk_padding = bits[31:29]
class CDNA_PKT_4(PacketType):
"""pkt_fmt=4: 16-bit packet (case 0xc, same as 0x8/0x14)"""
encoding = bits[3:0] == 4
unk_0 = bits[5:5] # (data_word >> 5) & 1
unk_1 = bits[9:6] # (data_word >> 6) & 0xf
unk_2 = bits[13:10] # (data_word >> 10) & 0xf
unk_3 = bits[15:14] # (data_word >> 0xe)
class CDNA_PKT_5(PacketType):
"""pkt_fmt=5: 48-bit packet (case 0x10)"""
encoding = bits[3:0] == 5
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_2 = bits[15:9] # (data >> 9) & 0x7f
unk_padding = bits[47:16]
class CDNA_WAVEEND(PacketType):
"""pkt_fmt=6: 16-bit WAVEEND packet (case 0x14, same as 0x8/0xc)"""
encoding = bits[3:0] == 6
unk_0 = bits[5:5] # (data_word >> 5) & 1
unk_1 = bits[9:6] # (data_word >> 6) & 0xf
wave = bits[13:10] # (data_word >> 10) & 0xf
simd = bits[15:14] # (data_word >> 0xe)
class CDNA_EXEC(PacketType):
"""pkt_fmt=10: 16-bit EXEC packet (case 0x24)"""
encoding = bits[3:0] == 10
unk_0 = bits[8:5] # (data_word >> 5) & 0xf
unk_1 = bits[10:9] # (data_word >> 9) & 3
unk_2 = bits[15:11] # (data_word >> 0xb)
class CDNA_PKT_11(PacketType):
"""pkt_fmt=11: 64-bit packet (case 0x28)"""
encoding = bits[3:0] == 11
unk_0 = bits[8:5] # (data_word >> 5) & 0xf
unk_1 = bits[10:9] # (data_word >> 9) & 3
unk_2 = bits[15:15] # (data_word >> 0xf) & 1
unk_padding = bits[63:16]
class CDNA_INST(PacketType):
"""pkt_fmt=13: 32-bit INST packet (case 0x30)"""
encoding = bits[3:0] == 13
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[9:8] # (data >> 8) & 3
unk_2 = bits[11:10] # (data >> 10) & 3
unk_3 = bits[13:12] # (data >> 0xc) & 3
unk_4 = bits[15:14] # (data >> 0xe) & 3
unk_5 = bits[19:18] # (data >> 0x12) & 3
unk_6 = bits[21:20] # (data >> 0x14) & 3
unk_7 = bits[23:22] # (data >> 0x16) & 3
unk_8 = bits[25:24] # (data >> 0x18) & 3
unk_9 = bits[27:26] # (data >> 0x1a) & 3
unk_padding = bits[31:28]
class CDNA_PKT_14(PacketType):
"""pkt_fmt=14: 64-bit packet (case 0x34)"""
encoding = bits[3:0] == 14
unk_0 = bits[5:5] # (data >> 5) & 1
unk_1 = bits[9:6] # (data >> 6) & 0xf
unk_2 = bits[11:10] # (data >> 10) & 3
unk_3 = bits[24:12] # (data >> 0xc) & 0x1fff
unk_4 = bits[37:25] # (data >> 0x19) & 0x1fff
unk_5 = bits[50:38] # (data >> 0x26) & 0x1fff
unk_6 = bits[51:51] # (data >> 0x33) & 1
unk_padding = bits[63:52]
class CDNA_PKT_15(PacketType):
"""pkt_fmt=15: 48-bit packet (case 0x38, same as 0x10)"""
encoding = bits[3:0] == 15
unk_0 = bits[6:5] # (data >> 5) & 3
unk_1 = bits[7:7] # (data >> 7) + 1 & 1
unk_2 = bits[15:9] # (data >> 9) & 0x7f
unk_padding = bits[47:16]
CDNA_PKT_TYPES: dict[int, type[PacketType]] = {
0: CDNA_DELTA, 1: CDNA_TIMESTAMP, 2: CDNA_PKT_2, 3: CDNA_WAVESTART, 4: CDNA_PKT_4,
5: CDNA_PKT_5, 6: CDNA_WAVEEND, 10: CDNA_EXEC, 11: CDNA_PKT_11, 13: CDNA_INST, 14: CDNA_PKT_14, 15: CDNA_PKT_15,
}
# Validate CDNA packet definitions
for pkt_fmt, pkt_cls in CDNA_PKT_TYPES.items():
assert pkt_cls.encoding.default == pkt_fmt, f"{pkt_cls.__name__} encoding {pkt_cls.encoding.default} != pkt_fmt {pkt_fmt}"
assert CDNA_PKT_SIZES[pkt_fmt] * 2 == pkt_cls._size_nibbles, f"{pkt_cls.__name__} size {pkt_cls._size_nibbles//2} != {CDNA_PKT_SIZES[pkt_fmt]}"
def decode(data: bytes) -> Iterator[PacketType]:
"""Decode CDNA SQTT blob using 16-bit header format."""
pos, time, ts_offset = 0, 0, None
while pos + 2 <= len(data):
header = int.from_bytes(data[pos:pos+2], 'little')
pkt_fmt = header & 0xf
pkt_size = CDNA_PKT_SIZES[pkt_fmt]
if pos + pkt_size > len(data): break
raw = int.from_bytes(data[pos:pos+pkt_size], 'little')
# pkt_fmt=0 has delta in bits[11:4], accumulate it
if pkt_fmt == 0: time += ((raw >> 4) & 0xff) * 4
# pkt_fmt=1 with unk_0=0 is absolute timestamp - use it to anchor time
if pkt_fmt == 1 and ((raw >> 4) & 0xfff) == 0:
abs_ts = raw >> 16
if ts_offset is None: ts_offset = abs_ts - time # first timestamp: save offset
else: time = ((abs_ts - ts_offset) & ~3) - 4 # subsequent: compute time, align to 4, subtract 4
pkt_cls = CDNA_PKT_TYPES[pkt_fmt]
yield pkt_cls.from_raw(raw, time)
pos += pkt_size
if __name__ == "__main__":
import sys, pickle
if len(sys.argv) < 2:
print("Usage: python sqtt_cdna.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} ===")
for pkt in decode(event.blob):
print(f"{pkt._time:8}: {pkt}")
+122
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@@ -0,0 +1,122 @@
# maps SQTT trace packets to instructions.
from dataclasses import dataclass
from typing import Iterator
from extra.assembly.amd.sqtt import decode, print_packets, INST, VALUINST, IMMEDIATE, WAVESTART, WAVEEND, InstOp, PacketType, IMMEDIATE_MASK
from extra.assembly.amd.dsl import Inst
from extra.assembly.amd.autogen.rdna3.ins import SOPP, s_endpgm
from extra.assembly.amd.autogen.rdna3.enum import SOPPOp
@dataclass(frozen=True)
class InstructionInfo:
pc: int
wave: int
inst: Inst
def map_insts(data:bytes, lib:bytes, target:int) -> Iterator[tuple[PacketType, InstructionInfo|None]]:
"""maps SQTT packets to instructions, yields (packet, instruction_info or None)"""
# map pcs to insts
from tinygrad.viz.serve import amd_decode
pc_map = amd_decode(lib, target)
wave_pc:dict[int, int] = {}
# only processing packets on one [CU, SIMD] unit
def simd_select(p) -> bool: return getattr(p, "cu", 0) == 0 and getattr(p, "simd", 0) == 0
for p in decode(data):
if not simd_select(p): continue
if isinstance(p, WAVESTART):
assert p.wave not in wave_pc, "only one inflight wave per unit"
wave_pc[p.wave] = next(iter(pc_map))
continue
if isinstance(p, WAVEEND):
pc = wave_pc.pop(p.wave)
yield (p, InstructionInfo(pc, p.wave, s_endpgm()))
continue
# skip OTHER_ instructions, they don't belong to this unit
if isinstance(p, INST) and p.op.name.startswith("OTHER_"): continue
if isinstance(p, IMMEDIATE_MASK):
# immediate mask may yield multiple times per packet
for wave in range(16):
if p.mask & (1 << wave):
inst = pc_map[pc:=wave_pc[wave]]
# can this assert be more strict?
assert isinstance(inst, SOPP), f"IMMEDIATE_MASK packet must map to SOPP, got {inst}"
wave_pc[wave] += inst.size()
yield (p, InstructionInfo(pc, wave, inst))
continue
if isinstance(p, (VALUINST, INST, IMMEDIATE)):
inst = pc_map[pc:=wave_pc[p.wave]]
# s_delay_alu doesn't get a packet?
if isinstance(inst, SOPP) and inst.op in {SOPPOp.S_DELAY_ALU}:
wave_pc[p.wave] += inst.size()
inst = pc_map[pc:=wave_pc[p.wave]]
# identify a branch instruction, only used for asserts
is_branch = isinstance(inst, SOPP) and "BRANCH" in inst.op_name
if is_branch: assert isinstance(p, INST) and p.op in {InstOp.JUMP_NO, InstOp.JUMP}, f"branch can only be folowed by jump packets, got {p}"
# JUMP handling
if isinstance(p, INST) and p.op is InstOp.JUMP:
assert is_branch, f"JUMP packet must map to a branch instruction, got {inst}"
x = inst.simm16 & 0xffff
wave_pc[p.wave] += inst.size() + (x - 0x10000 if x & 0x8000 else x)*4
else:
if is_branch: assert inst.op != SOPPOp.S_BRANCH, f"S_BRANCH must have a JUMP packet, got {p}"
wave_pc[p.wave] += inst.size()
yield (p, InstructionInfo(pc, p.wave, inst))
continue
# for all other packets (VMEMEXEC, ALUEXEC, etc.), yield with None
yield (p, None)
# test to compare every packet with the rocprof decoder
def test_rocprof_inst_traces_match(sqtt, prg, target):
from tinygrad.viz.serve import amd_decode
from extra.sqtt.roc import decode as roc_decode, InstExec
addr_table = amd_decode(prg.lib, target)
disasm = {addr+prg.base:(inst.disasm(), inst.size()) for addr,inst in addr_table.items()}
rctx = roc_decode([sqtt], {prg.tag:disasm})
rwaves = rctx.inst_execs.get((sqtt.kern, sqtt.exec_tag), [])
rwaves_iter:dict[int, list[Iterator[InstExec]]] = {} # wave unit (0-15) -> list of inst trace iterators for all executions on that unit
for w in rwaves: rwaves_iter.setdefault(w.wave_id, []).append(w.unpack_insts())
passed_insts = 0
for pkt, info in map_insts(sqtt.blob, prg.lib, target):
if DEBUG >= 2: print_packets([pkt])
if info is None: continue
if DEBUG >= 2: print(f"{' '*29}{info.inst.disasm()}")
rocprof_inst = next(rwaves_iter[info.wave][0])
ref_pc = rocprof_inst.pc-prg.base
# always check pc matches
assert ref_pc == info.pc, f"pc mismatch {ref_pc}:{disasm[rocprof_inst.pc][0]} != {info.pc}:{info.inst.disasm()}"
# special handling for s_endpgm, it marks the wave completion.
if info.inst == s_endpgm():
completed_wave = list(rwaves_iter[info.wave].pop(0))
assert len(completed_wave) == 0, f"incomplete instructions in wave {info.wave}"
# otherwise the packet timestamp is time + "stall"
else:
assert pkt._time == rocprof_inst.time+rocprof_inst.stall
passed_insts += 1
for k,v in rwaves_iter.items():
assert len(v) == 0, f"incomplete wave {k}"
if len(rwaves):
print(f"passed for {passed_insts} instructions across {len(rwaves)} waves scheduled on {len(rwaves_iter)} wave units")
if __name__ == "__main__":
import argparse, pickle, pathlib
from tinygrad.helpers import temp, DEBUG
parser = argparse.ArgumentParser()
parser.add_argument('--profile', type=pathlib.Path, metavar="PATH", help='Path to profile (optional file, default: latest profile)',
default=pathlib.Path(temp("profile.pkl", append_user=True)))
parser.add_argument('--kernel', type=str, default=None, metavar="NAME", help='Kernel to focus on (optional name, default: all kernels)')
args = parser.parse_args()
with open(args.profile, "rb") as f:
data = pickle.load(f)
sqtt_events = [e for e in data if type(e).__name__ == "ProfileSQTTEvent"]
kern_events = {e.tag:e for e in data if type(e).__name__ == "ProfileProgramEvent"}
target = next((e for e in data if type(e).__name__ == "ProfileDeviceEvent" and e.device.startswith("AMD"))).props["gfx_target_version"]
for e in sqtt_events:
if args.kernel is not None and args.kernel != e.kern: continue
if not e.itrace: continue
print(f"==== {e.kern}")
test_rocprof_inst_traces_match(e, kern_events[e.kern], target)
+266
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@@ -0,0 +1,266 @@
#!/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, decode_program
from extra.assembly.amd import decode_inst
from extra.assembly.amd.autogen.rdna3.ins import SOPP, SOPPOp
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 profile_instructions(kernel: bytes):
"""Profile individual instruction compile times."""
from extra.assembly.amd.emu import _get_runner, _canonical_runner_cache
from tinygrad.helpers import Context
_get_runner.cache_clear()
_canonical_runner_cache.clear()
results = []
i = 0
while i < len(kernel):
inst = decode_inst(kernel[i:])
if isinstance(inst, SOPP) and inst.op == SOPPOp.S_CODE_END: break
inst_bytes = bytes(kernel[i:i + inst.size() + 4])
try: inst_str = repr(inst)
except Exception: inst_str = f"<{type(inst).__name__}>"
# Time the full compile (sink + render + compile)
start = time.perf_counter()
with Context(CCACHE=0):
runner, is_new = _get_runner(inst_bytes)
compile_time = time.perf_counter() - start
results.append({
'inst_str': inst_str + ('' if is_new else ' [CACHED]'),
'compile_ms': compile_time * 1000 if is_new else 0,
})
i += inst.size()
return sorted(results, key=lambda x: x['compile_ms'], reverse=True)
def benchmark_python_split(kernel: bytes, global_size, local_size, args_ptr, rsrc2: int, iterations: int = 5):
"""Benchmark Python emulator with compile and execution times."""
from extra.assembly.amd.emu import _get_runner, _canonical_runner_cache
from tinygrad.helpers import Context
_get_runner.cache_clear()
_canonical_runner_cache.clear()
decode_program.cache_clear()
# Measure compile time (decode_program builds sinks, renders, and compiles)
compile_start = time.perf_counter()
with Context(CCACHE=0):
program = decode_program(kernel)
compile_time = time.perf_counter() - compile_start
n_compiled = len(_canonical_runner_cache)
# Execution time
exec_time = benchmark_emulator("Python", python_run_asm, kernel, global_size, local_size, args_ptr, rsrc2, iterations)
return compile_time, exec_time, len(program), n_compiled
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", "sin", "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")
parser.add_argument("--profile", type=str, default=None, help="Profile instructions for a specific kernel (e.g. 'sin')")
parser.add_argument("--top", type=int, default=20, help="Number of top instructions to show in profile")
args = parser.parse_args()
# Profile mode: show individual instruction timing
if args.profile:
kernel_info = get_tinygrad_kernel(args.profile)
if kernel_info is None:
print(f"Failed to get kernel for '{args.profile}'")
return
kernel = kernel_info[0]
print(f"Profiling instructions for '{args.profile}' kernel...")
print("=" * 110)
results = profile_instructions(kernel)
print(f"{'Instruction':<90} {'Compile(ms)':>12}")
print("-" * 110)
for r in results[:args.top]:
inst = r['inst_str'][:87] + "..." if len(r['inst_str']) > 90 else r['inst_str']
print(f"{inst:<90} {r['compile_ms']:>12.3f}")
print("-" * 110)
total = sum(r['compile_ms'] for r in results)
print(f"{'TOTAL':<90} {total:>12.3f}")
return
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
buffers, args_arr, args_ptr, ranges = setup_buffers(buf_sizes, buf_data)
# Benchmark Python emulator (must be first to measure compile time before cache is populated)
py_compile, py_exec, n_insts, n_compiled = benchmark_python_split(kernel, global_size, local_size, args_ptr, rsrc2, args.iterations)
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_compiled} unique) × {n_workgroups} WGs × {n_threads} threads = {total_work:,} ops")
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_compile is not None:
py_exec_rate = total_work / py_exec / 1e6
print(f" Compile: {py_compile*1000:8.3f} ms ({n_compiled} unique)")
print(f" Exec: {py_exec*1000:8.3f} ms ({py_exec_rate:7.2f} M ops/s)")
if rust_time:
rust_rate = total_work / rust_time / 1e6
speedup = py_exec / rust_time if py_exec 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_compiled, n_workgroups, py_compile, py_exec, rust_time))
# Summary table
print("\n" + "=" * 110)
print("SUMMARY")
print("=" * 110)
print(f"{'Name':<16} {'Insts':<6} {'Unique':<6} {'WGs':<5} {'Compile (ms)':<14} {'Exec (ms)':<12} {'Rust (ms)':<12} {'Speedup':<10}")
print("-" * 110)
for name, n_insts, n_compiled, n_wgs, py_compile, py_exec, rust_time in results:
compile_ms = f"{py_compile*1000:.3f}" if py_compile else "error"
exec_ms = f"{py_exec*1000:.3f}" if py_exec else "error"
if rust_time:
rust_ms = f"{rust_time*1000:.3f}"
speedup = f"{py_exec/rust_time:.1f}x" if py_exec else "N/A"
else:
rust_ms, speedup = "N/A", "N/A"
print(f"{name:<16} {n_insts:<6} {n_compiled:<6} {n_wgs:<5} {compile_ms:<14} {exec_ms:<12} {rust_ms:<12} {speedup:<10}")
if __name__ == "__main__":
main()
+38
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@@ -0,0 +1,38 @@
"""Shared test helpers for RDNA3 tests."""
import shutil
from dataclasses import dataclass
@dataclass
class KernelInfo:
code: bytes
src: str
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")
ARCH_TO_TARGET:dict[str, list[str]] = {
"rdna3":["gfx1100"],
"rdna4":["gfx1200"],
"cdna":["gfx950", "gfx942"],
}
TARGET_TO_ARCH:dict[str, str] = {t:arch for arch,targets in ARCH_TO_TARGET.items() for t in targets}
def get_target(arch:str) -> str: return ARCH_TO_TARGET[arch][0]
def get_mattr(arch:str) -> str:
return {"rdna3":"+real-true16,+wavefrontsize32", "rdna4":"+real-true16,+wavefrontsize32", "cdna":"+wavefrontsize64"}[arch]
@@ -4,10 +4,10 @@ Uses run_asm() with memory output, so tests can run on both emulator and real ha
Set USE_HW=1 to run on both emulator and hardware, comparing results.
"""
import ctypes, math, os, struct
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from extra.assembly.amd.autogen.rdna3.ins import *
from test.mockgpu.amd.emu import run_asm
from tinygrad.renderer.amd.dsl import NULL, SCC, VCC_LO, VCC_HI, EXEC_LO, EXEC_HI, M0
from extra.assembly.amd.emu import run_asm
from extra.assembly.amd.dsl import NULL, SCC, VCC_LO, VCC_HI, EXEC_LO, EXEC_HI, M0
def _i32(f: float) -> int: return struct.unpack('<I', struct.pack('<f', f))[0]
def _f32(i: int) -> float: return struct.unpack('<f', struct.pack('<I', i & 0xFFFFFFFF))[0]
@@ -47,7 +47,7 @@ def get_gpu_target() -> tuple[int, int, int]:
"""Get the GPU target as (major, minor, stepping) tuple."""
if not USE_HW: return (0, 0, 0)
from tinygrad.device import Device
return Device["AMD"].target # type: ignore[attr-defined]
return Device["AMD"].target
def skip_unless_gfx(min_major: int, min_minor: int = 0, reason: str = ""):
"""Skip test if GPU target is below the minimum required version."""
@@ -60,12 +60,11 @@ def skip_unless_gfx(min_major: int, min_minor: int = 0, reason: str = ""):
return test_func
return decorator
# Output buffer layout: vgpr[N_VGPRS][n_lanes], sgpr[N_SGPRS], vcc, scc, exec
# Output buffer layout: vgpr[16][32], sgpr[16], vcc, scc, exec
N_VGPRS, N_SGPRS, WAVE_SIZE = 16, 16, 32
VGPR_BYTES = N_VGPRS * WAVE_SIZE * 4 # 16 regs * 32 lanes * 4 bytes = 2048
SGPR_BYTES = N_SGPRS * 4 # 16 regs * 4 bytes = 64
_VGPR_REGION = N_VGPRS * WAVE_SIZE * 4 # minimum vgpr region size (tests may use as scratch)
def _out_bytes(n_lanes: int) -> int: return max(N_VGPRS * n_lanes * 4, _VGPR_REGION) + SGPR_BYTES + 12
OUT_BYTES = _out_bytes(WAVE_SIZE) # default for single-wave (backward compat)
OUT_BYTES = VGPR_BYTES + SGPR_BYTES + 12 # + vcc + scc + exec
# Float conversion helpers
def f2i(f: float) -> int: return _i32(f)
@@ -76,10 +75,10 @@ def i642f(i: int) -> float: return struct.unpack('<d', struct.pack('<Q', i))[0]
def assemble(instructions: list) -> bytes:
return b''.join(inst.to_bytes() for inst in instructions)
# Simple WaveState class for test output parsing (mirrors test/mockgpu/amd/emu.py interface for tests)
# Simple WaveState class for test output parsing (mirrors emu.py interface for tests)
class WaveState:
def __init__(self, n_lanes: int = 32):
self.vgpr = [[0] * 256 for _ in range(n_lanes)] # vgpr[lane][reg]
def __init__(self):
self.vgpr = [[0] * 256 for _ in range(32)] # vgpr[lane][reg]
self.sgpr = [0] * 128
self.vcc = 0
self.scc = 0
@@ -103,53 +102,49 @@ def get_prologue_epilogue(n_lanes: int) -> tuple[list, list]:
# Save EXEC early (before we modify it for VGPR stores)
s_mov_b32(s[95], EXEC_LO),
# Restore EXEC to all active lanes for VGPR stores (test may have modified EXEC)
s_mov_b32(EXEC_LO, (1 << min(n_lanes, WAVE_SIZE)) - 1),
s_mov_b32(EXEC_LO, (1 << n_lanes) - 1),
s_load_b64(s[92:93], s[80:81], 0, soffset=NULL),
s_waitcnt(0), # simm16=0 waits for all
v_lshlrev_b32_e32(v[240], 2, v[255]),
]
vgpr_bytes = N_VGPRS * n_lanes * 4
for i in range(N_VGPRS):
epilogue.append(global_store_b32(addr=v[240], data=v[i], saddr=s[92:93], offset=i * n_lanes * 4))
epilogue.append(global_store_b32(addr=v[240], data=v[i], saddr=s[92:93], offset=i * WAVE_SIZE * 4))
epilogue.append(v_mov_b32_e32(v[241], 0))
epilogue.append(v_cmp_eq_u32_e32(v[255], v[241]))
epilogue.append(s_and_saveexec_b32(s[94], VCC_LO))
# Scalar stores: only thread 0. Use v[240]=vgpr_bytes as base offset so immediate offsets stay small.
epilogue.append(v_mov_b32_e32(v[240], vgpr_bytes))
epilogue.append(v_mov_b32_e32(v[240], 0))
for i in range(N_SGPRS):
epilogue.append(v_mov_b32_e32(v[243], s[i]))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=i * 4))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=VGPR_BYTES + i * 4))
epilogue.append(v_mov_b32_e32(v[243], s[90]))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=SGPR_BYTES))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=VGPR_BYTES + SGPR_BYTES))
epilogue.append(v_mov_b32_e32(v[243], s[91]))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=SGPR_BYTES + 4))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=VGPR_BYTES + SGPR_BYTES + 4))
# Store EXEC (saved earlier in s[95])
epilogue.append(v_mov_b32_e32(v[243], s[95]))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=SGPR_BYTES + 8))
epilogue.append(global_store_b32(addr=v[240], data=v[243], saddr=s[92:93], offset=VGPR_BYTES + SGPR_BYTES + 8))
epilogue.append(s_mov_b32(EXEC_LO, s[94]))
epilogue.append(s_endpgm())
return prologue, epilogue
def parse_output(out_buf: bytes, n_lanes: int) -> WaveState:
"""Parse output buffer into WaveState."""
vgpr_bytes = N_VGPRS * n_lanes * 4
st = WaveState(n_lanes)
st = WaveState()
for i in range(N_VGPRS):
for lane in range(n_lanes):
off = i * n_lanes * 4 + lane * 4
off = i * WAVE_SIZE * 4 + lane * 4
st.vgpr[lane][i] = struct.unpack_from('<I', out_buf, off)[0]
for i in range(N_SGPRS):
st.sgpr[i] = struct.unpack_from('<I', out_buf, vgpr_bytes + i * 4)[0]
st.vcc = struct.unpack_from('<I', out_buf, vgpr_bytes + SGPR_BYTES)[0]
st.scc = struct.unpack_from('<I', out_buf, vgpr_bytes + SGPR_BYTES + 4)[0]
st.sgpr[i] = struct.unpack_from('<I', out_buf, VGPR_BYTES + i * 4)[0]
st.vcc = struct.unpack_from('<I', out_buf, VGPR_BYTES + SGPR_BYTES)[0]
st.scc = struct.unpack_from('<I', out_buf, VGPR_BYTES + SGPR_BYTES + 4)[0]
# Store EXEC in its proper location (index 126)
st.sgpr[EXEC_LO.offset] = struct.unpack_from('<I', out_buf, vgpr_bytes + SGPR_BYTES + 8)[0]
st.sgpr[EXEC_LO.offset] = struct.unpack_from('<I', out_buf, VGPR_BYTES + SGPR_BYTES + 8)[0]
return st
def run_program_emu(instructions: list, n_lanes: int = 1) -> WaveState:
"""Run instructions via emulator run_asm, dump state to memory, return WaveState."""
buf_sz = _out_bytes(n_lanes)
out_buf = (ctypes.c_uint8 * buf_sz)(*([0] * buf_sz))
out_buf = (ctypes.c_uint8 * OUT_BYTES)(*([0] * OUT_BYTES))
out_addr = ctypes.addressof(out_buf)
prologue, epilogue = get_prologue_epilogue(n_lanes)
@@ -176,7 +171,7 @@ def run_program_hw(instructions: list, n_lanes: int = 1) -> WaveState:
from tinygrad.helpers import flat_mv
dev = Device["AMD"]
compiler = HIPCompiler(dev.arch) # type: ignore[attr-defined]
compiler = HIPCompiler(dev.arch)
prologue, epilogue = get_prologue_epilogue(n_lanes)
code = assemble(prologue + instructions + epilogue)
@@ -223,14 +218,13 @@ amdhsa.kernels:
"""
lib = compiler.compile(asm_src)
prg = AMDProgram(dev, "test", lib) # type: ignore[arg-type]
prg = AMDProgram(dev, "test", lib)
buf_sz = _out_bytes(n_lanes)
out_gpu = dev.allocator.alloc(buf_sz)
out_gpu = dev.allocator.alloc(OUT_BYTES)
assert out_gpu.va_addr % 16 == 0, f"buffer not 16-byte aligned: 0x{out_gpu.va_addr:x}"
prg(out_gpu, global_size=(1, 1, 1), local_size=(n_lanes, 1, 1), wait=True)
out_buf = bytearray(buf_sz)
out_buf = bytearray(OUT_BYTES)
dev.allocator._copyout(flat_mv(memoryview(out_buf)), out_gpu)
return parse_output(bytes(out_buf), n_lanes)
@@ -282,6 +276,6 @@ def run_program(instructions: list, n_lanes: int = 1, ulp_tolerance: int = 0) ->
hw_st = run_program_hw(instructions, n_lanes)
diffs = compare_wave_states(emu_st, hw_st, n_lanes, ulp_tolerance=ulp_tolerance)
if diffs:
raise AssertionError("Emulator vs Hardware mismatch:\n" + "\n".join(diffs))
raise AssertionError(f"Emulator vs Hardware mismatch:\n" + "\n".join(diffs))
return hw_st
return emu_st
@@ -5,7 +5,7 @@ Includes: ds_store_b32, ds_load_b32, ds_store_2addr_*, ds_load_2addr_*,
ds_inc_*, ds_dec_*, ds_cmpstore_*, ds_storexchg_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestDS2Addr(unittest.TestCase):
"""Tests for DS_*_2ADDR instructions."""
@@ -601,6 +601,7 @@ class TestDS2AddrStride64(unittest.TestCase):
self.assertEqual(st.vgpr[0][6], 0xAAAAAAAA, "new val 0")
self.assertEqual(st.vgpr[0][7], 0xBBBBBBBB, "new val 1")
def test_ds_storexchg_rtn_b64(self):
"""DS_STOREXCHG_RTN_B64: exchange 64-bit value and return old."""
instructions = [
@@ -760,110 +761,5 @@ class TestDsPermute(unittest.TestCase):
self.assertEqual(st.vgpr[0][2], 0x11111111)
class TestDSLargeOffset(unittest.TestCase):
"""Tests for DS instructions with offsets > 255 (offset1 > 0).
The DS offset is a 16-bit value encoded as (offset1 << 8) | offset0.
These tests verify that offset1 is used correctly, not just offset0.
"""
def test_ds_store_load_b32_offset_256(self):
"""DS_STORE_B32/DS_LOAD_B32 with offset=256 (offset0=0, offset1=1)."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0xDEADBEEF),
v_mov_b32_e32(v[0], s[0]),
ds_store_b32(addr=v[10], data0=v[0], offset0=0, offset1=1), # offset = 256
s_waitcnt(lgkmcnt=0),
ds_load_b32(addr=v[10], vdst=v[1], offset0=0, offset1=1), # offset = 256
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][1], 0xDEADBEEF)
def test_ds_store_load_b32_offset_300(self):
"""DS_STORE_B32/DS_LOAD_B32 with offset=300 (offset0=44, offset1=1)."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0xCAFEBABE),
v_mov_b32_e32(v[0], s[0]),
ds_store_b32(addr=v[10], data0=v[0], offset0=44, offset1=1), # offset = 300
s_waitcnt(lgkmcnt=0),
ds_load_b32(addr=v[10], vdst=v[1], offset0=44, offset1=1), # offset = 300
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][1], 0xCAFEBABE)
def test_ds_store_load_b64_offset_512(self):
"""DS_STORE_B64/DS_LOAD_B64 with offset=512 (offset0=0, offset1=2)."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0x11111111),
v_mov_b32_e32(v[0], s[0]),
s_mov_b32(s[0], 0x22222222),
v_mov_b32_e32(v[1], s[0]),
ds_store_b64(addr=v[10], data0=v[0:1], offset0=0, offset1=2), # offset = 512
s_waitcnt(lgkmcnt=0),
ds_load_b64(addr=v[10], vdst=v[2:3], offset0=0, offset1=2), # offset = 512
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][2], 0x11111111)
self.assertEqual(st.vgpr[0][3], 0x22222222)
def test_ds_large_offset_distinct_from_small(self):
"""Verify offset=256 and offset=0 address different LDS locations."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0xAAAAAAAA),
v_mov_b32_e32(v[0], s[0]),
s_mov_b32(s[0], 0xBBBBBBBB),
v_mov_b32_e32(v[1], s[0]),
# Store 0xAAAAAAAA at offset=0, 0xBBBBBBBB at offset=256
ds_store_b32(addr=v[10], data0=v[0], offset0=0, offset1=0), # offset = 0
ds_store_b32(addr=v[10], data0=v[1], offset0=0, offset1=1), # offset = 256
s_waitcnt(lgkmcnt=0),
# Read back both
ds_load_b32(addr=v[10], vdst=v[2], offset0=0, offset1=0), # offset = 0
ds_load_b32(addr=v[10], vdst=v[3], offset0=0, offset1=1), # offset = 256
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][2], 0xAAAAAAAA, "offset=0 should read 0xAAAAAAAA")
self.assertEqual(st.vgpr[0][3], 0xBBBBBBBB, "offset=256 should read 0xBBBBBBBB")
def test_ds_store_load_b32_offset_448(self):
"""DS_STORE_B32/DS_LOAD_B32 with offset=448 (offset0=192, offset1=1) - matches matmul B tile."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0x12345678),
v_mov_b32_e32(v[0], s[0]),
ds_store_b32(addr=v[10], data0=v[0], offset0=192, offset1=1), # offset = 448
s_waitcnt(lgkmcnt=0),
ds_load_b32(addr=v[10], vdst=v[1], offset0=192, offset1=1), # offset = 448
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][1], 0x12345678)
def test_ds_load_b64_offset_392(self):
"""DS_LOAD_B64 with offset=392 (offset0=136, offset1=1) - matches matmul B tile load."""
instructions = [
v_mov_b32_e32(v[10], 0),
s_mov_b32(s[0], 0xAABBCCDD),
v_mov_b32_e32(v[0], s[0]),
s_mov_b32(s[0], 0x11223344),
v_mov_b32_e32(v[1], s[0]),
ds_store_b64(addr=v[10], data0=v[0:1], offset0=136, offset1=1), # offset = 392
s_waitcnt(lgkmcnt=0),
ds_load_b64(addr=v[10], vdst=v[2:3], offset0=136, offset1=1), # offset = 392
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][2], 0xAABBCCDD)
self.assertEqual(st.vgpr[0][3], 0x11223344)
if __name__ == '__main__':
unittest.main()
@@ -3,7 +3,7 @@
Includes: flat_load_*, flat_store_*, flat_atomic_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestFlatAtomic(unittest.TestCase):
"""Tests for FLAT atomic instructions."""
@@ -3,7 +3,7 @@
Includes: global_load_*, global_store_*, global_atomic_*, global_load_d16_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestGlobalAtomic(unittest.TestCase):
"""Tests for GLOBAL atomic instructions."""
@@ -3,7 +3,7 @@
Includes: scratch_load_*, scratch_store_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestScratchStore(unittest.TestCase):
"""Tests for SCRATCH store instructions."""
@@ -4,7 +4,7 @@ Includes: s_load_b32, s_load_b64, s_load_b128, s_load_b256, s_load_b512
Tests both immediate and register offset addressing modes.
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
# Use offset into output buffer for test data (output buffer is 2124 bytes)
TEST_OFFSET = 2000
@@ -4,7 +4,7 @@ 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 test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestBasicScalar(unittest.TestCase):
"""Tests for basic scalar operations."""
@@ -932,76 +932,5 @@ class Test64BitSOPLiterals(unittest.TestCase):
self.assertEqual(st.vgpr[0][1], 0) # zero-extended, not sign-extended
class TestBarrier(unittest.TestCase):
"""Tests for s_barrier — workgroup synchronization across wavefronts."""
def test_barrier_cross_wave_lds(self):
"""Wave 0 writes to LDS, s_barrier, wave 1 reads — verifies cross-wave synchronization.
64 threads (2 waves of 32). Each thread writes (tid+1) to LDS[tid*4], then after
s_barrier, reads LDS[(tid^32)*4] the value written by the other wave. Without barrier
support, wave 1 would read stale/zero LDS values.
"""
instructions = [
# v[255] = tid (saved by prologue), copy to v[1]
v_mov_b32_e32(v[1], v[255]),
# v[2] = tid + 1
v_add_nc_u32_e32(v[2], 1, v[1]),
# v[3] = tid * 4
v_lshlrev_b32_e32(v[3], 2, v[1]),
# Store (tid+1) to LDS[tid*4]
ds_store_b32(addr=v[3], data0=v[2]),
s_waitcnt(lgkmcnt=0),
s_barrier(),
# Read from the other wave's slot: LDS[(tid^32)*4]
v_xor_b32_e32(v[4], 32, v[1]),
v_lshlrev_b32_e32(v[5], 2, v[4]),
ds_load_b32(addr=v[5], vdst=v[0]),
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=64)
for tid in range(64):
self.assertEqual(st.vgpr[tid][0], (tid ^ 32) + 1, f"tid={tid}")
def test_barrier_two_phases(self):
"""Two barriers with three phases — tests multiple barriers in sequence.
Phase 1: all threads write (tid+100) to LDS[tid*4], barrier.
Phase 2: all threads read other wave's value, add 1000, write to LDS[(tid+64)*4], barrier.
Phase 3: all threads read the other wave's phase-2 output into v[0].
"""
instructions = [
# v[255] = tid (saved by prologue), copy to v[1]
v_mov_b32_e32(v[1], v[255]),
# v[2] = tid + 100
v_add_nc_u32_e32(v[2], 100, v[1]),
# v[3] = tid * 4
v_lshlrev_b32_e32(v[3], 2, v[1]),
# Phase 1: write (tid+100) to LDS[tid*4]
ds_store_b32(addr=v[3], data0=v[2]),
s_waitcnt(lgkmcnt=0),
s_barrier(),
# Phase 2: read from other wave, add 1000, write to separate LDS region
v_xor_b32_e32(v[4], 32, v[1]),
v_lshlrev_b32_e32(v[5], 2, v[4]),
ds_load_b32(addr=v[5], vdst=v[6]),
s_waitcnt(lgkmcnt=0),
v_add_nc_u32_e32(v[7], 0x3e8, v[6]),
v_add_nc_u32_e32(v[8], 64, v[1]),
v_lshlrev_b32_e32(v[9], 2, v[8]),
ds_store_b32(addr=v[9], data0=v[7]),
s_waitcnt(lgkmcnt=0),
s_barrier(),
# Phase 3: read other wave's phase-2 output into v[0]
v_add_nc_u32_e32(v[10], 64, v[4]),
v_lshlrev_b32_e32(v[11], 2, v[10]),
ds_load_b32(addr=v[11], vdst=v[0]),
s_waitcnt(lgkmcnt=0),
]
st = run_program(instructions, n_lanes=64)
for tid in range(64):
self.assertEqual(st.vgpr[tid][0], tid + 100 + 1000, f"tid={tid}")
if __name__ == '__main__':
unittest.main()
@@ -5,7 +5,7 @@ Includes: v_mov_b32, v_cvt_*, v_sin_f32, v_rcp_f32, v_exp_f32, v_rndne_f32,
v_readfirstlane_b32
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestMov(unittest.TestCase):
"""Tests for V_MOV_B32."""
@@ -373,6 +373,7 @@ class TestF64Conversions(unittest.TestCase):
def test_v_cvt_f64_f32_pi(self):
"""V_CVT_F64_F32 converts f32 pi to f64."""
import math
instructions = [
s_mov_b32(s[0], f2i(3.14159265)),
v_mov_b32_e32(v[0], s[0]),
@@ -1579,55 +1580,5 @@ class TestPermlane64(unittest.TestCase):
self.assertEqual(st.vgpr[0][1], 0x12345678)
class TestSwap(unittest.TestCase):
"""Tests for V_SWAP_B32 - swap two VGPRs."""
def test_v_swap_b32_basic(self):
"""V_SWAP_B32 swaps two VGPR values."""
instructions = [
v_mov_b32_e32(v[0], 42),
v_mov_b32_e32(v[1], 99),
v_swap_b32_e32(v[0], v[1]),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][0], 99)
self.assertEqual(st.vgpr[0][1], 42)
def test_v_swap_b32_same_reg(self):
"""V_SWAP_B32 with same src and dst is a no-op."""
instructions = [
v_mov_b32_e32(v[0], 0xDEADBEEF),
v_swap_b32_e32(v[0], v[0]),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][0], 0xDEADBEEF)
def test_v_swap_b32_multi_lane(self):
"""V_SWAP_B32 swaps per-lane values independently."""
instructions = [
# v[0] = lane_id * 10, v[1] = lane_id * 100
v_lshlrev_b32_e32(v[0], 1, v[255]), # v[0] = lane_id * 2
v_add_nc_u32_e32(v[0], v[0], v[255]), # v[0] = lane_id * 3
v_mul_u32_u24_e32(v[1], 100, v[255]), # v[1] = lane_id * 100
v_swap_b32_e32(v[0], v[1]),
]
st = run_program(instructions, n_lanes=4)
for lane in range(4):
self.assertEqual(st.vgpr[lane][0], lane * 100)
self.assertEqual(st.vgpr[lane][1], lane * 3)
def test_v_swap_b32_chain(self):
"""Two swaps in sequence restore original values."""
instructions = [
v_mov_b32_e32(v[0], 0xAAAAAAAA),
v_mov_b32_e32(v[1], 0x55555555),
v_swap_b32_e32(v[0], v[1]),
v_swap_b32_e32(v[0], v[1]),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vgpr[0][0], 0xAAAAAAAA)
self.assertEqual(st.vgpr[0][1], 0x55555555)
if __name__ == '__main__':
unittest.main()
@@ -5,7 +5,7 @@ Includes: v_add_f32, v_mul_f32, v_and_b32, v_or_b32, v_xor_b32,
v_add_nc_u32, v_cndmask_b32, v_add_f16, v_mul_f16
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestBasicArithmetic(unittest.TestCase):
"""Tests for basic arithmetic VOP2 instructions."""
@@ -4,7 +4,7 @@ Includes: v_fma_f32, v_div_scale_f32, v_div_fmas_f32, v_div_fixup_f32,
v_alignbit_b32, v_bfe_i32, v_mad_u64_u32, v_readlane_b32, v_writelane_b32
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestFMA(unittest.TestCase):
"""Tests for FMA instructions."""
@@ -725,7 +725,7 @@ class TestLaneOps(unittest.TestCase):
# v[5] should have the value only in lane 1
for lane in range(4):
if lane == 1:
self.assertEqual(st.vgpr[lane][5], 0x12345678, "v[5] lane 1 should have 0x12345678")
self.assertEqual(st.vgpr[lane][5], 0x12345678, f"v[5] lane 1 should have 0x12345678")
else:
self.assertEqual(st.vgpr[lane][5], 0, f"v[5] lane {lane} should be 0")
@@ -1082,6 +1082,7 @@ class TestF64Ops(unittest.TestCase):
"""Full f64->i64 conversion sequence with negative value."""
import struct
val = f2i64(-8.0)
lit = 0xC1F00000 # high 32 bits of f64 -2^32
instructions = [
s_mov_b32(s[0], val & 0xffffffff),
s_mov_b32(s[1], (val >> 32) & 0xffffffff),
@@ -1137,6 +1138,7 @@ class TestF64Ops(unittest.TestCase):
# v_fma_f64 v[7:8], v[17:18], v[7:8], v[15:16]
# We need to capture the exact input values and verify output matches hardware
# v[7:8] before = 0x3f80fdf3_d69db28f (0.008296875941334462)
v78 = 0x3f80fdf3d69db28f
# For the FMA to produce 0xbf457ef0_ab8c254d, we need v[17:18] and v[15:16]
# Let's test with known precision-sensitive values
a = 1.0000000001
@@ -1393,7 +1395,7 @@ class TestWMMAMore(unittest.TestCase):
def test_v_wmma_f32_16x16x16_f16_basic(self):
"""V_WMMA_F32_16X16X16_F16 basic test - verify output is non-zero."""
instructions: list[Inst] = []
instructions = []
instructions.append(s_mov_b32(s[0], 0x3c003c00))
for i in range(16, 32):
instructions.append(v_mov_b32_e32(v[i], s[0]))
@@ -1849,6 +1851,7 @@ class TestMed3(unittest.TestCase):
def test_v_med3_f32_with_nan(self):
"""V_MED3_F32: NaN handling - returns min of non-NaN values."""
import math
instructions = [
s_mov_b32(s[0], 0x7fc00000), # NaN
v_mov_b32_e32(v[0], s[0]),
@@ -2487,6 +2490,7 @@ class TestDivScaleF64(unittest.TestCase):
independently. This catches the bug where the emulator was setting VCC
for all lanes to the same value.
"""
import math
# Use lane-varying input: lane 0 gets 2.0, lane 1 gets 3.0, etc.
# All normal values should result in VCC=0 for each lane
instructions = [
@@ -2717,6 +2721,7 @@ class TestDivScaleFmasF64Integration(unittest.TestCase):
This is the exact bug scenario: tan([2.0, 3.0, 4.0]) was failing because
VCC from DIV_SCALE was being set incorrectly for all lanes.
"""
import math
# Set up values like tan() would: different values per lane
instructions = [
# Create per-lane values: 2.0, 3.0, 4.0, 5.0
@@ -2754,7 +2759,7 @@ class TestVOP3VOPC(unittest.TestCase):
def test_v_cmp_ge_f32_e64_nan(self):
"""V_CMP_GE_F32_E64: |NaN| >= |0.0| should be FALSE (NaN comparisons always false)."""
from tinygrad.runtime.autogen.amd.rdna3.ins import VOP3_SDST
from extra.assembly.amd.autogen.rdna3.ins import VOP3_SDST
instructions = [
s_mov_b32(s[0], 0xffc00000), # NaN
s_mov_b32(s[1], 0x00000000), # 0.0
@@ -3,7 +3,7 @@
Includes: v_pk_add_f16, v_pk_mul_f16, v_pk_fma_f16, v_pack_b32_f16, v_wmma_*, v_dot2_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
class TestPackInstructions(unittest.TestCase):
"""Tests for pack instructions."""
@@ -418,7 +418,7 @@ class TestWMMAF16(unittest.TestCase):
def test_v_wmma_f16_16x16x16_f16_all_ones(self):
"""V_WMMA_F16_16X16X16_F16 with all ones produces 16.0 in f16."""
instructions: list[Inst] = []
instructions = []
instructions.append(s_mov_b32(s[0], 0x3c003c00)) # packed f16 1.0
# Initialize A matrix in v[16:23] (8 regs)
for i in range(16, 24):
@@ -442,7 +442,7 @@ class TestWMMAF16(unittest.TestCase):
def test_v_wmma_f16_16x16x16_f16_with_accumulator(self):
"""V_WMMA_F16_16X16X16_F16 with non-zero accumulator."""
instructions: list[Inst] = []
instructions = []
instructions.append(s_mov_b32(s[0], 0x3c003c00)) # packed f16 1.0
instructions.append(s_mov_b32(s[1], 0x4500)) # f16 5.0 in lo bits only
# Initialize A matrix in v[16:23] (8 regs)
@@ -471,7 +471,7 @@ class TestWMMAF16(unittest.TestCase):
Regression test: WMMA was using static register indices instead of dynamic.
This test uses v[64:71] for A, v[80:87] for B, v[96:103] for C/D.
"""
instructions: list[Inst] = []
instructions = []
instructions.append(s_mov_b32(s[0], 0x3c003c00)) # packed f16 1.0
# Initialize A matrix in v[64:71] (8 regs)
for i in range(64, 72):
@@ -502,7 +502,7 @@ class TestWMMA(unittest.TestCase):
def test_v_wmma_f32_16x16x16_f16_all_ones(self):
"""V_WMMA_F32_16X16X16_F16 with all ones produces 16.0."""
instructions: list[Inst] = []
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]))
@@ -518,7 +518,7 @@ class TestWMMA(unittest.TestCase):
def test_v_wmma_f32_16x16x16_f16_with_accumulator(self):
"""V_WMMA_F32_16X16X16_F16 with non-zero accumulator."""
instructions: list[Inst] = []
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):
@@ -540,7 +540,7 @@ class TestWMMA(unittest.TestCase):
causing incorrect results when registers weren't at the default positions.
This test uses v[64:71] for A, v[80:87] for B, v[96:103] for C/D.
"""
instructions: list[Inst] = []
instructions = []
instructions.append(s_mov_b32(s[0], 0x3c003c00)) # packed f16 1.0
# Initialize A matrix in v[64:71]
for i in range(64, 72):
@@ -569,7 +569,7 @@ class TestWMMABF16(unittest.TestCase):
def test_v_wmma_f32_16x16x16_bf16_all_ones(self):
"""V_WMMA_F32_16X16X16_BF16 with all ones produces 16.0."""
instructions: list[Inst] = []
instructions = []
# BF16 1.0 = 0x3f80, packed = 0x3f803f80
instructions.append(s_mov_b32(s[0], 0x3f803f80))
for i in range(16, 32):
@@ -586,7 +586,7 @@ class TestWMMABF16(unittest.TestCase):
def test_v_wmma_f32_16x16x16_bf16_with_accumulator(self):
"""V_WMMA_F32_16X16X16_BF16 with non-zero accumulator."""
instructions: list[Inst] = []
instructions = []
# BF16 1.0 = 0x3f80, packed = 0x3f803f80
instructions.append(s_mov_b32(s[0], 0x3f803f80))
instructions.append(s_mov_b32(s[1], f2i(5.0)))
@@ -3,7 +3,7 @@
Includes: v_cmp_class_f32, v_cmp_class_f16, v_cmp_eq_*, v_cmp_lt_*, v_cmp_gt_*
"""
import unittest
from test.amd.hw.helpers import *
from extra.assembly.amd.test.hw.helpers import *
VCC = 106 # SGPR index for VCC_LO
@@ -104,34 +104,6 @@ class TestCmpClass(unittest.TestCase):
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vcc & 1, 0, "Signaling NaN should not match quiet mask")
def test_v_cmp_lg_f32_nan(self):
"""v_cmp_lg_f32 is ordered not-equal (<>): NaN <> x should be False per IEEE 754."""
quiet_nan = 0x7fc00000
one_f32 = 0x3f800000 # 1.0f
instructions = [
s_mov_b32(s[0], quiet_nan),
v_mov_b32_e32(v[0], s[0]),
s_mov_b32(s[1], one_f32),
v_mov_b32_e32(v[1], s[1]),
v_cmp_lg_f32_e32(v[0], v[1]),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vcc & 1, 0, "v_cmp_lg_f32(NaN, 1.0) should be 0")
def test_v_cmp_neq_f32_nan(self):
"""v_cmp_neq_f32 is unordered not-equal (!=): NaN != x should be True per IEEE 754."""
quiet_nan = 0x7fc00000
one_f32 = 0x3f800000 # 1.0f
instructions = [
s_mov_b32(s[0], quiet_nan),
v_mov_b32_e32(v[0], s[0]),
s_mov_b32(s[1], one_f32),
v_mov_b32_e32(v[1], s[1]),
v_cmp_neq_f32_e32(v[0], v[1]),
]
st = run_program(instructions, n_lanes=1)
self.assertEqual(st.vcc & 1, 1, "v_cmp_neq_f32(NaN, 1.0) should be 1")
def test_v_cmp_sets_vcc_bits(self):
"""V_CMP_EQ sets VCC bits based on per-lane comparison."""
instructions = [
@@ -7,8 +7,9 @@ VOPD executes two operations simultaneously. Key behavior:
- Op Y can use ops 0-18 (includes ADD_NC_U32, LSHLREV, AND)
"""
import unittest
from test.amd.hw.helpers import run_program, v, v_mov_b32_e32
from tinygrad.runtime.autogen.amd.rdna3.ins import VOPD, VOPD_LIT, VOPDOp
from extra.assembly.amd.test.hw.helpers import run_program, run_program_emu, run_program_hw, compare_wave_states, \
v, s, v_mov_b32_e32, s_mov_b32
from extra.assembly.amd.autogen.rdna3.ins import VOPD, VOPD_LIT, VOPDOp
class TestVOPDBasic(unittest.TestCase):
"""Basic VOPD functionality tests."""
@@ -108,7 +109,7 @@ class TestVOPDLiterals(unittest.TestCase):
Tests that the 32-bit literal (SIMM32) is correctly passed to the instruction.
fma(2.0, 3.0, 10.0) = 2*3 + 10 = 16.0
"""
from test.amd.hw.helpers import f2i, i2f
from extra.assembly.amd.test.hw.helpers import f2i, i2f
instructions = [
v_mov_b32_e32(v[0], f2i(2.0)), # v[0] = 2.0
v_mov_b32_e32(v[1], f2i(3.0)), # v[1] = 3.0
@@ -126,7 +127,7 @@ class TestVOPDLiterals(unittest.TestCase):
Tests that the 32-bit literal (SIMM32) is correctly used as the multiplier.
fma(2.0, 5.0, 3.0) = 2*5 + 3 = 13.0
"""
from test.amd.hw.helpers import f2i, i2f
from extra.assembly.amd.test.hw.helpers import f2i, i2f
instructions = [
v_mov_b32_e32(v[0], f2i(2.0)), # v[0] = 2.0
v_mov_b32_e32(v[1], f2i(3.0)), # v[1] = 3.0
@@ -1,14 +1,11 @@
# Test to compare Python and Rust RDNA3 emulators by running real tinygrad kernels
import unittest, ctypes
from dataclasses import dataclass
from pathlib import Path
from tinygrad import Device
from test.mockgpu.amd.emu import WaveState, _decode_at, WAVE_SIZE, VCC_LO, EXEC_LO, SCC
from tinygrad.renderer.amd import decode_inst
import tinygrad
REMU_PATH = Path(tinygrad.__file__).parent.parent / "extra/remu/target/release/libremu.so"
if not REMU_PATH.exists(): REMU_PATH = Path(tinygrad.__file__).parent.parent / "extra/remu/target/release/libremu.dylib"
from extra.assembly.amd.emu import WaveState, decode_program, WAVE_SIZE, VCC_LO, EXEC_LO, SCC
from extra.assembly.amd import decode_inst
from extra.assembly.amd.test.helpers import KernelInfo
from extra.assembly.amd.test.bench_emu import REMU_PATH
def set_valid_mem_ranges(ranges): pass # emu2 doesn't need this
@@ -21,15 +18,6 @@ def _vals_equal(a: int, b: int) -> bool:
if a == b: return True
return _is_f32_nan(a) and _is_f32_nan(b)
@dataclass
class KernelSnapshot:
code: bytes
src: str
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
@dataclass
class StateSnapshot:
pc: int
@@ -93,14 +81,12 @@ class RustEmulator:
return snap.to_snapshot()
def free(self):
if self.ctx:
self.lib.wave_free(self.ctx)
self.ctx = None
if self.ctx: self.lib.wave_free(self.ctx); self.ctx = None
class PythonEmulator:
def __init__(self):
self.state: WaveState | None = None
self.program: dict[int, tuple] = {} # lazily populated: pc -> (name, fxn, globals)
self.program: dict | None = None
self.vmem_buf = None
self.lds_buf = None
self.kernel_buf = None # Keep kernel bytes alive
@@ -110,29 +96,27 @@ class PythonEmulator:
import ctypes
from tinygrad.device import Buffer, BufferSpec
from tinygrad.dtype import dtypes
# Store kernel in a ctypes buffer so _decode_at can read from memory at actual PC address
# Store kernel in a ctypes buffer so generic instructions can read from vmem at actual PC address
self.kernel_buf = (ctypes.c_char * len(kernel)).from_buffer_copy(kernel)
self.lib_addr = ctypes.addressof(self.kernel_buf)
self.program = {}
# Remap program dict to use actual addresses (like run_asm does)
program_raw = decode_program(kernel)
self.program = {self.lib_addr + offset: val for offset, val in program_raw.items()}
self.state = WaveState(n_lanes)
self.state.pc = self.lib_addr # Set PC to code base address
self.vmem_buf = Buffer('CPU', 1 << 40, dtypes.uint32, options=BufferSpec(external_ptr=0)).ensure_allocated()
self.lds_buf = Buffer('CPU', 65536 // 4, dtypes.uint32).ensure_allocated()
def _ensure_decoded(self, pc: int):
if pc not in self.program:
runner, _ = _decode_at(pc, "rdna3")
self.program[pc] = (runner.p.function_name, runner._prg.fxn, runner.p.globals)
def step(self) -> int:
import ctypes
assert self.state is not None
assert self.program is not None and self.state is not None
pc = self.state.pc
if pc == 0xFFFFFFFFFFFFFFFF: return -1
self._ensure_decoded(pc)
name, fxn, globals_list = self.program[pc]
buf_addrs = {0: self.state.sgpr_buf._buf.va_addr, 1: self.state.vgpr_buf._buf.va_addr, # type: ignore[union-attr]
2: self.vmem_buf._buf.va_addr, 3: self.lds_buf._buf.va_addr} # type: ignore[union-attr]
if pc == 0xFFFFFFFFFFFFFFFF or pc not in self.program: return -1
name, fxn, globals_list, _runner = self.program[pc]
if fxn is None: return 1 # unsupported instruction
buf_addrs = {0: self.state.sgpr_buf._buf.va_addr, 1: self.state.vgpr_buf._buf.va_addr,
2: self.vmem_buf._buf.va_addr, 3: self.lds_buf._buf.va_addr}
# Direct ctypes call - bypasses HCQ overhead
fxn(*[ctypes.c_uint64(buf_addrs[g]) for g in globals_list], ctypes.c_int32(0))
return -1 if self.state.pc == 0xFFFFFFFFFFFFFFFF else 0
@@ -153,7 +137,7 @@ class PythonEmulator:
exec_mask=sgpr[EXEC_LO.offset], sgpr=sgpr, vgpr=vgpr)
def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: tuple[int, int, int],
local_size: tuple[int, int, int], max_steps: int, debug: bool, trace_len: int,
local_size: tuple[int, int, int], program, max_steps: int, debug: bool, trace_len: int,
kernel_idx: int = 0, max_workgroups: int = 8) -> tuple[bool, str, int]:
"""Run a single kernel through both emulators. Returns (success, message, total_steps)."""
gx, gy, gz = global_size
@@ -194,9 +178,8 @@ def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: t
rust_before = rust.get_snapshot()
python_before = python.get_snapshot()
pc_addr = python.lib_addr + python_before.pc * 4 # Convert word offset to actual address
python._ensure_decoded(pc_addr)
inst_hex_name = python.program[pc_addr][0]
inst_info = python.program.get(python.lib_addr + python_before.pc * 4) # Convert word offset to actual address
inst_hex_name = inst_info[0] if inst_info else f"unknown at PC={python_before.pc}"
# Decode the instruction to get mnemonic for sync_after checks
try:
# Format is mnemonic_hexbytes, e.g. v_exp_f32_e32_014b027e -> hex is 014b027e
@@ -205,7 +188,7 @@ def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: t
inst_bytes = bytes.fromhex(inst_bytes_hex) if inst_bytes_hex else b''
decoded = decode_inst(inst_bytes) if inst_bytes else None
inst_mnemonic = repr(decoded).split('(')[0] if decoded else ""
except Exception:
except:
inst_mnemonic = ""
# For generic instructions, use function name for sync_after check
if not inst_mnemonic: inst_mnemonic = inst_hex_name
@@ -237,18 +220,16 @@ def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: t
python_diffs = pb.diff(next_pb, n_lanes, "->")
if rust_diffs: trace_lines.append(f" rust: {', '.join(rust_diffs[:5])}")
if python_diffs: trace_lines.append(f" python: {', '.join(python_diffs[:5])}")
elif rust_diffs: trace_lines.append(" python: (no changes)")
elif rust_diffs: trace_lines.append(f" python: (no changes)")
else:
# Last traced instruction - compare with current state
rust_diffs = rb.diff(rust_before, n_lanes, "->")
python_diffs = pb.diff(python_before, n_lanes, "->")
if rust_diffs: trace_lines.append(f" rust: {', '.join(rust_diffs[:5])}")
if python_diffs: trace_lines.append(f" python: {', '.join(python_diffs[:5])}")
elif rust_diffs: trace_lines.append(" python: (no changes)")
elif rust_diffs: trace_lines.append(f" python: (no changes)")
trace_str = "\n".join(trace_lines)
msg = f"K{kernel_idx} WG({gidx},{gidy},{gidz}) Step {step} before inst '{inst_str}': states differ (rust vs python):\n "
msg += "\n ".join(diffs[:10]) + f"\n Recent instructions:\n{trace_str}"
return False, msg, total_steps
return False, f"K{kernel_idx} WG({gidx},{gidy},{gidz}) Step {step} before inst '{inst_str}': states differ (rust vs python):\n " + "\n ".join(diffs[:10]) + f"\n Recent instructions:\n{trace_str}", total_steps
rust_result = rust.step()
python_result = python.step()
@@ -258,9 +239,7 @@ def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: t
if rust_result == 1 and python_result == 0:
raise unittest.SkipTest(f"Rust emulator doesn't support instruction: {inst_str}")
trace_str = "\n".join(f" step {s}: PC={pc:3d} {d}" for s, pc, d, _, _ in trace)
msg = (f"K{kernel_idx} WG({gidx},{gidy},{gidz}) Step {step}: different return codes: "
f"rust={rust_result}, python={python_result}, inst={inst_str}\n Recent instructions:\n{trace_str}")
return False, msg, total_steps
return False, f"K{kernel_idx} WG({gidx},{gidy},{gidz}) Step {step}: different return codes: rust={rust_result}, python={python_result}, inst={inst_str}\n Recent instructions:\n{trace_str}", total_steps
# Sync Python state to Rust after instructions with known Rust emulator differences
if sync_after:
@@ -293,7 +272,7 @@ def run_single_kernel(kernel: bytes, n_lanes: int, args_ptr: int, global_size: t
return True, f"Completed {gx*gy*gz} workgroups", total_steps
def compare_emulators_multi_kernel(kernels: list[KernelSnapshot], buf_pool: dict[int, int], max_steps: int = 1000,
def compare_emulators_multi_kernel(kernels: list[KernelInfo], buf_pool: dict[int, int], max_steps: int = 1000,
debug: bool = False, trace_len: int = 10, buf_data: dict[int, bytes] | None = None) -> tuple[bool, str]:
"""Run all kernels through both emulators with shared buffer pool."""
if buf_data is None: buf_data = {}
@@ -323,11 +302,12 @@ def compare_emulators_multi_kernel(kernels: list[KernelSnapshot], buf_pool: dict
kernel_ranges = ranges | {(args_ptr, ctypes.sizeof(args))}
set_valid_mem_ranges(kernel_ranges)
program = decode_program(kernel.code)
n_lanes = kernel.local_size[0] * kernel.local_size[1] * kernel.local_size[2]
ok, msg, steps = run_single_kernel(
kernel.code, min(n_lanes, 32), args_ptr, kernel.global_size,
kernel.local_size, max_steps, debug, trace_len, ki
kernel.local_size, program, max_steps, debug, trace_len, ki
)
total_steps += steps
if not ok:
@@ -353,11 +333,12 @@ def compare_emulators_with_memory(kernel: bytes, n_lanes: int, buf_sizes: list,
ranges.add((args_ptr, ctypes.sizeof(args)))
set_valid_mem_ranges(ranges)
program = decode_program(kernel)
# Legacy wrapper assumes local_size = (n_lanes, 1, 1)
ok, msg, _ = run_single_kernel(kernel, n_lanes, args_ptr, global_size, (n_lanes, 1, 1), max_steps, debug, trace_len)
ok, msg, _ = run_single_kernel(kernel, n_lanes, args_ptr, global_size, (n_lanes, 1, 1), program, max_steps, debug, trace_len)
return ok, msg
def get_kernels_from_tinygrad(op_fn) -> tuple[list[KernelSnapshot], dict[int, int], dict[int, bytes]]:
def get_kernels_from_tinygrad(op_fn) -> tuple[list[KernelInfo], dict[int, int], dict[int, bytes]]:
"""Compile a tinygrad operation and extract all kernels with their buffer mappings."""
from tinygrad import Tensor
from tinygrad.runtime.support.elf import elf_loader
@@ -395,7 +376,7 @@ def get_kernels_from_tinygrad(op_fn) -> tuple[list[KernelSnapshot], dict[int, in
buf_pool[buf_id] = b.nbytes
buf_idxs.append(buf_id)
buf_sizes.append(b.nbytes)
kernels.append(KernelSnapshot(
kernels.append(KernelInfo(
code=bytes(sec.content),
src=lowered.prg.p.src,
global_size=tuple(lowered.prg.p.global_size),
@@ -412,7 +393,6 @@ def get_kernel_from_tinygrad(op_fn) -> tuple[bytes, tuple[int, int, int], tuple[
k = kernels[-1]
return k.code, k.global_size, k.local_size, k.buf_sizes
@unittest.skipUnless(Device.DEFAULT == "AMD", "requires AMD device")
class TestTinygradKernels(unittest.TestCase):
"""Compare emulators on real tinygrad-compiled kernels."""
@@ -449,8 +429,7 @@ class TestTinygradKernels(unittest.TestCase):
def test_cast(self): self._test_kernel(lambda T: T.empty(32).half().float() + T.empty(32).int().float())
# Pooling - regression for VCC wave32 mode
def test_pool2d(self):
self._test_kernel(lambda T: T.empty(1, 1, 8, 8).avg_pool2d(kernel_size=(4,4)) + T.empty(1, 1, 8, 8).max_pool2d(kernel_size=(4,4)))
def test_pool2d(self): self._test_kernel(lambda T: T.empty(1, 1, 8, 8).avg_pool2d(kernel_size=(4,4)) + T.empty(1, 1, 8, 8).max_pool2d(kernel_size=(4,4)))
# Convolution
def test_conv2d(self): self._test_kernel(lambda T: T.empty(1, 2, 8, 8).conv2d(T.empty(2, 2, 3, 3)), max_steps=50000)
@@ -1,12 +1,22 @@
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 tinygrad.runtime.autogen.amd.rdna3.ins import *
from tinygrad.renderer.amd.dsl import s, v
from extra.assembly.amd.autogen.rdna3.ins import *
from extra.assembly.amd.dsl import s, v, Inst
def custom_add_one(A:UOp) -> UOp:
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")
@@ -21,10 +31,10 @@ def custom_add_one(A:UOp) -> UOp:
global_store_b32(addr=v[0], data=v[1], saddr=s[0:1]),
s_endpgm(),
]
sink = UOp.sink(A.base, threads, arg=KernelInfo(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=tuple([UOp(Ops.INS, arg=x) for x in insts]))))
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)))
def custom_add_var(A:UOp, B:UOp) -> UOp:
def custom_add_var(A:UOp, B:UOp, arch:str) -> UOp:
A,B = A.flatten(), B.flatten()
assert A.dtype.base == dtypes.uint32, f"buffer dtype must be uint32, got {A.dtype}"
threads = UOp.special(A.size, "lidx0")
@@ -40,14 +50,14 @@ def custom_add_var(A:UOp, B:UOp) -> UOp:
global_store_b32(addr=v[0], data=v[1], saddr=s[4:5]),
s_endpgm(),
]
sink = UOp.sink(A.base, B.base, var, threads, arg=KernelInfo(f"custom_add_var_{A.size}"))
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]))))
sink = UOp.sink(A.base, B.base, var, threads, arg=KernelInfo(name:=f"custom_add_one_{A.size}"))
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=(*sink.src, sink)),
*assemble_insts(insts, name, arch, kernarg_size=16)))
@unittest.skipUnless(Device.DEFAULT == "AMD", "requires AMD device")
class TestCustomKernel(unittest.TestCase):
def test_simple(self):
a = Tensor.full((16, 16), 1.).contiguous().realize()
a = Tensor.custom_kernel(a, fxn=custom_add_one)[0]
a = Tensor.custom_kernel(a, fxn=functools.partial(custom_add_one, arch=Device[Device.DEFAULT].renderer.arch))[0]
ei = a.schedule()[-1].lower()
self.assertEqual(ei.prg.estimates.ops, a.numel())
self.assertEqual(ei.prg.estimates.mem, a.nbytes()*2)
@@ -57,7 +67,7 @@ class TestCustomKernel(unittest.TestCase):
def test_variable(self):
b = Tensor.full((16, 16), 1, dtype=dtypes.uint32).contiguous().realize()
a = Tensor.zeros_like(b).contiguous().realize()
a = Tensor.custom_kernel(a, b, fxn=custom_add_var)[0]
a = Tensor.custom_kernel(a, b, fxn=functools.partial(custom_add_var, arch=Device[Device.DEFAULT].renderer.arch))[0]
ei = a.schedule()[-1].lower()
for i in range(4):
ei.run({"var":i})
@@ -1,8 +1,8 @@
import unittest
from tinygrad.renderer.amd.dsl import *
from tinygrad.renderer.amd.dsl import VDSTYField
from tinygrad.runtime.autogen.amd.rdna3.enum import VOP1Op, VOP2Op
from tinygrad.runtime.autogen.amd.rdna3.ins import VOP1
from extra.assembly.amd.dsl import *
from extra.assembly.amd.dsl import VDSTYField
from extra.assembly.amd.autogen.rdna3.enum import VOP1Op, VOP2Op
from extra.assembly.amd.autogen.rdna3.ins import VOP1
class TestRegisters(unittest.TestCase):
def test_vgpr_single(self):
@@ -4,14 +4,14 @@ from collections import defaultdict
from tinygrad.helpers import DEBUG
from tinygrad.dtype import dtypes
from tinygrad.uop.ops import UOp, Ops
from test.mockgpu.amd.emu import parse_pcode
from test.mockgpu.amd.pcode import parse_expr
from tinygrad.runtime.autogen.amd.rdna3.str_pcode import PCODE
from tinygrad.runtime.autogen.amd.rdna3.enum import VOP1Op, VOP2Op, SOP2Op, DSOp
from extra.assembly.amd.emu import parse_pcode
from extra.assembly.amd.pcode import parse_expr
from extra.assembly.amd.autogen.rdna3.str_pcode import PCODE
from extra.assembly.amd.autogen.rdna3.enum import VOP1Op, VOP2Op, VOP3Op, SOP1Op, SOP2Op, DSOp
def _srcs():
"""Create minimal source variables for pcode parsing."""
def u32(v=0): return UOp.const(dtypes.uint32, v)
u32 = lambda v=0: UOp.const(dtypes.uint32, v)
return {'S0': u32(), 'S1': u32(), 'S2': u32(), 'SCC': u32(), 'VCC': UOp.const(dtypes.uint64, 0), 'laneId': u32()}
class TestBasicParsing(unittest.TestCase):
@@ -90,16 +90,16 @@ class TestParseExpr(unittest.TestCase):
def test_variable_lookup(self):
"""Test variable lookup in parse_expr."""
vrs = {'x': UOp.const(dtypes.uint32, 42)}
result = parse_expr('x', vrs)
vars = {'x': UOp.const(dtypes.uint32, 42)}
result = parse_expr('x', vars)
self.assertEqual(result.arg, 42)
def test_binary_ops(self):
"""Test parsing binary operations."""
vrs = {'a': UOp.const(dtypes.uint32, 10), 'b': UOp.const(dtypes.uint32, 5)}
vars = {'a': UOp.const(dtypes.uint32, 10), 'b': UOp.const(dtypes.uint32, 5)}
# Addition
result = parse_expr('a + b', vrs)
result = parse_expr('a + b', vars)
self.assertEqual(result.op, Ops.ADD)
# Subtraction with constant folding
@@ -109,8 +109,8 @@ class TestParseExpr(unittest.TestCase):
def test_ternary(self):
"""Test parsing ternary expressions."""
vrs = {'cond': UOp.const(dtypes.bool, True), 'a': UOp.const(dtypes.uint32, 1), 'b': UOp.const(dtypes.uint32, 0)}
result = parse_expr('cond ? a : b', vrs)
vars = {'cond': UOp.const(dtypes.bool, True), 'a': UOp.const(dtypes.uint32, 1), 'b': UOp.const(dtypes.uint32, 0)}
result = parse_expr('cond ? a : b', vars)
self.assertEqual(result.op, Ops.WHERE)
class TestForLoopParsing(unittest.TestCase):
@@ -120,14 +120,13 @@ class TestForLoopParsing(unittest.TestCase):
"""Verify CLZ pcode is available."""
pcode = PCODE.get(VOP1Op.V_CLZ_I32_U32_E32)
self.assertIsNotNone(pcode)
assert pcode is not None
self.assertIn('for', pcode.lower())
def test_clz_parsing(self):
"""Test CLZ pcode parsing produces correct structure."""
pcode = PCODE[VOP1Op.V_CLZ_I32_U32_E32]
S0 = UOp.const(dtypes.uint32, 0xFFFFFFFF) # All ones - CLZ should be 0
_vrs, assigns = parse_pcode(pcode, {'S0': S0})
vars, assigns = parse_pcode(pcode, {'S0': S0})
self.assertEqual(len(assigns), 1)
dest, val = assigns[0]
@@ -139,7 +138,7 @@ class TestForLoopParsing(unittest.TestCase):
"""Test CLZ with input 0 - should return -1."""
pcode = PCODE[VOP1Op.V_CLZ_I32_U32_E32]
S0 = UOp.const(dtypes.uint32, 0)
_vrs, assigns = parse_pcode(pcode, {'S0': S0})
vars, assigns = parse_pcode(pcode, {'S0': S0})
# Check that the innermost value (default) is -1 (may be wrapped in CAST)
val = assigns[0][1]
@@ -158,7 +157,7 @@ class TestForLoopParsing(unittest.TestCase):
self.skipTest("V_CTZ_I32_B32_E32 pcode not available")
S0 = UOp.const(dtypes.uint32, 1) # LSB set - CTZ should be 0
_vrs, assigns = parse_pcode(pcode, {'S0': S0})
vars, assigns = parse_pcode(pcode, {'S0': S0})
self.assertEqual(len(assigns), 1)
class TestDSPcodePatterns(unittest.TestCase):
@@ -168,7 +167,6 @@ class TestDSPcodePatterns(unittest.TestCase):
"""Test DS_LOAD_B32 pcode is parseable."""
pcode = PCODE.get(DSOp.DS_LOAD_B32)
self.assertIsNotNone(pcode)
assert pcode is not None
self.assertIn('RETURN_DATA', pcode)
self.assertIn('MEM[', pcode)
@@ -176,7 +174,6 @@ class TestDSPcodePatterns(unittest.TestCase):
"""Test DS_STORE_B32 pcode is parseable."""
pcode = PCODE.get(DSOp.DS_STORE_B32)
self.assertIsNotNone(pcode)
assert pcode is not None
self.assertIn('MEM[', pcode)
self.assertIn('DATA', pcode)
@@ -185,9 +182,9 @@ class TestDSPcodePatterns(unittest.TestCase):
# Create a mock LDS buffer
lds = UOp(Ops.PARAM, dtypes.uint32.ptr(16384), arg=3)
addr = UOp.const(dtypes.uint32, 0)
vrs = {'_lds': lds, 'ADDR': addr, 'OFFSET': UOp.const(dtypes.uint32, 0)}
vars = {'_lds': lds, 'ADDR': addr, 'OFFSET': UOp.const(dtypes.uint32, 0)}
result = parse_expr('MEM[ADDR + OFFSET].b32', vrs)
result = parse_expr('MEM[ADDR + OFFSET].b32', vars)
# Should be an INDEX operation into LDS
self.assertIsNotNone(result)
@@ -195,7 +192,6 @@ class TestDSPcodePatterns(unittest.TestCase):
"""Test DS_STORE_2ADDR_B32 pcode parsing produces MEM writes."""
pcode = PCODE.get(DSOp.DS_STORE_2ADDR_B32)
self.assertIsNotNone(pcode)
assert pcode is not None
srcs = {
'ADDR': UOp.const(dtypes.uint32, 0),
'OFFSET0': UOp.const(dtypes.uint32, 0),
@@ -211,13 +207,12 @@ class TestDSPcodePatterns(unittest.TestCase):
self.assertTrue(dest.startswith('MEM['))
# val should be (addr, write_val) tuple
self.assertIsInstance(val, tuple)
self.assertEqual(len(val), 2) # type: ignore[arg-type]
self.assertEqual(len(val), 2)
def test_ds_load_2addr_b32_parsing(self):
"""Test DS_LOAD_2ADDR_B32 pcode parsing produces RETURN_DATA assignments."""
pcode = PCODE.get(DSOp.DS_LOAD_2ADDR_B32)
self.assertIsNotNone(pcode)
assert pcode is not None
lds = UOp(Ops.PARAM, dtypes.uint32.ptr(16384), arg=3)
srcs = {
'ADDR': UOp.const(dtypes.uint32, 0),
@@ -235,7 +230,6 @@ class TestDSPcodePatterns(unittest.TestCase):
def test_ds_store_address_calculation(self):
"""Test DS_STORE_2ADDR_B32 calculates correct addresses (offset * 4)."""
pcode = PCODE.get(DSOp.DS_STORE_2ADDR_B32)
assert pcode is not None
srcs = {
'ADDR': UOp.const(dtypes.uint32, 100),
'OFFSET0': UOp.const(dtypes.uint32, 2),
@@ -246,14 +240,14 @@ class TestDSPcodePatterns(unittest.TestCase):
srcs['laneId'] = UOp.const(dtypes.uint32, 0)
_, assigns = parse_pcode(pcode, srcs)
# Check addresses: 100 + 2*4 = 108, 100 + 5*4 = 120
# assigns[i][1] is (addr, val) tuple for MEM writes; mypy sees UOp
self.assertEqual(assigns[0][1][0].simplify().arg, 108) # type: ignore[index]
self.assertEqual(assigns[1][1][0].simplify().arg, 120) # type: ignore[index]
addr0, _ = assigns[0][1]
addr1, _ = assigns[1][1]
self.assertEqual(addr0.simplify().arg, 108)
self.assertEqual(addr1.simplify().arg, 120)
def test_ds_store_data_values(self):
"""Test DS_STORE_2ADDR_B32 uses correct data values."""
pcode = PCODE.get(DSOp.DS_STORE_2ADDR_B32)
assert pcode is not None
srcs = {
'ADDR': UOp.const(dtypes.uint32, 0),
'OFFSET0': UOp.const(dtypes.uint32, 0),
@@ -263,10 +257,11 @@ class TestDSPcodePatterns(unittest.TestCase):
}
srcs['laneId'] = UOp.const(dtypes.uint32, 0)
_, assigns = parse_pcode(pcode, srcs)
# assigns[i][1] is (addr, val) tuple for MEM writes; mypy sees UOp
_, val0 = assigns[0][1]
_, val1 = assigns[1][1]
# DATA[31:0] should preserve the value
self.assertEqual(assigns[0][1][1].simplify().arg, 0xAAAAAAAA) # type: ignore[index]
self.assertEqual(assigns[1][1][1].simplify().arg, 0xBBBBBBBB) # type: ignore[index]
self.assertEqual(val0.simplify().arg, 0xAAAAAAAA)
self.assertEqual(val1.simplify().arg, 0xBBBBBBBB)
class TestConditionalParsing(unittest.TestCase):
"""Test conditional (if/elsif/else) pcode parsing."""
@@ -278,7 +273,7 @@ class TestConditionalParsing(unittest.TestCase):
s0 = UOp.const(dtypes.uint32, 10)
s1 = UOp.const(dtypes.uint32, 20)
scc = UOp.const(dtypes.uint32, 1)
_vrs, assigns = parse_pcode(pcode, {'S0': s0, 'S1': s1, 'SCC': scc})
vars, assigns = parse_pcode(pcode, {'S0': s0, 'S1': s1, 'SCC': scc})
self.assertEqual(len(assigns), 1)
dest, val = assigns[0]
self.assertTrue(dest.startswith('D0'))
@@ -299,8 +294,7 @@ class TestAllPcode(unittest.TestCase):
'ADDR': u32(), 'ADDR_BASE': u32(), 'TADDR': u32(), 'DATA': u32(), 'DATA0': u32(), 'DATA1': u32(), 'DATA2': u32(),
'VDATA': u32(), 'VDATA0': u32(), 'VDATA1': u32(), 'VDATA2': u32(), 'VDATA3': u32(),
'OPSEL': u32(), 'OPSEL_HI': u32(), 'NEG': u32(), 'NEG_HI': u32(), 'CLAMP': u32(),
'M0': u32(), 'PC': u64(), 'DENORM': u32(1), 'ROUND_MODE': u32(), 'ROUND_TOWARD_ZERO': u32(),
'ROUND_NEAREST_EVEN': u32(), 'WAVE_STATUS': u32(),
'M0': u32(), 'PC': u64(), 'DENORM': u32(1), 'ROUND_MODE': u32(), 'ROUND_TOWARD_ZERO': u32(), 'ROUND_NEAREST_EVEN': u32(), 'WAVE_STATUS': u32(),
'MAX_FLOAT_F32': u32(0x7f7fffff), 'Unsigned': u32(1), 'clampedLOD': u32(),
'_lds': lds, '_vmem': lds, '_active': UOp.const(dtypes.bool, True)}
@@ -312,9 +306,7 @@ class TestAllPcode(unittest.TestCase):
try:
parse_pcode(pcode, srcs)
passed += 1
except RuntimeError as e:
skipped += 1
errors[str(e)].append(op.name)
except RuntimeError as e: skipped += 1; errors[str(e)].append(op.name)
except Exception as e: self.fail(f"[{arch}] {op.name}: {e}\nPcode: {pcode[:200]}")
total = len(pcode_dict)
pct = 100 * passed / total
@@ -325,15 +317,15 @@ class TestAllPcode(unittest.TestCase):
self.assertGreaterEqual(pct, min_pct, f"[{arch}] {pct:.1f}% < {min_pct}% threshold")
def test_parse_all_cdna_pcode(self):
from tinygrad.runtime.autogen.amd.cdna.str_pcode import PCODE as CDNA_PCODE
from extra.assembly.amd.autogen.cdna.str_pcode import PCODE as CDNA_PCODE
self._parse_all_pcode(CDNA_PCODE, "CDNA", min_pct=60)
def test_parse_all_rdna3_pcode(self):
from tinygrad.runtime.autogen.amd.rdna3.str_pcode import PCODE as RDNA3_PCODE
from extra.assembly.amd.autogen.rdna3.str_pcode import PCODE as RDNA3_PCODE
self._parse_all_pcode(RDNA3_PCODE, "RDNA3", min_pct=90)
def test_parse_all_rdna4_pcode(self):
from tinygrad.runtime.autogen.amd.rdna4.str_pcode import PCODE as RDNA4_PCODE
from extra.assembly.amd.autogen.rdna4.str_pcode import PCODE as RDNA4_PCODE
self._parse_all_pcode(RDNA4_PCODE, "RDNA4", min_pct=65)
if __name__ == "__main__":
@@ -4,10 +4,10 @@
Note: Graphics-only formats (EXP, MUBUF, MTBUF, MIMG) are not supported - use GLOBAL/FLAT for memory access in compute.
"""
import unittest
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from tinygrad.renderer.amd.dsl import VCC_HI, EXEC_LO, NULL
from extra.assembly.amd.autogen.rdna3.ins import *
from extra.assembly.amd.dsl import VCC_HI, EXEC_LO, NULL
OFF = NULL # OFF is alias for NULL
from tinygrad.renderer.amd import detect_format
from extra.assembly.amd import detect_format
class TestDS(unittest.TestCase):
@@ -2,10 +2,9 @@
# the Inst constructor should be looking at the types of the fields to correctly set the value
import unittest, struct
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from tinygrad.renderer.amd.dsl import Inst
from test.amd.test_roundtrip import compile_asm
from test.amd.disasm import disasm
from extra.assembly.amd.autogen.rdna3.ins import *
from extra.assembly.amd.dsl import Inst
from extra.assembly.amd.test.test_roundtrip import compile_asm
class IntegrationTestBase(unittest.TestCase):
inst: Inst
@@ -13,7 +12,7 @@ class IntegrationTestBase(unittest.TestCase):
def tearDown(self):
if not hasattr(self, 'inst'): return
b = self.inst.to_bytes()
st = disasm(self.inst)
st = self.inst.disasm()
# Test that the instruction can be compiled by LLVM and produces the same bytes
desc = f"{st:25s} {self.inst} {b!r}"
self.assertEqual(b, compile_asm(st, arch=self.arch), desc)
@@ -133,11 +132,11 @@ class TestIntegrationCDNA(IntegrationTestBase):
arch = "cdna"
def test_mfma(self):
from tinygrad.runtime.autogen.amd.cdna.ins import v_mfma_f32_16x16x16_f16
from extra.assembly.amd.autogen.cdna.ins import v_mfma_f32_16x16x16_f16
self.inst = v_mfma_f32_16x16x16_f16(v[0:3], v[0:1], v[0:1], 0)
def test_mfma_fp8(self):
from tinygrad.runtime.autogen.amd.cdna.ins import v_mfma_f32_16x16x128_f8f6f4
from extra.assembly.amd.autogen.cdna.ins import v_mfma_f32_16x16x128_f8f6f4
self.inst = v_mfma_f32_16x16x128_f8f6f4(v[0:3], v[0:5], v[0:5], 1, cbsz=2, blgp=2)
class TestRegisterSliceSyntax(unittest.TestCase):
@@ -161,9 +160,9 @@ class TestRegisterSliceSyntax(unittest.TestCase):
# 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)
d = disasm(inst)
disasm = inst.disasm()
# Disasm shows s[4:7] - user should be able to copy this back
self.assertIn("s[4:7]", d)
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.sz, 4, "s[4:7] from disasm should give 4 registers")
+258
View File
@@ -0,0 +1,258 @@
#!/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()
@@ -8,11 +8,11 @@ Only compute-relevant instruction formats are tested. Graphics-only formats not
- VIMAGE/VSAMPLE: image sampling instructions (RDNA4)
- VBUFFER: buffer instructions (RDNA4)
"""
import unittest, re, functools
import unittest, re, subprocess, functools
from tinygrad.helpers import fetch
from test.amd.disasm import disasm
from tinygrad.renderer.amd import decode_inst, detect_format
from test.amd.helpers import llvm_assemble, llvm_filter_valid_asm, get_target, get_mattr
from extra.assembly.amd.disasm import disasm
from extra.assembly.amd import decode_inst, detect_format
from extra.assembly.amd.test.helpers import get_llvm_mc, get_target, get_mattr
LLVM_BASE = "https://raw.githubusercontent.com/llvm/llvm-project/llvmorg-21.1.0/llvm/test/MC/AMDGPU"
@@ -40,7 +40,7 @@ RDNA4_FILES = ['gfx12_asm_sop1.s', 'gfx12_asm_sop2.s', 'gfx12_asm_sopp.s', 'gfx1
'gfx12_asm_vop1.s', 'gfx12_asm_vop2.s', 'gfx12_asm_vopc.s', 'gfx12_asm_vopcx.s', 'gfx12_asm_vop3.s', 'gfx12_asm_vop3c.s',
'gfx12_asm_vop3cx.s', 'gfx12_asm_vop3p.s', 'gfx12_asm_vop3_from_vop1.s', 'gfx12_asm_vop3_from_vop2.s',
'gfx12_asm_vop3p_features.s', 'gfx12_asm_vopd.s', 'gfx12_asm_vopd_features.s',
'gfx12_asm_ds.s', 'gfx12_asm_smem.s', 'gfx12_asm_vflat.s',
'gfx12_asm_ds.s', 'gfx12_asm_smem.s',
'gfx12_asm_wmma_w32.s']
def _parse_llvm_tests(text: str, pattern: str) -> list[tuple[str, bytes]]:
@@ -74,13 +74,42 @@ def _get_tests_uncached(f: str, arch: str) -> list[tuple[str, bytes]]:
# Exclude v_interp_* (graphics-only, not on CDNA)
if arch == "cdna": tests = [(asm, data) for asm, data in tests if not asm.startswith('v_interp_')]
# Filter out tests where original ASM isn't valid on target (e.g., gfx9 tests with gfx942/gfx950 constraints)
if arch == "cdna" and not ('gfx942' in f or 'gfx950' in f or 'gfx90a' in f):
tests = llvm_filter_valid_asm(tests, get_target(arch), get_mattr(arch))
if arch == "cdna" and not ('gfx942' in f or 'gfx950' in f or 'gfx90a' in f): tests = _filter_valid_asm(tests, arch)
return tests
@functools.cache
def _get_tests(f: str, arch: str) -> list[tuple[str, bytes]]: return _get_tests_uncached(f, arch)
def _compile_asm_batch(instrs: list[str], arch: str = "rdna3", mcpu: str|None = None) -> list[bytes]:
if not instrs: return []
mcpu, mattr = mcpu or get_target(arch), get_mattr(arch)
result = subprocess.run([get_llvm_mc(), '-triple=amdgcn', f'-mcpu={mcpu}', f'-mattr={mattr}', '-show-encoding'],
input=".text\n" + "\n".join(instrs) + "\n", capture_output=True, text=True, timeout=30)
if result.returncode != 0: raise RuntimeError(f"llvm-mc failed: {result.stderr.strip()}")
return [bytes.fromhex(line.split('encoding:')[1].strip()[1:-1].replace('0x', '').replace(',', '').replace(' ', ''))
for line in result.stdout.split('\n') if 'encoding:' in line]
def _filter_valid_asm(tests: list[tuple[str, bytes]], arch: str) -> list[tuple[str, bytes]]:
"""Filter out tests where the original ASM isn't valid on the target (e.g., gfx9 tests with gfx942/gfx950 constraints)."""
if not tests: return []
mcpu = get_target(arch)
# Batch assemble all instructions, parse stderr to find which lines failed
instrs = [asm for asm, _ in tests]
result = subprocess.run([get_llvm_mc(), '-triple=amdgcn', f'-mcpu={mcpu}', '-show-encoding'],
input=".text\n" + "\n".join(instrs) + "\n", capture_output=True, text=True, timeout=30)
# Parse error lines from stderr (format: "<stdin>:N:..." where N is 1-indexed, line 1 is ".text")
failed_lines = set()
for line in result.stderr.split('\n'):
if m := re.match(r'<stdin>:(\d+):', line): failed_lines.add(int(m.group(1)) - 1) # -1 for .text, so line 2 -> index 1 -> tests[0]
# Also filter out tests where LLVM roundtrip doesn't match original (reserved bits set in original)
valid = [(asm, data) for i, (asm, data) in enumerate(tests) if (i + 1) not in failed_lines]
if not valid: return []
llvm_result = subprocess.run([get_llvm_mc(), '-triple=amdgcn', f'-mcpu={mcpu}', '-show-encoding'],
input=".text\n" + "\n".join(asm for asm, _ in valid) + "\n", capture_output=True, text=True, timeout=30)
llvm_bytes = [bytes.fromhex(line.split('encoding:')[1].strip()[1:-1].replace('0x', '').replace(',', '').replace(' ', ''))
for line in llvm_result.stdout.split('\n') if 'encoding:' in line]
return [(asm, data) for (asm, data), lb in zip(valid, llvm_bytes) if lb == data]
def _make_test(f: str, arch: str, test_type: str):
def test(self):
tests = _get_tests(f, arch)
@@ -98,17 +127,15 @@ def _make_test(f: str, arch: str, test_type: str):
self.assertEqual(skipped, 0, f"{name}: {skipped} tests skipped, expected 0")
elif test_type == "repr":
# Test that eval(repr(inst)) reproduces the instruction
if arch == "rdna3": import tinygrad.runtime.autogen.amd.rdna3.ins as ins # type: ignore[no-redef]
elif arch == "rdna4": import tinygrad.runtime.autogen.amd.rdna4.ins as ins # type: ignore[no-redef]
elif arch == "cdna": import tinygrad.runtime.autogen.amd.cdna.ins as ins # type: ignore[no-redef]
if arch == "rdna3": import extra.assembly.amd.autogen.rdna3.ins as ins
elif arch == "rdna4": import extra.assembly.amd.autogen.rdna4.ins as ins
elif arch == "cdna": import extra.assembly.amd.autogen.cdna.ins as ins
ns = {k: getattr(ins, k) for k in dir(ins) if not k.startswith('_')}
passed, skipped = 0, 0
for _, data in tests:
try:
decoded = detect_format(data, arch).from_bytes(data)
if decoded.to_bytes()[:len(data)] != data:
skipped += 1
continue # skip if binary roundtrip fails
if decoded.to_bytes()[:len(data)] != data: skipped += 1; continue # skip if binary roundtrip fails
r = repr(decoded)
try:
decoded2 = eval(r, ns) # noqa: S307
@@ -126,12 +153,12 @@ def _make_test(f: str, arch: str, test_type: str):
enc = decoded.to_bytes()[:len(data)]
# Skip if roundtrip fails, disasm fails, or op_name is missing (disasm starts with space)
if enc == data and (d := disasm(decoded)) and not d.startswith(' '): to_test.append((enc, d))
except Exception: pass
except: pass
skipped = len(tests) - len(to_test)
print(f"{name}: {len(to_test)} passed, {skipped} skipped")
self.assertEqual(skipped, 0, f"{name}: {skipped} tests skipped, expected 0")
# Compare disasm->reassemble with original encoding (filter reserved bit cases where LLVM can't reproduce)
llvm_bytes = llvm_assemble([t[1] for t in to_test], mcpu, get_mattr(arch))
llvm_bytes = _compile_asm_batch([t[1] for t in to_test], arch, mcpu)
valid = [(enc, d, llvm) for (enc, d), llvm in zip(to_test, llvm_bytes) if llvm == enc]
print(f"{name}: {len(valid)}/{len(to_test)} matched LLVM encoding")
for enc, _, llvm in valid: self.assertEqual(llvm, enc)
@@ -1,6 +1,6 @@
#!/usr/bin/env python3
"""Test that invalid instructions raise exceptions through the mock GPU stack."""
import unittest, subprocess, os, sys, time
import unittest, subprocess, os, time
class TestMockGPUInvalidInstruction(unittest.TestCase):
def test_unsupported_instruction_raises(self):
@@ -43,7 +43,7 @@ dev.synchronize()
env["HCQDEV_WAIT_TIMEOUT_MS"] = "10000"
st = time.perf_counter()
result = subprocess.run([sys.executable, "-c", test_code], env=env, capture_output=True, text=True, timeout=60)
result = subprocess.run(["python", "-c", test_code], env=env, capture_output=True, text=True, timeout=60)
elapsed = time.perf_counter() - st
self.assertNotEqual(result.returncode, 0, "should have raised")
@@ -1,15 +1,11 @@
#!/usr/bin/env python3
"""Test PDF pseudocode extraction from generate.py."""
import unittest
from tinygrad.renderer.amd.generate import extract_pdf_text, extract_pcode, parse_xml, ARCHS, FIXES
from extra.assembly.amd.generate import extract_pdf_text, extract_pcode, parse_xml, ARCHS, FIXES
EXPECTED_PAGES = {"rdna3": 655, "rdna4": 711, "cdna": 610}
class TestPcodePDF(unittest.TestCase):
pages: dict
enums: dict
pcode: dict
@classmethod
def setUpClass(cls):
cls.pages = {arch: extract_pdf_text(cfg["pdf"]) for arch, cfg in ARCHS.items()}
@@ -37,8 +33,7 @@ class TestPcodePDF(unittest.TestCase):
'tmp = MEM[ADDR].u64;\nsrc = DATA.u64;\nMEM[ADDR].u64 = src >= tmp ? src : tmp;\nRETURN_DATA.u64 = tmp')
# GLOBAL_STORE_B128: should have 4 MEM stores (not truncated)
self.assertEqual(pcode[('GLOBAL_STORE_B128', 29)],
'MEM[ADDR].b32 = VDATA[31 : 0];\nMEM[ADDR + 4U].b32 = VDATA[63 : 32];\n'
'MEM[ADDR + 8U].b32 = VDATA[95 : 64];\nMEM[ADDR + 12U].b32 = VDATA[127 : 96]')
'MEM[ADDR].b32 = VDATA[31 : 0];\nMEM[ADDR + 4U].b32 = VDATA[63 : 32];\nMEM[ADDR + 8U].b32 = VDATA[95 : 64];\nMEM[ADDR + 12U].b32 = VDATA[127 : 96]')
# S_CMOVK_I32: should have full if/endif block
self.assertEqual(pcode[('S_CMOVK_I32', 2)],
"if SCC then\nD0.i32 = 32'I(signext(SIMM16.i16))\nendif")
+95
View File
@@ -0,0 +1,95 @@
#!/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()
+98
View File
@@ -0,0 +1,98 @@
import unittest, ctypes
from extra.assembly.amd.autogen.rdna4 import ins as ir4
from extra.assembly.amd.dsl import v, s
from extra.assembly.amd.emu import WaveState, decode_program
from tinygrad.device import Buffer, BufferSpec
from tinygrad.dtype import dtypes
class TestRDNA4Emu(unittest.TestCase):
def _run(self, insts: list, sgprs: dict[int, int] = None, vgprs: dict[tuple[int, int], int] = None) -> WaveState:
"""Run instructions and return final WaveState."""
# Add S_ENDPGM if not present
if not any(isinstance(i, ir4.SOPP) and i.op == ir4.SOPPOp.S_ENDPGM for i in insts):
insts = list(insts) + [ir4.SOPP(ir4.SOPPOp.S_ENDPGM, simm=0)]
# Assemble and decode
code = b''.join(i.to_bytes() for i in insts)
code_buf = (ctypes.c_uint8 * len(code)).from_buffer_copy(code)
code_addr = ctypes.addressof(code_buf)
program_raw = decode_program(code, "rdna4")
program = {code_addr + offset: val for offset, val in program_raw.items()}
# Setup wave state
st = WaveState(n_lanes=1)
st.pc = code_addr
if sgprs:
for idx, val in sgprs.items(): st._write_sgpr(idx, val)
if vgprs:
for (reg, lane), val in vgprs.items(): st._write_vgpr(reg, lane, val)
# Setup vmem buffer with external_ptr=0 (maps to address 0, allows any pointer access)
vmem_buf = Buffer('CPU', 1 << 40, dtypes.uint32, options=BufferSpec(external_ptr=0)).ensure_allocated()
# Execute
c_bufs = [ctypes.c_uint64(st.sgpr_buf._buf.va_addr), ctypes.c_uint64(st.vgpr_buf._buf.va_addr),
ctypes.c_uint64(vmem_buf._buf.va_addr), ctypes.c_uint64(0), ctypes.c_uint64(0)]
for _ in range(100):
if (pc := st.pc) == 0xFFFFFFFFFFFFFFFF or pc not in program: break
_, fxn, globals_list, _ = program[pc]
fxn(*[c_bufs[g] for g in globals_list])
return st
def test_vopd_dual_mov(self):
"""Test VOPD with two V_DUAL_MOV_B32 operations: v[1]=s[1], v[2]=s[2]."""
insts = [ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[1], vdsty=v[2], srcx0=s[1], srcy0=s[2], vsrcx1=v[0], vsrcy1=v[0])]
st = self._run(insts, sgprs={1: 0x40e00000, 2: 0x41100000}) # 7.0f, 9.0f
self.assertEqual(st._read_vgpr(1, 0), 0x40e00000) # v[1] = 7.0
self.assertEqual(st._read_vgpr(2, 0), 0x41100000) # v[2] = 9.0
def test_vopd_dual_mov_after_other_vopd(self):
"""Test VOPD reuse: first VOPD(v[3]=0, v[0]=?), then VOPD(v[1]=s[1], v[2]=s[2])."""
# This matches the BEAM kernel sequence that fails
insts = [
ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[3], vdsty=v[0], srcx0=0, srcy0=s[0], vsrcx1=v[0], vsrcy1=v[0]), # v[3]=0, v[0]=s[0]
ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[1], vdsty=v[2], srcx0=s[1], srcy0=s[2], vsrcx1=v[0], vsrcy1=v[0]), # v[1]=s[1], v[2]=s[2]
]
st = self._run(insts, sgprs={0: 0x40a00000, 1: 0x40e00000, 2: 0x41100000}) # 5.0f, 7.0f, 9.0f
self.assertEqual(st._read_vgpr(1, 0), 0x40e00000) # v[1] = 7.0
self.assertEqual(st._read_vgpr(2, 0), 0x41100000) # v[2] = 9.0
def test_vopd_with_s_add_f32_sequence(self):
"""Test full BEAM kernel sequence: s_add_f32 then VOPD."""
# This is the exact sequence from the failing BEAM kernel
insts = [
ir4.SOP2(ir4.SOP2Op.S_ADD_F32, sdst=s[0], ssrc0=s[0], ssrc1=s[8]), # s[0] = s[0] + s[8]
ir4.SOP2(ir4.SOP2Op.S_ADD_F32, sdst=s[1], ssrc0=s[1], ssrc1=s[9]), # s[1] = s[1] + s[9]
ir4.SOP2(ir4.SOP2Op.S_ADD_F32, sdst=s[2], ssrc0=s[2], ssrc1=s[10]), # s[2] = s[2] + s[10]
ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[3], vdsty=v[0], srcx0=0, srcy0=s[0], vsrcx1=v[0], vsrcy1=v[0]),
ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[1], vdsty=v[2], srcx0=s[1], srcy0=s[2], vsrcx1=v[0], vsrcy1=v[0]),
]
# Input: s[0:2] = [1,2,3], s[8:10] = [4,5,6]
# After s_add_f32: s[0:2] = [5,7,9]
st = self._run(insts, sgprs={0: 0x3f800000, 1: 0x40000000, 2: 0x40400000, # 1.0, 2.0, 3.0
8: 0x40800000, 9: 0x40a00000, 10: 0x40c00000}) # 4.0, 5.0, 6.0
self.assertEqual(st._read_vgpr(1, 0), 0x40e00000) # v[1] = 7.0
self.assertEqual(st._read_vgpr(2, 0), 0x41100000) # v[2] = 9.0
def test_s_mov_b32_then_vopd(self):
"""Test s_mov_b32 followed by VOPD - simulates BEAM kernel sequence."""
# Use s_mov_b32 with SGPR source (copy from pre-initialized SGPRs)
# s[10:12] will have values set by test harness, copy to s[0:2], then VOPD to VGPRs
insts = [
ir4.SOP1(ir4.SOP1Op.S_MOV_B32, sdst=s[0], ssrc0=s[10]), # s[0] = s[10]
ir4.SOP1(ir4.SOP1Op.S_MOV_B32, sdst=s[1], ssrc0=s[11]), # s[1] = s[11]
ir4.SOP1(ir4.SOP1Op.S_MOV_B32, sdst=s[2], ssrc0=s[12]), # s[2] = s[12]
ir4.VOPD(ir4.VOPDOp.V_DUAL_MOV_B32, ir4.VOPDOp.V_DUAL_MOV_B32,
vdstx=v[1], vdsty=v[2], srcx0=s[1], srcy0=s[2], vsrcx1=v[0], vsrcy1=v[0]),
]
st = self._run(insts, sgprs={10: 0x40a00000, 11: 0x40e00000, 12: 0x41100000}) # 5.0, 7.0, 9.0
self.assertEqual(st._read_vgpr(1, 0), 0x40e00000) # v[1] = 7.0
self.assertEqual(st._read_vgpr(2, 0), 0x41100000) # v[2] = 9.0
if __name__ == '__main__':
unittest.main()
@@ -1,10 +1,9 @@
#!/usr/bin/env python3
"""Roundtrip tests: generate tinygrad kernels, decode instructions, re-encode, verify match."""
import unittest, io, sys, re
from tinygrad import Device
from tinygrad.renderer.amd import detect_format
from test.amd.helpers import llvm_assemble, llvm_disasm, get_target, get_mattr
from test.amd.disasm import disasm
import unittest, io, sys, re, subprocess, os
from extra.assembly.amd.dsl import Inst
from extra.assembly.amd import decode_inst, detect_format
from extra.assembly.amd.test.helpers import get_llvm_mc, get_llvm_objdump, get_target, get_mattr
def disassemble_lib(lib: bytes, compiler) -> list[tuple[str, bytes]]:
"""Disassemble ELF binary and return list of (instruction_text, machine_code_bytes)."""
@@ -31,20 +30,46 @@ def disassemble_lib(lib: bytes, compiler) -> list[tuple[str, bytes]]:
def compile_asm(instr: str, arch: str = 'rdna3') -> bytes:
"""Compile a single instruction using LLVM."""
return llvm_assemble([instr], get_target(arch), get_mattr(arch))[0]
return compile_asm_batch([instr], arch)[0]
def compile_asm_batch(instrs: list[str], arch: str = 'rdna3') -> list[bytes]:
"""Compile multiple instructions with a single LLVM emission."""
return llvm_assemble(instrs, get_target(arch), get_mattr(arch))
"""Compile multiple instructions with a single llvm-mc call."""
if not instrs: return []
result = subprocess.run([get_llvm_mc(), '-triple=amdgcn', f'-mcpu={get_target(arch)}', f'-mattr={get_mattr(arch)}', '-show-encoding'],
input=".text\n" + "\n".join(instrs) + "\n", capture_output=True, text=True)
if result.returncode != 0: raise RuntimeError(f"llvm-mc batch failed: {result.stderr.strip()}")
encodings = []
for line in result.stdout.split('\n'):
if 'encoding:' in line:
enc = line.split('encoding:')[1].strip()
if enc.startswith('[') and enc.endswith(']'):
encodings.append(bytes.fromhex(enc[1:-1].replace('0x', '').replace(',', '').replace(' ', '')))
if len(encodings) != len(instrs): raise RuntimeError(f"expected {len(instrs)} encodings, got {len(encodings)}")
return encodings
def compile_and_disasm_batch(instrs: list[str], arch: str = 'rdna3') -> list[str]:
"""Compile instructions with LLVM and get LLVM's disassembly."""
import tempfile
if not instrs: return []
mcpu, mattr = get_target(arch), get_mattr(arch)
code = b''.join(llvm_assemble(instrs, mcpu, mattr))
return llvm_disasm(code, mcpu, mattr)[:len(instrs)]
src = ".text\n.globl test\n.p2align 8\n.type test,@function\ntest:\n" + "\n".join(f" {instr}" for instr in instrs) + "\n"
with tempfile.NamedTemporaryFile(suffix='.o', delete=False) as f:
obj_path = f.name
try:
result = subprocess.run([get_llvm_mc(), '-triple=amdgcn', f'-mcpu={mcpu}', f'-mattr={mattr}', '-filetype=obj', '-o', obj_path],
input=src, capture_output=True, text=True)
if result.returncode != 0: raise RuntimeError(f"llvm-mc failed: {result.stderr.strip()}")
result = subprocess.run([get_llvm_objdump(), '-d', f'--mcpu={mcpu}', obj_path], capture_output=True, text=True)
if result.returncode != 0: raise RuntimeError(f"llvm-objdump failed: {result.stderr.strip()}")
results: list[str] = []
for line in result.stdout.splitlines():
if '//' not in line: continue
instr = line.split('//')[0].strip()
if instr: results.append(instr)
return results[:len(instrs)]
finally:
os.unlink(obj_path)
@unittest.skipUnless(Device.DEFAULT == "AMD", "requires AMD device")
class TestTinygradKernelRoundtrip(unittest.TestCase):
"""Test roundtrip on real tinygrad-generated kernels using get_kernels_from_tinygrad pattern."""
arch = 'rdna3'
@@ -57,7 +82,7 @@ class TestTinygradKernelRoundtrip(unittest.TestCase):
"""
arch = self.arch
from test.amd.test_compare_emulators import get_kernels_from_tinygrad
from extra.assembly.amd.test.test_compare_emulators import get_kernels_from_tinygrad
from tinygrad.runtime.support.elf import elf_loader
from tinygrad.runtime.support.compiler_amd import HIPCompiler, AMDLLVMCompiler
from tinygrad.helpers import AMD_LLVM
@@ -74,6 +99,11 @@ class TestTinygradKernelRoundtrip(unittest.TestCase):
while offset < len(code):
remaining = code[offset:]
fmt = detect_format(remaining, arch)
if fmt is None:
decoded_instrs.append((ki, offset, None, None, None, False, "no format"))
offset += 4
continue
base_size = fmt._size()
if len(remaining) < base_size:
break
@@ -83,7 +113,7 @@ class TestTinygradKernelRoundtrip(unittest.TestCase):
size = decoded.size() # actual size including literal
orig_bytes = remaining[:size]
reencoded = decoded.to_bytes()
our_disasm = disasm(decoded)
our_disasm = decoded.disasm()
decode_ok = reencoded == orig_bytes
decode_err: str | None = None if decode_ok else f"orig={orig_bytes.hex()} reenc={reencoded.hex()}"
decoded_instrs.append((ki, offset, orig_bytes, decoded, our_disasm, decode_ok, decode_err))
@@ -147,20 +177,20 @@ class TestTinygradKernelRoundtrip(unittest.TestCase):
if our_disasm is None:
disasm_skipped += 1
elif idx in disasm_llvm_map:
llvm_disasm_str = disasm_llvm_map[idx]
if our_disasm == llvm_disasm_str:
llvm_disasm = disasm_llvm_map[idx]
if our_disasm == llvm_disasm:
disasm_passed += 1
else:
disasm_failed += 1
disasm_failures.append(f"K{ki}@{offset}: ours='{our_disasm}' llvm='{llvm_disasm_str}'")
disasm_failures.append(f"K{ki}@{offset}: ours='{our_disasm}' llvm='{llvm_disasm}'")
else:
disasm_skipped += 1
print(f"[{arch}] decode roundtrip: {decode_passed} passed, {decode_failed} failed, {decode_skipped} skipped")
print(f"[{arch}] asm via llvm: {asm_passed} passed, {asm_failed} failed, {asm_skipped} skipped")
print(f"[{arch}] disasm vs llvm: {disasm_passed} passed, {disasm_failed} failed, {disasm_skipped} skipped")
self.assertEqual(decode_failed, 0, "Decode failures:\n" + "\n".join(decode_failures[:20]))
self.assertEqual(asm_failed, 0, "Asm failures:\n" + "\n".join(asm_failures[:20]))
self.assertEqual(decode_failed, 0, f"Decode failures:\n" + "\n".join(decode_failures[:20]))
self.assertEqual(asm_failed, 0, f"Asm failures:\n" + "\n".join(asm_failures[:20]))
# Note: disasm string comparison is informational only - formatting differences between LLVM versions are expected
# Basic unary ops
@@ -5,23 +5,21 @@ from pathlib import Path
from tinygrad.helpers import DEBUG
from tinygrad.runtime.autogen import rocprof
from tinygrad.runtime.support.elf import elf_loader
from tinygrad.renderer.amd import decode_inst
from tinygrad.runtime.autogen.amd.rdna3.ins import SOPP
from tinygrad.runtime.autogen.amd.rdna3.enum import SOPPOp
from tinygrad.renderer.amd.sqtt import (decode, LAYOUT_HEADER, WAVESTART, WAVESTART_RDNA4, WAVEEND, INST, INST_RDNA4, VALUINST,
IMMEDIATE, IMMEDIATE_MASK, PACKET_TYPES_RDNA3, PACKET_TYPES_RDNA4,
InstOp, InstOpRDNA4, print_packets)
from test.amd.helpers import TARGET_TO_ARCH
from extra.assembly.amd import decode_inst
from extra.assembly.amd.autogen.rdna3.ins import SOPP
from extra.assembly.amd.autogen.rdna3.enum import SOPPOp
from extra.assembly.amd.sqtt import (decode, LAYOUT_HEADER, WAVESTART, WAVESTART_L4, WAVEEND, INST, INST_L4, VALUINST, IMMEDIATE, IMMEDIATE_MASK,
ALUEXEC, VMEMEXEC, PACKET_TYPES_L3, PACKET_TYPES_L4, InstOp, InstOpL4, print_packets)
from extra.assembly.amd.test.helpers import TARGET_TO_ARCH
import tinygrad
EXAMPLES_DIR = Path(tinygrad.__file__).parent.parent / "extra/sqtt/examples"
EXAMPLES_DIR = Path(__file__).parent.parent.parent.parent / "sqtt/examples"
# INST ops for non-traced SIMDs (excluded from instruction count)
OTHER_SIMD_OPS = {InstOp.OTHER_LDS_LOAD, InstOp.OTHER_LDS_STORE, InstOp.OTHER_LDS_STORE_64, InstOp.OTHER_LDS_STORE_128,
InstOp.OTHER_FLAT_LOAD, InstOp.OTHER_FLAT_STORE, InstOp.OTHER_FLAT_STORE_64, InstOp.OTHER_FLAT_STORE_96,
InstOp.OTHER_FLAT_STORE_128, InstOp.OTHER_GLOBAL_LOAD, InstOp.OTHER_GLOBAL_LOAD_VADDR,
InstOp.OTHER_GLOBAL_STORE_64, InstOp.OTHER_GLOBAL_STORE_96, InstOp.OTHER_GLOBAL_STORE_128,
InstOp.OTHER_GLOBAL_STORE_VADDR_128}
OTHER_SIMD_OPS_RDNA4 = {InstOpRDNA4.OTHER_VMEM, InstOpRDNA4.OTHER_VMEM_5}
OTHER_SIMD_OPS_L4 = {InstOpL4.OTHER_VMEM, InstOpL4.UNK_60}
# ═══════════════════════════════════════════════════════════════════════════════
# ROCPROF DECODER
@@ -34,18 +32,18 @@ def run_rocprof_decoder(blobs: list[bytes], lib: bytes, base: int, target: str):
assert text is not None, "no .text section found"
text_off, text_size = text.header.sh_addr, text.header.sh_size
blob_iter, current_blob = iter(blobs), [None] # type: ignore[var-annotated]
blob_iter, current_blob = iter(blobs), [None]
occupancy_records: list[tuple[int, int, int, int, bool]] = [] # (wave_id, simd, cu, time, is_start)
wave_insts: list[list[tuple[int, int]]] = [] # per-wave list of (time, stall)
@rocprof.rocprof_trace_decoder_se_data_callback_t
def copy_cb(buf, buf_size, _): # type: ignore[no-untyped-def]
def copy_cb(buf, buf_size, _):
blob = next(blob_iter, None)
if blob is None: return 0
current_blob[0] = (ctypes.c_ubyte * len(blob)).from_buffer_copy(blob) # type: ignore[call-overload]
buf[0] = ctypes.cast(current_blob[0], ctypes.POINTER(ctypes.c_ubyte)) # type: ignore[arg-type]
buf_size[0] = len(current_blob[0]) # type: ignore[arg-type]
return len(current_blob[0]) # type: ignore[arg-type]
current_blob[0] = (ctypes.c_ubyte * len(blob)).from_buffer_copy(blob)
buf[0] = ctypes.cast(current_blob[0], ctypes.POINTER(ctypes.c_ubyte))
buf_size[0] = len(current_blob[0])
return len(current_blob[0])
@rocprof.rocprof_trace_decoder_trace_callback_t
def trace_cb(record_type, events_ptr, n, _):
@@ -89,14 +87,13 @@ def run_rocprof_decoder(blobs: list[bytes], lib: bytes, base: int, target: str):
try: rocprof.rocprof_trace_decoder_parse_data(copy_cb, trace_cb, isa_cb, None)
except Exception as e: exc = e
(t:=threading.Thread(target=worker, daemon=True)).start()
t.join(timeout=5)
t.join(timeout=1)
if exc is not None: raise exc
if t.is_alive(): raise RuntimeError("rocprof decoder timeout")
return occupancy_records, wave_insts
class SQTTExamplesTestBase(unittest.TestCase):
target: str
examples: dict
@classmethod
def setUpClass(cls):
@@ -118,19 +115,17 @@ class SQTTExamplesTestBase(unittest.TestCase):
for i, event in enumerate(events):
with self.subTest(example=name, event=i):
packets = list(decode(event.blob))
if DEBUG >= 2:
print(f"\n=== {name} event {i} ===")
print_packets(packets)
if DEBUG >= 2: print(f"\n=== {name} event {i} ==="); print_packets(packets)
self.assertGreater(len(packets), 0, f"no packets decoded from {name} event {i}")
self.assertIsInstance(packets[0], LAYOUT_HEADER, f"first packet should be LAYOUT_HEADER in {name}")
def test_packet_types_valid(self):
all_classes = set(PACKET_TYPES_RDNA3.values()) | set(PACKET_TYPES_RDNA4.values())
all_classes = set(PACKET_TYPES_L3.values()) | set(PACKET_TYPES_L4.values())
for name, (events, *_) in self.examples.items():
for i, event in enumerate(events):
with self.subTest(example=name, event=i):
for pkt in decode(event.blob):
# Use isinstance to handle layout-specific subclasses (e.g., WAVESTART_RDNA4)
# Use isinstance to handle layout-specific subclasses (e.g., WAVESTART_L4)
self.assertTrue(any(isinstance(pkt, cls) for cls in all_classes), f"unknown packet type {type(pkt)} in {name}")
def test_wave_lifecycle(self):
@@ -138,7 +133,7 @@ class SQTTExamplesTestBase(unittest.TestCase):
if "empty" in name: continue
with self.subTest(example=name):
all_packets = [p for e in events for p in decode(e.blob)]
self.assertGreater(len([p for p in all_packets if isinstance(p, (WAVESTART, WAVESTART_RDNA4))]), 0, f"no WAVESTART in {name}")
self.assertGreater(len([p for p in all_packets if isinstance(p, (WAVESTART, WAVESTART_L4))]), 0, f"no WAVESTART in {name}")
self.assertGreater(len([p for p in all_packets if isinstance(p, WAVEEND)]), 0, f"no WAVEEND in {name}")
def test_time_monotonic(self):
@@ -153,9 +148,7 @@ class SQTTExamplesTestBase(unittest.TestCase):
if "gemm" not in name: continue
with self.subTest(example=name):
all_packets = [p for e in events for p in decode(e.blob)]
inst_names = [p.op.name for p in all_packets if isinstance(p, (INST, INST_RDNA4))]
self.assertGreater(len(inst_names), 0, f"no INST packets in {name}")
self.assertGreater(len([n for n in inst_names if n.startswith("JUMP")]), 0, f"no JUMP packets in {name}")
self.assertGreater(len([p for p in all_packets if isinstance(p, (INST, INST_L4))]), 0, f"no INST packets in {name}")
expected: dict[str, list[int]] = {} # override in subclasses
def test_packet_counts(self):
@@ -183,7 +176,7 @@ class SQTTExamplesTestBase(unittest.TestCase):
for event in events:
wave_starts: dict[tuple[int, int, int], int] = {}
for p in decode(event.blob):
if isinstance(p, (WAVESTART, WAVESTART_RDNA4)): wave_starts[(p.wave, p.simd, p.cu)] = p._time
if isinstance(p, (WAVESTART, WAVESTART_L4)): wave_starts[(p.wave, p.simd, p.cu)] = p._time
elif isinstance(p, WAVEEND) and (key := (p.wave, p.simd, p.cu)) in wave_starts:
our_waves.append((wave_starts[key], p._time))
self.assertEqual(sorted(our_waves), sorted(roc_waves), f"wave times mismatch in {name}")
@@ -200,7 +193,7 @@ class SQTTExamplesTestBase(unittest.TestCase):
for event in events:
for p in decode(event.blob):
if isinstance(p, INST) and p.op not in OTHER_SIMD_OPS: our_insts.append(p._time)
elif isinstance(p, INST_RDNA4) and p.op not in OTHER_SIMD_OPS_RDNA4: our_insts.append(p._time)
elif isinstance(p, INST_L4) and p.op not in OTHER_SIMD_OPS_L4: our_insts.append(p._time)
elif isinstance(p, VALUINST): our_insts.append(p._time)
elif isinstance(p, IMMEDIATE): our_insts.append(p._time)
elif isinstance(p, IMMEDIATE_MASK):
@@ -210,19 +203,22 @@ class SQTTExamplesTestBase(unittest.TestCase):
class TestSQTTExamplesRDNA3(SQTTExamplesTestBase):
target = "gfx1100"
expected = {
"profile_empty_run_0": [1974, 1961, 2014, 2065, 2092, 1998],
"profile_empty_run_1": [1979, 1972, 2019, 2070, 2097, 2003],
"profile_gemm_run_0": [2038, 11076, 2324, 2129, 2156, 2062],
"profile_gemm_run_1": [2038, 11037, 2318, 2129, 2156, 2062],
"profile_ops_run_0": [2038, 5070, 2078, 2129, 2156, 2062],
"profile_ops_run_1": [2038, 5007, 2078, 2129, 2156, 2062],
"profile_plus_run_0": [1979, 1979, 2030, 2070, 2097, 2003],
"profile_plus_run_1": [1979, 2043, 2030, 2070, 2097, 2003],
"profile_empty_run_0": [1844, 1885, 1905, 1956, 1983, 1889],
"profile_empty_run_1": [1780, 1885, 1905, 1956, 1983, 1889],
"profile_gemm_run_0": [2656, 2025, 2045, 2096, 2123, 2029, 3183, 2019, 2039, 2090, 2117, 2023, 19119, 2013, 2033, 2084, 2111, 2017],
"profile_gemm_run_1": [2662, 2025, 2045, 2096, 2123, 2029, 3179, 2019, 2039, 2090, 2117, 2023, 19113, 2071, 2091, 2142, 2169, 2075],
"profile_plus_run_0": [1886, 2013, 2033, 2084, 2111, 2017],
"profile_plus_run_1": [1988, 2071, 2091, 2142, 2169, 2075],
}
class TestSQTTExamplesRDNA4(SQTTExamplesTestBase): target = "gfx1200"
@unittest.skip("TODO: fix CDNA")
class TestSQTTExamplesCDNA(SQTTExamplesTestBase): target = "gfx950"
# CDNA/MI300 (gfx950) uses a completely different 16-bit header packet format, not the nibble-based format.
# See decode_tt_header_stream in ghidra/librocprof-trace-decoder.c - it reads 16-bit headers and uses
# pkt_fmt = header & 0xf to look up packet_class (0x10=2bytes, 0x20=4bytes, 0x30=6bytes, 0x40=8bytes).
# This is NOT implemented yet - the nibble decoder produces garbage for CDNA data.
@unittest.skip("CDNA/MI300 uses 16-bit header format, not nibble-based - decoder not implemented")
class TestSQTTExamplesCDNA(SQTTExamplesTestBase):
target = "gfx950"
if __name__ == "__main__":
unittest.main()
+170
View File
@@ -0,0 +1,170 @@
"""Tests comparing sqtt.py PACKET_TYPES_L3/L4 against AMD's rocprof-trace-decoder binary."""
import unittest, struct, ctypes, pickle
from pathlib import Path
ROCPROF_LIB = Path("/usr/lib/librocprof-trace-decoder.so")
EXAMPLES_DIR = Path(__file__).parent.parent.parent.parent / "sqtt/examples"
def _find_segment(perms: str):
"""Find a segment of the loaded library with given permissions (e.g. 'rw-p', 'r--p')."""
with open('/proc/self/maps', 'r') as f:
for line in f:
if 'librocprof-trace-decoder.so' in line and f' {perms} ' in line:
parts = line.split()
return int(parts[0].split('-')[0], 16), int(parts[2], 16)
return None, None
def _read_array(file_offset: int, count: int):
"""Read an array of uint8 at file_offset from the loaded library."""
base, seg_offset = _find_segment('rw-p')
if base is None: return None
return list((ctypes.c_uint8 * count).from_address(base + (file_offset - seg_offset)))
def _load_lib():
if not ROCPROF_LIB.exists(): return False
ctypes.CDLL(str(ROCPROF_LIB))
return True
# ═══════════════════════════════════════════════════════════════════════════════
# RDNA EXTRACTION (nibble-based format)
# ═══════════════════════════════════════════════════════════════════════════════
def extract_bit_tables():
"""Extract bit budget tables. Returns (layout2, layout3, layout4) or None."""
if not _load_lib(): return None
return _read_array(0x2d220, 32), _read_array(0x2d280, 32), _read_array(0x2d2c0, 32)
def extract_delta_fields():
"""Extract delta bitfield tables. Returns (layout2, layout3, layout4) dicts mapping type_id -> (lo, hi)."""
if not _load_lib(): return None
ro_base, ro_offset = _find_segment('r--p')
if ro_base is None: return None
def read_table(file_offset, num_entries):
addr = ro_base + (file_offset - ro_offset)
data = bytes((ctypes.c_uint8 * (num_entries * 12)).from_address(addr))
return {type_id: (lo, hi) for j in range(0, len(data), 12)
for type_id, lo, hi in [struct.unpack('<III', data[j:j+12])] if type_id < 32}
return read_table(0x26800, 24), read_table(0x26dc0, 25), read_table(0x27300, 27)
def extract_packet_encodings():
"""Extract packet encodings. Returns (L2, L3, L4) dicts mapping type_id -> (mask, value)."""
if not _load_lib(): return None
rw_base, rw_offset = _find_segment('rw-p')
if rw_base is None: return None
# Read base encodings from registration vector at 0x2d340
vec_start = ctypes.c_void_p.from_address(rw_base + (0x2d340 - rw_offset)).value
vec_end = ctypes.c_void_p.from_address(rw_base + (0x2d348 - rw_offset)).value
base = {}
if vec_start and vec_end:
for i in range((vec_end - vec_start) // 32):
addr = vec_start + i * 32
type_id = ctypes.c_uint8.from_address(addr).value
pat_start = ctypes.c_void_p.from_address(addr + 8).value
pat_end = ctypes.c_void_p.from_address(addr + 16).value
if pat_start and pat_end and 0 < (n := pat_end - pat_start) <= 8:
pat = list((ctypes.c_uint8 * n).from_address(pat_start))
base[type_id] = (sum(1 << j for j in range(n)), sum(b << j for j, b in enumerate(pat)))
return {**base, 17: (0x7f, 0x51), 25: (0x7f, 0x31)}, base, {**base} # L2 has overrides
# ═══════════════════════════════════════════════════════════════════════════════
# CDNA EXTRACTION (16-bit header format)
# ═══════════════════════════════════════════════════════════════════════════════
def extract_cdna_packet_sizes():
"""Extract CDNA pkt_fmt -> size mapping by running rocprof decoder to populate its hash table."""
from extra.assembly.amd.test.test_sqtt_examples import run_rocprof_decoder
if not (pkl_path := next((EXAMPLES_DIR / "gfx950").glob("*.pkl"), None)): return None
with open(pkl_path, "rb") as f: data = pickle.load(f)
sqtt_events = [e for e in data if type(e).__name__ == "ProfileSQTTEvent"]
prg = next((e for e in data if type(e).__name__ == "ProfileProgramEvent"), None)
if not sqtt_events or not prg: return None
# Run decoder to trigger hash table initialization
run_rocprof_decoder([e.blob for e in sqtt_events], prg.lib, prg.base, "gfx950")
# Extract hash table: head at 0x2d4f0, nodes are 16 bytes (next[8], key[4], value[4])
rw_base, rw_offset = _find_segment('rw-p')
if not (head := ctypes.c_void_p.from_address(rw_base + (0x2d4f0 - rw_offset)).value if rw_base else None): return None
pkt_sizes, node, seen = {}, head, set()
while node and node not in seen and len(pkt_sizes) < 20:
seen.add(node)
key, val = ctypes.c_uint32.from_address(node + 8).value, ctypes.c_uint32.from_address(node + 12).value
if key < 16 and val in (0x10, 0x20, 0x30, 0x40): pkt_sizes[key] = {0x10: 2, 0x20: 4, 0x30: 6, 0x40: 8}[val]
node = ctypes.c_void_p.from_address(node).value
return pkt_sizes if len(pkt_sizes) == 16 else None
# ═══════════════════════════════════════════════════════════════════════════════
# TESTS
# ═══════════════════════════════════════════════════════════════════════════════
class TestSQTTMatchesBinary(unittest.TestCase):
def test_bit_counts_match_layout3(self): self._test_bit_counts(3)
def test_bit_counts_match_layout4(self): self._test_bit_counts(4)
def test_encodings_match_layout3(self): self._test_encodings(3)
def test_encodings_match_layout4(self): self._test_encodings(4)
def test_delta_fields_match_layout3(self): self._test_delta_fields(3)
def test_delta_fields_match_layout4(self): self._test_delta_fields(4)
def test_cdna_packet_sizes(self):
"""Extract and verify CDNA pkt_fmt -> size mapping from rocprof's hash table."""
if not (EXAMPLES_DIR / "gfx950").exists(): self.skipTest("no CDNA examples")
pkt_sizes = extract_cdna_packet_sizes()
self.assertIsNotNone(pkt_sizes, "failed to extract CDNA packet sizes")
from extra.assembly.amd.sqtt_cdna import CDNA_PKT_SIZES
for pkt_fmt, size in CDNA_PKT_SIZES.items():
with self.subTest(pkt_fmt=pkt_fmt): self.assertEqual(pkt_sizes.get(pkt_fmt), size)
def _test_bit_counts(self, layout: int):
if not (tables := extract_bit_tables()): self.skipTest("rocprof-trace-decoder not installed")
from extra.assembly.amd.sqtt import PACKET_TYPES_L3, PACKET_TYPES_L4
for type_id, pkt_cls in {3: PACKET_TYPES_L3, 4: PACKET_TYPES_L4}[layout].items():
with self.subTest(packet=pkt_cls.__name__):
self.assertEqual(pkt_cls._size_nibbles * 4, tables[layout - 2][type_id])
def _test_encodings(self, layout: int):
if not (encodings := extract_packet_encodings()): self.skipTest("rocprof-trace-decoder not installed")
from extra.assembly.amd.sqtt import PACKET_TYPES_L3, PACKET_TYPES_L4
for type_id, pkt_cls in {3: PACKET_TYPES_L3, 4: PACKET_TYPES_L4}[layout].items():
with self.subTest(packet=pkt_cls.__name__):
self.assertEqual((pkt_cls.encoding.mask, pkt_cls.encoding.default), encodings[layout - 2][type_id])
def _test_delta_fields(self, layout: int):
if not (deltas := extract_delta_fields()): self.skipTest("rocprof-trace-decoder not installed")
from extra.assembly.amd.sqtt import PACKET_TYPES_L3, PACKET_TYPES_L4
for type_id, pkt_cls in {3: PACKET_TYPES_L3, 4: PACKET_TYPES_L4}[layout].items():
if type_id not in deltas[layout - 2]: continue
delta = getattr(pkt_cls, 'delta', None)
actual = (0, 0) if delta is None else (delta.lo, delta.hi + 1)
with self.subTest(packet=pkt_cls.__name__): self.assertEqual(actual, deltas[layout - 2][type_id])
if __name__ == "__main__":
tables = extract_bit_tables()
encodings = extract_packet_encodings()
deltas = extract_delta_fields()
TYPE_NAMES = {1: 'VALUINST', 2: 'VMEMEXEC', 3: 'ALUEXEC', 4: 'IMMEDIATE', 5: 'IMMEDIATE_MASK', 6: 'WAVERDY',
7: 'TS_DELTA_S8_W3', 8: 'WAVEEND', 9: 'WAVESTART', 10: 'TS_DELTA_S5_W2', 11: 'WAVEALLOC', 12: 'TS_DELTA_S5_W3',
13: 'PERF', 14: 'UTILCTR', 15: 'TS_DELTA_SHORT', 16: 'NOP', 17: 'TS_WAVE_STATE', 18: 'EVENT', 19: 'EVENT_BIG',
20: 'REG', 21: 'SNAPSHOT', 22: 'TS_DELTA_OR_MARK', 23: 'LAYOUT_HEADER', 24: 'INST', 25: 'UNK_25'}
print("L2:", tables[0], "\nL3:", tables[1], "\nL4:", tables[2])
if encodings and tables:
print(f"\n{'TypeID':>6} {'Name':>18} {'L2 enc':>12} {'L3 enc':>12} {'L4 enc':>12} {'L2':>4} {'L3':>4} {'L4':>4} {'L2 delta':>12} {'L3 delta':>12} {'L4 delta':>12}")
print("-" * 140)
for type_id in sorted(set(encodings[0]) | set(encodings[1]) | set(encodings[2])):
name = TYPE_NAMES.get(type_id, f'UNK_{type_id}')
bits = [tables[i][type_id] if type_id < len(tables[i]) else 0 for i in range(3)]
enc_strs = [f"0x{encodings[i][type_id][0]:02x}/0x{encodings[i][type_id][1]:02x}" if type_id in encodings[i] else "-" for i in range(3)]
delta_strs = [f"[{d[1]-1}:{d[0]}]" if (d := deltas[i].get(type_id, (0, 0)))[1] > d[0] else "-" for i in range(3)]
print(f"{type_id:6d} {name:>18} {enc_strs[0]:>12} {enc_strs[1]:>12} {enc_strs[2]:>12} {bits[0]:4d} {bits[1]:4d} {bits[2]:4d} {delta_strs[0]:>12} {delta_strs[1]:>12} {delta_strs[2]:>12}")
cdna = extract_cdna_packet_sizes()
if cdna: print(f"\nCDNA packet sizes: {cdna}")
unittest.main()
+1 -2
View File
@@ -34,8 +34,7 @@ class WallTimeEvent:
self.start = time.monotonic()
return self
def __exit__(self, *_):
self.time = time.monotonic() - self.start
_events[self.event]["wall"].append(self.time)
_events[self.event]["wall"].append(time.monotonic() - self.start)
return False
class KernelTimeEvent:
+101 -51
View File
@@ -1,5 +1,5 @@
# RDNA3 128x128 tiled GEMM kernel - DSL version
# Computes C = A @ B for NxN float32 matrices using 128x128 tiles
# Computes C = A @ B for 4096x4096 float32 matrices using 128x128 tiles
#
# Architecture: RDNA3 (gfx1100)
# Tile size: 128x128 (each workgroup computes one tile of C)
@@ -9,18 +9,19 @@
# 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 tinygrad.renderer.amd.dsl import s, v, VCC_LO, NULL
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from extra.assembly.amd.dsl import s, v, VCC_LO, NULL
from extra.assembly.amd.autogen.rdna3.ins import *
# =============================================================================
# Kernel constants
# =============================================================================
LDS_SIZE = 8320 # Local data share size in bytes
MATRIX_DIM = 4096 # Matrix dimension N (assumes square NxN matrices)
LDS_A_STRIDE = 0x210 # LDS stride for A tile (528 bytes)
LDS_B_STRIDE = 0x200 # LDS stride for B tile (512 bytes)
LDS_BASE_OFFSET = 0x1080 # Base LDS offset for tiles
@@ -50,18 +51,18 @@ 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_WORKGROUP_X = 2 # workgroup_id_x (system SGPR, follows user SGPRs)
S_WORKGROUP_Y = 3 # workgroup_id_y (system SGPR)
S_TILE_X = 2 # workgroup_x << 7
S_TILE_Y = 3 # workgroup_y << 7
S_DIM_N = 4 # matrix dimension N
S_LOOP_BOUND = 7 # K-8 (loop termination bound)
S_LOOP_CTR = 12 # loop counter (increments by 8)
S_PREFETCH_FLAG = 13 # prefetch condition flag / row stride in epilogue
S_TILE_X = 14 # workgroup_x << 7
S_TILE_Y = 15 # workgroup_y << 7
S_WORKGROUP_X = 14 # workgroup_id_x
S_WORKGROUP_Y = 15 # workgroup_id_y
# 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, B: N*4 bytes apart, A: N*64 bytes apart)
# Prefetch base pointers (8 pairs each, 16KB/256KB apart)
S_PREFETCH_B = 24 # s[24:39] - 8 B tile pointers
S_PREFETCH_A = 40 # s[40:55] - 8 A tile pointers
@@ -182,23 +183,54 @@ class Kernel:
waitcnt = (expcnt & 0x7) | ((lgkmcnt & 0x3f) << 4) | ((vmcnt & 0x3f) << 10)
self.emit(s_waitcnt(simm16=waitcnt))
def finalize(self):
"""Patch branch offsets and return the finalized instruction list."""
def to_asm(self):
# Patch branch offsets: simm16 = (target_pos - branch_end_pos) / 4
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
# TODO: replace this with direct ELF
body = ['\t' + inst.disasm() for inst in self.instructions]
# 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', 179),
('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: 179', ' .wavefront_size: 32', f'amdhsa.target: amdgcn-amd-amdhsa--{self.arch}',
'amdhsa.version:', ' - 1', ' - 2', '...', '\t.end_amdgpu_metadata'])
# =============================================================================
# Kernel builder
# =============================================================================
def build_kernel(N, arch='gfx1100'):
assert N % 128 == 0, f"N must be a multiple of 128 (tile size), got {N}"
assert N >= 256, f"N must be >= 256 (prefetch pipeline requires at least 2 K-blocks), got {N}"
def build_kernel(arch='gfx1100'):
k = Kernel(arch)
# ===========================================================================
@@ -206,7 +238,7 @@ def build_kernel(N, arch='gfx1100'):
# ===========================================================================
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_OUT_PTR[0]:S_OUT_PTR[1]], sbase=s[0:1], offset=0x10, soffset=NULL))
k.emit(s_mov_b32(s[S_DIM_N], N))
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))
@@ -221,20 +253,19 @@ def build_kernel(N, arch='gfx1100'):
# 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: each pointer 1 row of B apart (N*4 bytes)
k.emit(s_add_u32(s[S_PREFETCH_B+i*2], s[S_KERNARG_B[0]], i * N * 4))
for i in range(1, 8): # B: 16KB apart
k.emit(s_add_u32(s[S_PREFETCH_B+i*2], s[S_KERNARG_B[0]], i * 0x4000))
k.emit(s_addc_u32(s[S_PREFETCH_B+i*2+1], s[S_KERNARG_B[1]], 0))
k.emit(s_mov_b64(s[S_PREFETCH_A:S_PREFETCH_A+1], s[S_KERNARG_A[0]:S_KERNARG_A[1]])) # A[0]: no offset
for i in range(1, 8): # A: each pointer 16 rows of A apart (16*N*4 bytes)
k.emit(s_add_u32(s[S_PREFETCH_A+i*2], s[S_KERNARG_A[0]], i * N * 64))
for i in range(1, 8): # A: 256KB apart
k.emit(s_add_u32(s[S_PREFETCH_A+i*2], s[S_KERNARG_A[0]], i * 0x40000))
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*N + (lane_id/8)*N + lane_id%8) * 4
# 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[V_LANE_ID]))
k.emit(v_lshlrev_b32_e32(v[V_GLOBAL_B_ADDR], 2, v[V_GLOBAL_B_ADDR]))
k.emit(s_mul_i32(s[19], s[S_TILE_Y], N))
k.emit(v_mul_lo_u32(v[V_GLOBAL_A_ADDR], v[4], N)) # (lane_id/8)*N
k.emit(v_add_nc_u32_e32(v[V_GLOBAL_A_ADDR], v[V_LANE_ID_MOD8], v[V_GLOBAL_A_ADDR])) # + lane_id%8
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]))
@@ -305,13 +336,13 @@ def build_kernel(N, arch='gfx1100'):
if not NO_GLOBAL:
# Advance prefetch pointers (VGPR)
#k.emit(v_add_nc_u32_e32(v[V_GLOBAL_B_ADDR], N * 32, v[V_GLOBAL_B_ADDR]))
#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 (64-bit adds): B advances 8 rows (8*N*4 bytes), A advances 8 cols (8*4 bytes)
# 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], N * 32))
k.emit(s_add_u32(s[S_PREFETCH_B+i*2], s[S_PREFETCH_B+i*2], 0x20000))
k.emit(s_addc_u32(s[S_PREFETCH_B+i*2+1], s[S_PREFETCH_B+i*2+1], 0))
for i in range(8):
k.emit(s_add_u32(s[S_PREFETCH_A+i*2], s[S_PREFETCH_A+i*2], 0x20))
@@ -428,7 +459,7 @@ def build_kernel(N, arch='gfx1100'):
k.emit(s_sendmsg(simm16=3)) # DEALLOC_VGPRS
k.emit(s_endpgm())
return k.finalize()
return k.to_asm()
# =============================================================================
# Test harness
@@ -442,7 +473,16 @@ def test_matmul():
dev = Device[Device.DEFAULT]
print(f"Device arch: {dev.renderer.arch}")
insts = build_kernel(N, 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.renderer.arch)
binary = dev.compiler.compile(asm)
print(f"Compiled! Binary size: {len(binary)} bytes")
rng = np.random.default_rng(42)
a = Tensor(rng.random((N, N), dtype=np.float32) - 0.5)
@@ -457,10 +497,10 @@ 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)]
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]))))
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)))
c = Tensor.custom_kernel(a, b, c, fxn=asm_kernel)[2]
ei = c.schedule()[0].lower()
@@ -474,23 +514,33 @@ def test_matmul():
with Context(DEBUG=2): tc = (a @ b).realize()
with Context(DEBUG=0): err = (c - tc).square().mean().item()
print(f"mean squared error {err}")
if err != err or err > 1e-06:
c_np, tc_np = c.numpy(), tc.numpy()
for bi in range(N // 128):
for bj in range(N // 128):
blk_c = c_np[bi*128:(bi+1)*128, bj*128:(bj+1)*128]
blk_ref = tc_np[bi*128:(bi+1)*128, bj*128:(bj+1)*128]
blk_diff = blk_c - blk_ref
zero_rows = [i for i in range(128) if np.all(np.abs(blk_c[i,:]) < 1e-10)]
nz_rows = [i for i in range(128) if i not in zero_rows]
nz_mse = float(np.mean(blk_diff[nz_rows,:]**2)) if nz_rows else 0
print(f"Block ({bi},{bj}): zero_rows={zero_rows}, nz_rows_mse={nz_mse:.2e}")
# show first few non-zero row comparisons
if nz_rows and nz_mse > 1e-6:
for r in nz_rows[:3]:
print(f" row {r} asm[0:8]: {blk_c[r,:8]}")
print(f" row {r} ref[0:8]: {blk_ref[r,:8]}")
raise RuntimeError("matmul is wrong!")
if err != err or err > 1e-06: raise RuntimeError("matmul is wrong!")
def run_sqtt():
"""Run with SQTT profiling and write trace files."""
import subprocess, os
# Run test_matmul in a subprocess with SQTT enabled from the start (no verify)
env = {**os.environ, "AMD": "1", "SQTT": "1", "CNT": "1", "PROFILE": "1", "PYTHONPATH": ".", "VERIFY": "0"}
result = subprocess.run(
["python", "-c", "from extra.gemm.amd_asm_matmul import test_matmul; test_matmul()"],
capture_output=True, text=True, env=env, timeout=120
)
print(result.stdout)
# Run roc.py to extract trace data
result = subprocess.run(
["python", "extra/sqtt/roc.py", "--profile", "/tmp/profile.pkl.tiny", "--kernel", "kernel"],
capture_output=True, text=True, env={**os.environ, "DEBUG": "5"}, timeout=60
)
output = result.stdout + result.stderr
# Write full output to trace file
with open("/tmp/sqtt_trace.txt", "w") as f:
f.write(output)
print(f"Wrote {len(output)} bytes to /tmp/sqtt_trace.txt")
if __name__ == "__main__":
test_matmul()
if getenv("ASM", 0): print(build_kernel(Device[Device.DEFAULT].arch))
elif getenv("SQTT", 0): run_sqtt()
else: test_matmul()
+9631 -707
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@@ -1,57 +1,47 @@
import atexit, functools
from tinygrad.runtime.support.compiler_amd import HIPCompiler
from tinygrad import Tensor, Device, dtypes
from tinygrad.dtype import AddrSpace
from tinygrad.uop.ops import UOp, Ops, KernelInfo, AxisType
from tinygrad.renderer import Estimates
from tinygrad.helpers import getenv, all_same, DEBUG
from extra.gemm.asm.cdna.asm import build_kernel, TILE_M, TILE_N, TILE_K, NUM_WG
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) -> UOp:
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(NUM_WG, "gidx0")
insts = build_kernel(batch, M, N, K, A.dtype.base)
lds = UOp(Ops.DEFINE_LOCAL, dtypes.uint8.ptr(size=133_120, addrspace=AddrSpace.LOCAL), (), 'lds')
sink = UOp.sink(C.base, A.base, B.base, lds, lidx, gidx,
arg=KernelInfo(name=f"gemm_{batch}_{M}_{N}_{K}", estimates=Estimates(ops=2*batch*M*N*K, mem=(batch*M*K + K*N + batch*M*N)*2)))
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]))))
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)))
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
def _asm_gemm_report():
print(f'asm_gemm: {counters["used"]} used, {len(counters["todos"])} not used')
if DEBUG >= 2 and counters["todos"]:
from collections import Counter
for msg, cnt in Counter(counters["todos"]).most_common(): print(f' {cnt:3d}x {msg}')
atexit.register(_asm_gemm_report)
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 == 0 and b.uop.axis is None: M //= len(a.device)
elif a.ndim == 2 and a.uop.axis == 1 and b.uop.axis == 0: K //= len(a.device)
elif a.ndim == 2 and a.uop.axis is None and b.uop.axis == 1: N //= len(a.device)
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)
elif a.ndim == 3 and a.uop.axis is None and b.uop.axis == 1: N //= len(a.device)
elif a.ndim == 3 and a.uop.axis == 2 and b.uop.axis == 0: K //= 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 (M % TILE_M != 0 or N % TILE_N != 0 or K % TILE_K != 0) and arch == "gfx950":
return todo(f"GEMM shape ({M},{N},{K}) not a multiple of ({TILE_M},{TILE_N},{TILE_K})")
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
@@ -86,10 +76,6 @@ def custom_gemm_bw(gradient:UOp, kernel:UOp):
def asm_gemm(a:Tensor, b:Tensor) -> Tensor:
assert can_use_asm_gemm(a, b), f"{counters['todos'][-1]}"
counters["used"] += 1
unfold_batch = a.ndim == 3 and isinstance(a.device, tuple) and a.uop.axis == 2 and b.uop.axis == 0
if unfold_batch:
orig_batch = a.shape[0]
a = a.reshape(a.shape[0]*a.shape[1], a.shape[2])
squeeze = a.ndim == 2
if squeeze: a = a.unsqueeze(0)
@@ -97,26 +83,18 @@ def asm_gemm(a:Tensor, b:Tensor) -> Tensor:
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 (m_sharded:=is_multi and a.uop.axis == 1): M //= len(a.device)
n_sharded = is_multi and b.uop.axis == 1
if is_multi:
if n_sharded:
out = Tensor(Tensor.empty(batch, M, N//len(a.device), dtype=a.dtype, device=a.device).uop.multi(2), device=a.device)
elif m_sharded:
out = Tensor(Tensor.empty(batch, M, N, dtype=a.dtype, device=a.device).uop.multi(1), device=a.device)
else:
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)
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)
renderer = Device[a.device[0] if is_multi else a.device].renderer
dname, arch = renderer.device, getattr(renderer, "arch", "")
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):
out = Tensor.custom_kernel(out, a, b, fxn=functools.partial(custom_asm_gemm, dname=dname), grad_fxn=custom_gemm_bw)[0]
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)
out = out.squeeze(0) if squeeze else out
if unfold_batch: out = out.reshape(orig_batch, -1, out.shape[-1])
return out
return out.squeeze(0) if squeeze else out
+3 -7
View File
@@ -10,9 +10,9 @@ HEVC_ROUNDUP = getenv("DATA_ROUNDUP", 32)
@functools.cache
def _hevc_jitted_decoder(out_image_size:tuple[int, int], max_hist:int, inplace:bool):
def hevc_decode_frame(pos:Variable, hevc_tensor:Tensor, offset:Variable, sz:Variable, opaque:Tensor, i:Variable, *hist:Tensor, outbuf:Tensor|None=None):
x = hevc_tensor[offset:offset+sz*HEVC_ROUNDUP].decode_hevc_frame(pos, out_image_size, opaque[i], hist).realize()
x = hevc_tensor[offset:offset+sz*HEVC_ROUNDUP].decode_hevc_frame(pos, out_image_size, opaque[i], hist)
if outbuf is not None: outbuf.assign(x).realize()
return x
return x.realize()
return TinyJit(hevc_decode_frame)
def hevc_decode(hevc_tensor:Tensor, opaque:Tensor, frame_info:list, luma_h:int, luma_w:int,
@@ -74,14 +74,10 @@ if __name__ == "__main__":
Device.default.synchronize()
# decode all frames using the iterator
tm = Timing("decoding whole file: ", on_exit=(lambda et: f", {len(frame_info)} frames, {len(frame_info)/(et/1e9):.2f} fps"))
with tm:
with Timing("decoding whole file: ", on_exit=(lambda et: f", {len(frame_info)} frames, {len(frame_info)/(et/1e9):.2f} fps")):
images = list(hevc_decode(hevc_tensor, opaque_nv, frame_info, luma_h, luma_w, history=hist, preallocated_outputs=out_images))
Device.default.synchronize()
fps = len(frame_info)/(tm.et/1e9)
assert fps >= getenv("ASSERT_FPS", 0), f"HEVC decode too slow: {fps:.2f} fps"
# validation
if getenv("VALIDATE", 0):
import pickle
+27 -24
View File
@@ -1,27 +1,29 @@
import os
import os, pathlib
# TODO: there is a timing bug without this
os.environ["AMD_AQL"] = "1"
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
from tinygrad.device import Device
from tinygrad.runtime.support.compiler_amd import HIPCompiler
from extra.assembly.amd.dsl import Reg, Inst, s, v
NUM_WORKGROUPS = 96
WAVE_SIZE = 32
NUM_WAVES = 4
NUM_WAVES = 2
FLOPS_PER_MATMUL = 16*16*16*2
INTERNAL_LOOP = getenv("LOOP", 10_000)
INTERNAL_LOOP = 1_000_00
INSTRUCTIONS_PER_LOOP = 200
DIRECTIVE = ".amdhsa_wavefront_size32 1"
def repeat(insts:list[Inst], n:int, counter_sreg:Reg) -> list[Inst]:
assemblyTemplate = (pathlib.Path(__file__).parent / "template.s").read_text()
def repeat(insts:list[Inst], n:int, counter_sreg:Reg) -> bytes:
preamble = s_mov_b32(counter_sreg, n).to_bytes()
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()]
return preamble + insts_bytes + sub_inst.to_bytes() + cmp_inst.to_bytes() + branch_inst.to_bytes() + s_endpgm().to_bytes()
def launchBenchmark(instruction, vgprIndices, dense=True, accum=False, **kwargs):
if accum:
@@ -30,17 +32,16 @@ def launchBenchmark(instruction, vgprIndices, dense=True, accum=False, **kwargs)
inst = instruction(v[0:vgprIndices[0]], v[vgprIndices[1]:vgprIndices[2]], v[vgprIndices[1]:vgprIndices[2]], 1)
else:
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)])
vgprs:set = set()
for n,_ in inst._fields:
if isinstance(val:=getattr(inst, n), Reg) and val.offset >= v.offset: vgprs |= {val.offset+i for i in range(val.sz)}
inst_bytes = repeat([inst for _ in range(INSTRUCTIONS_PER_LOOP)], n=INTERNAL_LOOP, counter_sreg=s[1])
inst_hex = "\n".join(" .byte " + ",".join(f"0x{b:02x}" for b in inst_bytes[i:i+16]) for i in range(0, len(inst_bytes), 16)) + "\n"
src = assemblyTemplate.replace("INTERNAL_LOOP", str(INTERNAL_LOOP)).replace("INSTRUCTION", inst_hex).replace("VGPR_COUNT", str(len(vgprs)))
src = src.replace("DIRECTIVE", DIRECTIVE)
lib = COMPILER.compile(src)
fxn = DEV.runtime("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)])
FLOPs = FLOPS_PER_MATMUL * NUM_WAVES * NUM_WORKGROUPS * INTERNAL_LOOP * INSTRUCTIONS_PER_LOOP
print(f"{inst.op_name.lower():<29} : {FLOPs/elapsed/10**12:.2f} T(FL)OPS")
@@ -48,8 +49,9 @@ if __name__=="__main__":
DEV = Device[Device.DEFAULT]
arch = DEV.renderer.arch
COMPILER = HIPCompiler(arch)
if arch in {'gfx1100', 'gfx1103', 'gfx1151'}:
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from extra.assembly.amd.autogen.rdna3.ins import *
if arch == 'gfx1103': NUM_WORKGROUPS = 8
if arch == 'gfx1151': NUM_WORKGROUPS = 32
launchBenchmark(v_wmma_bf16_16x16x16_bf16, (7,8,15))
@@ -59,7 +61,7 @@ if __name__=="__main__":
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 *
from extra.assembly.amd.autogen.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
@@ -88,7 +90,8 @@ if __name__=="__main__":
FLOPS_PER_MATMUL = 16*16*64*2
launchBenchmark(v_swmmac_i32_16x16x64_iu4, (7,8,9,10,13,14), False)
elif arch == 'gfx950':
from tinygrad.runtime.autogen.amd.cdna.ins import *
from extra.assembly.amd.autogen.cdna.ins import *
DIRECTIVE = ".amdhsa_accum_offset 4"
NUM_WORKGROUPS = 256
WAVE_SIZE = 64
NUM_WAVES = 4
+33
View File
@@ -0,0 +1,33 @@
.text
.globl matmul
.p2align 8
.type matmul,@function
matmul:
INSTRUCTION
.rodata
.p2align 6
.amdhsa_kernel matmul
.amdhsa_next_free_vgpr VGPR_COUNT
.amdhsa_next_free_sgpr 3
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
+8 -14
View File
@@ -41,13 +41,9 @@ class Attention:
self.n_rep = self.n_heads // self.n_kv_heads
self.max_context = max_context
if getenv("WQKV"):
self.wqkv = linear(dim, self.n_heads * self.head_dim + self.n_kv_heads * self.head_dim * 2, bias=False)
else:
self.wq = linear(dim, self.n_heads * self.head_dim, bias=False)
self.wk = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
self.wv = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
self.wq = linear(dim, self.n_heads * self.head_dim, bias=False)
self.wk = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
self.wv = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
self.wo = linear(self.n_heads * self.head_dim, dim, bias=False)
self.q_norm = nn.RMSNorm(dim, qk_norm) if qk_norm is not None else None
@@ -55,11 +51,9 @@ class Attention:
def __call__(self, x:Tensor, start_pos:Union[Variable,int], freqs_cis:Tensor, mask:Optional[Tensor]=None) -> Tensor:
if getenv("WQKV"):
xqkv = self.wqkv(x)
xqkv = xqkv.reshape(xqkv.shape[0], xqkv.shape[1], self.n_kv_heads, self.n_rep + 2, self.head_dim)
xq = xqkv[:, :, :, :self.n_rep].reshape(xqkv.shape[0], xqkv.shape[1], -1)
xk = xqkv[:, :, :, self.n_rep:self.n_rep+1].reshape(xqkv.shape[0], xqkv.shape[1], -1)
xv = xqkv[:, :, :, self.n_rep+1:self.n_rep+2].reshape(xqkv.shape[0], xqkv.shape[1], -1)
if not hasattr(self, 'wqkv'): self.wqkv = Tensor.cat(self.wq.weight, self.wk.weight, self.wv.weight)
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.contiguous_backward()), self.wv(x)
@@ -206,14 +200,14 @@ class Transformer:
def forward(self, tokens:Tensor, start_pos:Union[Variable,int], temperature:float, top_k:int, top_p:float, alpha_f:float, alpha_p:float):
_bsz, seqlen = tokens.shape
h = self.tok_embeddings(tokens).contiguous()
h = self.tok_embeddings(tokens)
freqs_cis = self.freqs_cis.cast(h.dtype)[:, start_pos:start_pos+seqlen, :, :, :]
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).contiguous().contiguous_backward()).contiguous_backward()
logits = self.output(self.norm(h))
if math.isnan(temperature): return logits
return sample(logits[:, -1, :].flatten(), temperature, top_k, top_p, alpha_f, alpha_p)
+1 -1
View File
@@ -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).cast(obj.dtype).reshape(obj.shape))
obj.assign(dat.to(obj.device).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)
+11 -7
View File
@@ -3,7 +3,7 @@ from __future__ import annotations
import enum, collections
from typing import Iterator
from tinygrad.helpers import colored
from tinygrad.renderer.amd.sqtt import PacketType, bits
from extra.assembly.amd.sqtt import PacketType, bits
# ═══════════════════════════════════════════════════════════════════════════════
# STALL REASONS
@@ -129,6 +129,14 @@ 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_samples(samples:list[tuple[PMASample, int]]) -> None:
if not samples: return
base_pc = min(s.pc_offset for s, _ in samples)
for s, tpc_id in samples:
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 - base_pc:06x} {stall_str} ev={s.stall_key:2d} active={s.active} wave={s.wave_id:2d} gpc={gpc} tpc={tpc} sm={sm}")
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)
@@ -179,11 +187,7 @@ if __name__ == "__main__":
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))
samples = list(decode(raw, sm_ver))
print(f"\nDecoded {len(samples)} samples:")
print_samples(samples)
print_aggregated(samples)
+1 -1
View File
@@ -7,7 +7,7 @@ export CAPTURE_PROCESS_REPLAY=1
rm "$LOGOPS" 2>/dev/null || true
test/external/process_replay/reset.py
CI=1 python3 -m pytest -n=auto test/backend/test_ops.py test/backend/test_nn.py test/unit/test_winograd.py test/null/test_real_world.py --durations=20
CI=1 python3 -m pytest -n=auto test/test_ops.py test/test_nn.py test/unit/test_winograd.py test/null/test_real_world.py --durations=20
CL=1 python3 -m pytest test/test_tiny.py
# extract, sort and uniq
+2 -2
View File
@@ -7,8 +7,8 @@ import subprocess, struct, math, functools
from tinygrad import Tensor, dtypes, Device
from tinygrad.helpers import getenv
from tinygrad.runtime.autogen.amd.rdna3.ins import *
from tinygrad.renderer.amd.asm import waitcnt
from extra.assembly.amd.autogen.rdna3.ins import *
from extra.assembly.amd.asm import waitcnt
from test.testextra.test_cfg_viz import asm_kernel
-24
View File
@@ -1,24 +0,0 @@
#!/bin/sh
install_loc="$HOME/.local/bin"
docker build --platform=linux/amd64 -t cuda-nvcc:12.8 - <<'EOF'
FROM ubuntu:22.04
RUN apt-get update && apt-get install -y --no-install-recommends wget ca-certificates && \
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
dpkg -i cuda-keyring_1.1-1_all.deb && \
apt-get update && apt-get install -y --no-install-recommends cuda-nvcc-12-8 cuda-nvdisasm-12-8 cuda-cuobjdump-12-8 && rm -rf /var/lib/apt/lists/*
ENV PATH=/usr/local/cuda/bin:$PATH
EOF
mkdir -p "$install_loc"
tee "$install_loc/nvccshim" >/dev/null <<'EOF'
#!/bin/sh
set -eu
# assume the final arg is the input path
# mount it so that container can read it
dir=$(dirname "${@: -1}")
exec docker run --rm --platform=linux/amd64 -v "$dir":"$dir" cuda-nvcc:12.8 "$(basename "$0")" "$@"
EOF
chmod +x "$install_loc/nvccshim"
for t in nvcc nvdisasm; do
ln -sf "$install_loc/nvccshim" "$install_loc/$t"
done
+23 -6
View File
@@ -2,13 +2,30 @@
## Getting SQ Thread Trace
`VIZ=2` to enable SQTT profiling.
`SQTT_ITRACE_SE_MASK=X` to select shader engines for instruction tracing, -1 = all, 0 = disabled, >0 = SE bitmask, default 0b11.
SQTT is implemented on top of normal tinygrad profiling, `VIZ=1 SQTT=1` to get profile pickle with sqtt data embedded in it.
`SQTT_BUFFER_SIZE=X` to change size of SQTT buffer (per shader engine, 6 SEs on 7900xtx) in megabytes, default 256.
## Viewing the traces
`SQTT_ITRACE_SE_MASK=X` to select for which shader engines instruction tracing will be enabled, -1 is all, 0 is none (instruction tracing disabled), >0 is
bitfield/mask for SEs to enable instruction tracing on. Masking shader engines will give smaller file sizes at a cost of less hits and kernels that
don't have any wavefront on first simd of shader engine with instruction tracing enabled will not have instruction timings.
The default is 2 (second shader engine only), only one for file size reasons, second instead of first because dispatch starts from it so there is
greater chance that kernels with small global size will have instruction tracing data.
Note that instruction tracing might not be available for kernels with small global dims, this is not a bug, but it can be improved with various hacks
to the point where it can reliably trace a kernel consisting of a single wavefront (am only, not quite reliable under amdgpu due to waves sometimes
being dispatched starting from different simds). More info in comments in ops_amd.py
- Web UI: `tinygrad/viz/serve.py`
- Command line: `python -m tinygrad.renderer.amd.sqtt`
## Converting pickled profile with SQTT data into RGP file
```bash
extra/sqtt/rgptool.py create "/tmp/profile.pkl.$USER" -o /tmp/gpu0.rgp
```
Then load gpu0.rgp into Radeon GPU Profiler. It works just fine both in wine (macos, native version available for linux) and via ssh X forwarding
If multiple gpus are used you can select which one to export with `-d` like this:
```bash
extra/sqtt/rgptool.py create "/tmp/profile.pkl.$USER" -d 'AMD:5' -o /tmp/gpu5.rgp
```
+152
View File
@@ -0,0 +1,152 @@
import os
os.environ["PYTHONPATH"] = "."
os.environ["SQTT"] = "1"
if "DEV" not in os.environ: os.environ["DEV"] = "AMD"
os.environ["PROFILE"] = "1"
os.environ["AMD_LLVM"] = "0"
from dataclasses import replace
import atexit, contextlib
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
from extra.sqtt.attempt_sqtt_parse import parse_sqtt_print_packets
dev = Device["AMD"]
@contextlib.contextmanager
def save_sqtt():
# clear the old traces
dev.profile_events.clear()
sqtt:dict[str, list[WaveExec]] = {}
yield sqtt
events = dev.profile_events
#rctx = decode(events)
#assert len(rctx.inst_execs) > 0, "empty sqtt output"
#sqtt.update(rctx.inst_execs)
for e in events:
if isinstance(e, ProfileSQTTEvent):
print(replace(e, blob=b''))
if e.se == 0:
parse_sqtt_print_packets(e.blob)
template = """.text
.globl matmul
.p2align 8
.type matmul,@function
matmul:
INSTRUCTION
.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
.amdhsa_wavefront_size32 1
.end_amdhsa_kernel
.amdgpu_metadata
---
amdhsa.version:
- 1
- 0
amdhsa.kernels:
- .name: matmul
.symbol: matmul.kd
.group_segment_fixed_size: 0
.private_segment_fixed_size: 0
.wavefront_size: 32
.sgpr_count: 8
.vgpr_count: 8
.max_flat_workgroup_size: 1024
.kernarg_segment_align: 8
.kernarg_segment_size: 8
.args:
- .address_space: global
.name: a
.offset: 0
.size: 8
.type_name: 'float*'
.value_kind: global_buffer
...
.end_amdgpu_metadata
"""
def run_asm(src, num_workgroups=1, num_waves=1):
WAVE_SIZE = 32
t = Tensor.empty(0x1000).realize()
buf = t.uop.buffer.ensure_allocated()
lib = dev.compiler.compile(template.replace("INSTRUCTION", '\n'.join(src)))
dev.compiler.disassemble(lib)
fxn = AMDProgram(dev, "matmul", lib)
fxn(buf._buf, global_size=(num_workgroups,1,1), local_size=(WAVE_SIZE*num_waves,1,1), wait=True)
if __name__ == "__main__":
with save_sqtt() as sqtt:
run_asm([
"s_nop 100",
"s_nop 100",
"s_load_b64 s[0:1], s[0:1], null",
"s_waitcnt lgkmcnt(0)",
"s_nop 100",
"s_nop 100",
"s_add_i32 s2, s2, 10",
"s_add_i32 s2, s2, 10",
"s_nop 100",
"s_nop 100",
"v_mov_b32_e32 v0, 0",
"v_mov_b32_e32 v0, 0",
"s_nop 100",
"s_nop 100",
"v_dual_fmac_f32 v2, v48, v24 :: v_dual_fmac_f32 v9, v37, v51",
"v_dual_fmac_f32 v2, v48, v24 :: v_dual_fmac_f32 v9, v37, v51",
"s_nop 100",
"s_nop 100",
"global_load_b128 v[2:5], v0, s[0:1]",
"global_load_b128 v[2:5], v0, s[0:1]",
"s_nop 100",
"s_nop 100",
"s_sendmsg sendmsg(MSG_DEALLOC_VGPRS)",
"s_endpgm",
], num_workgroups=1, num_waves=1)
exit(0)
with save_sqtt() as sqtt:
#(Tensor.empty(16,16) @ Tensor.empty(16,16)).elu().realize()
#Tensor.empty(1, 64).sum(axis=1).realize()
Tensor.empty(1).log2().realize()
exit(0)
with save_sqtt() as sqtt:
# what's in v0?
run_asm([
"v_mov_b32_e32 v0, 0",
"v_mov_b32_e32 v1, 0",
"s_clause 0x1",
"s_load_b64 s[0:1], s[0:1], null",
"s_waitcnt lgkmcnt(0)",
]+[
"global_load_b32 v1, v0, s[0:1]",
]*10+[
"global_load_b32 v10, v1, s[0:1]",
"s_waitcnt vmcnt(0)",
#"v_rcp_f32 v1, v0"
#"v_add_f32_e32 v1 v0 v0",
#"v_add_f32_e32 v5 v4 v4",
#"v_add_f32_e32 v7 v6 v6",
#"v_add_f32_e32 v1 v0 v0",
#"v_add_f32_e32 v2 v1 v1",
#"s_nop 1"
]*5+[
"v_add_f32_e32 v3 v2 v2",
]*5+[
"v_mul_f32_e32 v3 v2 v2",
]*7)
+548
View File
@@ -0,0 +1,548 @@
import pickle, sys
from tinygrad.helpers import getenv, Timing, colored
from extra.sqtt.roc import decode, ProfileSQTTEvent
# do these enums match fields in the packets?
#from tinygrad.runtime.support.amd import import_soc
#soc = import_soc([11])
#perf_sel = {getattr(soc, k):k for k in dir(soc) if k.startswith("SQ_PERF_")}
# Instruction packets (one per ISA op)
# NOTE: these are bad guesses and may be wrong! feel free to update if you know better
# some names were taken from SQ_TT_TOKEN_MASK_TOKEN_EXCLUDE_SHIFT
# we see 18 opcodes
# opcodes(18): 1 2 3 4 5 6 8 9 F 10 11 12 14 15 16 17 18 19
# if you exclude everything, you are left with 6
# opcodes( 6): 10 11 14 15 16 17
# sometimes we see a lot of B, but not repeatable
# not seen
# 7 A C
# NOTE: INST runs before EXEC
OPCODE_COLORS = {
# dispatches are BLACK
0x1: "BLACK",
0x18: "BLACK",
# execs are yellow
0x2: "yellow",
0x3: "yellow",
0x4: "YELLOW",
0x5: "YELLOW",
# waves are blue
0x8: "blue",
0x9: "blue",
0x6: "cyan",
0xb: "cyan",
}
OPCODE_NAMES = {
# gated by SQ_TT_TOKEN_EXCLUDE_VALUINST_SHIFT (but others must be enabled for it to show)
0x01: "VALUINST",
# gated by SQ_TT_TOKEN_EXCLUDE_VMEMEXEC_SHIFT
0x02: "VMEMEXEC",
# gated by SQ_TT_TOKEN_EXCLUDE_ALUEXEC_SHIFT
0x03: "ALUEXEC",
# gated by SQ_TT_TOKEN_EXCLUDE_IMMEDIATE_SHIFT
0x04: "IMMEDIATE",
0x05: "IMMEDIATE_MASK",
# gated by SQ_TT_TOKEN_EXCLUDE_WAVERDY_SHIFT
0x06: "WAVERDY",
# gated by SQ_TT_TOKEN_EXCLUDE_WAVESTARTEND_SHIFT
0x08: "WAVEEND",
0x09: "WAVESTART",
# gated by SQ_TT_TOKEN_EXCLUDE_WAVEALLOC_SHIFT
0x0B: "WAVEALLOC", # FFF00
# gated by NOT SQ_TT_TOKEN_EXCLUDE_PERF_SHIFT
0x0D: "PERF",
# gated by SQ_TT_TOKEN_EXCLUDE_EVENT_SHIFT
0x12: "EVENT",
0x13: "EVENT_BIG", # FFFFF800
# some gated by SQ_TT_TOKEN_EXCLUDE_REG_SHIFT, some always there. something is broken with the timing on this
0x14: "REG",
# gated by SQ_TT_TOKEN_EXCLUDE_INST_SHIFT
0x18: "INST",
# gated by SQ_TT_TOKEN_EXCLUDE_UTILCTR_SHIFT
0x19: "UTILCTR",
# this is the first (8 byte) packet in the bitstream
0x17: "LAYOUT_HEADER", # layout/mode/group + selectors A/B (reversed)
# pure time (no extra bits)
0x0F: "TS_DELTA_SHORT",
0x10: "NOP",
0x11: "TS_WAVE_STATE", # almost pure time, has a small flag
# not a good name, but seen and understood mostly
0x15: "SNAPSHOT", # small delta + 50-ish bits of snapshot
0x16: "TS_DELTA_OR_MARK", # 36-bit long delta or 36-bit marker
# packets we haven't seen / rarely see 0x0b
0x07: "TS_DELTA_S8_W3_7", # shift=8, width=3 (small delta)
0x0A: "TS_DELTA_S5_W2_A", # shift=5, width=2
0x0C: "TS_DELTA_S5_W3_B", # shift=5, width=3 (different consumer)
}
# SALU = 0x0 / s_mov_b32
# SMEM = 0x1 / s_load_b*
# JUMP = 0x3 / s_cbranch_scc0
# NEXT = 0x4 / s_cbranch_execz
# MESSAGE = 0x9 / s_sendmsg
# VALU = 0xb / v_(exp,log)_f32_e32
# VALU = 0xd / v_lshlrev_b64
# VALU = 0xe / v_mad_u64_u32
# VMEM = 0x21 / global_load_b32
# VMEM = 0x22 / global_load_b32
# VMEM = 0x24 / global_store_b32
# VMEM = 0x25 / global_store_b64
# VMEM = 0x27 / global_store
# VMEM = 0x28 / global_store_b64
# LDS = 0x29 / ds_load_b128
# LDS = 0x2b / ds_store_b32
# LDS = 0x2e / ds_store_b128
# ???? = 0x5a / hidden global_load instruction
# ???? = 0x5b / hidden global_load instruction
# ???? = 0x5c / hidden global_store instruction
# VALU = 0x73 / v_cmpx_eq_u32_e32 (not normal VALUINST)
OPNAME = {
0x0: "SALU",
0x1: "SMEM",
0x3: "JUMP",
0x4: "NEXT",
0x9: "MESSAGE",
0xb: "VALU",
0xd: "VALU",
0xe: "VALU",
0x21: "VMEM_LOAD",
0x22: "VMEM_LOAD",
0x24: "VMEM_STORE",
0x25: "VMEM_STORE",
0x26: "VMEM_STORE",
0x27: "VMEM_STORE",
0x28: "VMEM_STORE",
0x29: "LDS_LOAD",
0x2b: "LDS_STORE",
0x2e: "LDS_STORE",
0x50: "__SIMD_LDS_LOAD",
0x51: "__SIMD_LDS_LOAD",
0x54: "__SIMD_LDS_STORE",
0x5a: "__SIMD_VMEM_LOAD",
0x5b: "__SIMD_VMEM_LOAD",
0x5c: "__SIMD_VMEM_STORE",
0x5d: "__SIMD_VMEM_STORE",
0x5e: "__SIMD_VMEM_STORE",
0x5f: "__SIMD_VMEM_STORE",
0x72: "SALU_OR",
0x73: "VALU_CMPX",
}
ALUSRC = {
1: "SALU",
2: "VALU",
3: "VALU_SALU",
}
MEMSRC = {
0: "LDS",
1: "__LDS",
2: "VMEM",
3: "__VMEM",
}
# these tables are from rocprof trace decoder
# rocprof_trace_decoder_parse_data-0x11c6a0
# parse_sqtt_180 = b *rocprof_trace_decoder_parse_data-0x11c6a0+0x110040
# ---------- 1. local_138: 256-byte state->opcode table ----------
STATE_TO_OPCODE: bytes = bytes([
0x10, 0x16, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x17, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x07, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x19, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x00, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x11, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x12, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x15, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x16, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x17, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x07, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x19, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x00, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x11, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
0x10, 0x13, 0x18, 0x01, 0x05, 0x0b, 0x0c, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x09, 0x04, 0x03, 0x02,
0x10, 0x15, 0x18, 0x01, 0x06, 0x08, 0x0d, 0x00, 0x0f, 0x14, 0x18, 0x01, 0x0a, 0x04, 0x03, 0x02,
])
# opcode mask (the bits used to determine the opcode, worked out by looking at the repeats in STATE_TO_OPCODE)
opcode_mask = {
0x10: 0b1111,
0x16: 0b1111111,
0x17: 0b1111111,
0x07: 0b1111111,
0x19: 0b1111111,
0x11: 0b1111111,
0x12: 0b11111111,
0x13: 0b11111111,
0x15: 0b1111111,
0x18: 0b111,
0x1: 0b111,
0x5: 0b11111,
0x6: 0b11111,
0xb: 0b11111,
0x8: 0b11111,
0xc: 0b11111,
0xd: 0b11111,
0xf: 0b1111,
0x14: 0b1111,
0x9: 0b11111,
0xa: 0b11111,
0x4: 0b1111,
0x3: 0b1111,
0x2: 0b1111,
}
# ---------- 2. DAT_0012e280: nibble budget per opcode&0x1F ----------
NIBBLE_BUDGET = [
0x08, 0x0C, 0x08, 0x08, 0x0C, 0x18, 0x18, 0x40, 0x14, 0x20, 0x30, 0x14, 0x34, 0x1C, 0x30, 0x08,
0x04, 0x18, 0x18, 0x20, 0x40, 0x40, 0x30, 0x40, 0x14, 0x30, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
]
# ---------- 3. delta_map from your hash nodes ----------
# opcode -> (shift, width)
DELTA_MAP_DEFAULT = {
0x01: (3, 3), # shift=3, end=6
0x02: (4, 2), # shift=4, end=6
0x03: (4, 2), # shift=4, end=6
0x04: (4, 3), # shift=4, end=7
0x05: (5, 3), # shift=5, end=8
0x06: (5, 3), # shift=5, end=8
0x07: (8, 3), # shift=8, end=11
0x08: (5, 3), # shift=5, end=8
0x09: (5, 2), # shift=5, end=7
0x0A: (5, 2), # shift=5, end=7
0x0B: (5, 3), # shift=5, end=8
0x0C: (5, 3), # shift=5, end=8
0x0D: (5, 3), # shift=5, end=8
# NOTE: 0x0e can never be decoded, it's not in the STATE_TO_OPCODE table
#0x0E: (7, 2), # shift=7, end=9
0x0F: (4, 4), # shift=4, end=8
0x10: (0, 0), # shift=0, end=0 (no delta)
0x11: (7, 9), # shift=7, end=16
0x12: (8, 3), # shift=8, end=11
0x13: (8, 3), # shift=8, end=11
0x14: (4, 3), # shift=4, end=7
0x15: (7, 3), # shift=7, end=10
0x16: (12, 36), # shift=12, end=48 (36-bit field, matches the 0x16 special-case)
0x17: (0, 0), # shift=0, end=0 (no delta)
0x18: (4, 3), # shift=4, end=7
0x19: (7, 2), # shift=7, end=9
}
# ---------- 4. One-line-per-packet parser ----------
def reg_mask(opcode):
nb_bits = NIBBLE_BUDGET[opcode & 0x1F]
shift, width = DELTA_MAP_DEFAULT[opcode]
delta_mask = ((1 << width) - 1) << shift
assert delta_mask & opcode_mask[opcode] == 0, "masks shouldn't overlap"
return ((1 << nb_bits) - 1) & ~(delta_mask | opcode_mask[opcode])
def decode_packet_fields(opcode: int, reg: int) -> str:
"""
Decode packet payloads conservatively, using:
- NIBBLE_BUDGET[opcode & 0x1F] to mask reg down to true width.
- DELTA_MAP_DEFAULT[opcode] to expose the "primary" field (often delta).
- Per-opcode layouts derived from rocprof's decompiled consumers.
"""
# --- 0. Restrict to real packet bits not used in delta ---------------------------------
pkt = reg & reg_mask(opcode)
fields: list[str] = []
match opcode:
case 0x01: # VALUINST
# 6 bit field
flag = (pkt >> 6) & 1
wave = pkt >> 7
fields.append(f"wave={wave:x}")
if flag: fields.append("flag")
case 0x02: # VMEMEXEC
# 2 bit field (pipe is a guess)
src = pkt>>6
fields.append(f"src={src} [{MEMSRC.get(src, '')}]")
case 0x03: # ALUEXEC
# 2 bit field
src = pkt>>6
fields.append(f"src={src} [{ALUSRC.get(src, '')}]")
case 0x04: # IMMEDIATE_4
# 5 bit field (actually 4)
wave = pkt >> 7
fields.append(f"wave={wave:x}")
case 0x05: # IMMEDIATE_5
# 16 bit field
# 1 bit per wave
fields.append(f"mask={pkt>>8:016b}")
case 0x6:
# wave ready FFFF00
# 16 bit field
# 1 bit per wave
fields.append(f"mask={pkt>>8:016b}")
case 0x0d:
# 20 bit field
fields.append(f"arg = {pkt>>8:X}")
case 0x12:
fields.append(f"event = {pkt>>11:X}")
case 0x15:
fields.append(f"snap = {pkt>>10:X}")
case 0x19:
# wave end
fields.append(f"ctr = {pkt>>9:X}")
case 0xf:
extracted_delta = (reg >> 4) & 0xF
fields.append(f"strange_delta=0x{extracted_delta:x}")
case 0x11:
# DELTA_MAP_DEFAULT: shift=7, width=9 -> small delta.
# FF0000 is the mask
coarse = pkt >> 16
fields.append(f"coarse=0x{coarse:02x}")
# From decomp:
# - when layout<3 and coarse&1, it sets a "has interesting wave" flag
# - when coarse&8, it marks all live waves as "terminated"
if coarse & 0x01:
fields.append("flag_wave_interest=1")
if coarse & 0x08:
fields.append("flag_terminate_all=1")
case 0x8:
# wave end, this is 20 bits (FFF00)
flag7 = (pkt >> 8) & 1
simd = (pkt >> 9) & 3
cu = ((pkt >> 11) & 0x7) | (flag7 << 3)
wave = (pkt >> 15) & 0x1f
fields.append(f"wave={wave:x}")
fields.append(f"simd={simd}")
fields.append(f"cu={cu}")
case 0x9:
# From case 9 (WAVESTART) in multiple consumers:
# flag7 = (w >> 7) & 1 (low bit of uVar41)
# cls2 = (w >> 8) & 3 (class / group)
# slot4 = (w >> 10) & 0xf (slot / group index)
# idx_lo = (w >> 0xd) & 0x1f (low index, layout<4 path)
# idx_hi = (w >> 0xf) & 0x1f (high index, layout>=4 path)
# id7 = (w >> 0x19) & 0x7f (7-bit id)
flag7 = (pkt >> 7) & 1
simd = (pkt >> 8) & 3
cu = ((pkt >> 10) & 0x7) | (flag7 << 3)
wave = (pkt >> 13) & 0x1F
id7 = (pkt >> 17)
fields.append(f"wave={wave:x}")
fields.append(f"simd={simd}")
fields.append(f"cu={cu}")
fields.append(f"id7=0x{id7:x}")
case 0x18:
# FFF88 is the mask
# From case 0x18:
# low3 = w & 7
# grp3 = (w >> 3) or (w >> 4) & 7 (layout-dependent)
# flags = bits 6 (B6) and 7 (B7)
# hi8 = (w >> 0xc) & 0xff (layout 4 path)
# hi7 = (w >> 0xd) & 0x7f (other layouts)
# idx5 = (w >> 7) or (w >> 8) & 0x1f, used as wave index
flag1 = (pkt >> 3) & 1
flag2 = (pkt >> 7) & 1
wave = (pkt >> 8) & 0x1F
op = (pkt >> 13)
fields.append(f"wave={wave:x}")
fields.append(f"op=0x{op:02x} [{OPNAME.get(op, '')}]")
if flag1: fields.append("flag1")
if flag2: fields.append("flag2")
case 0x14:
subop = (pkt >> 16) & 0xFFFF # (short)(w >> 0x10)
val32 = (pkt >> 32) & 0xFFFFFFFF # (uint)(w >> 0x20)
slot = (pkt >> 7) & 0x7 # index in local_168[...] tables
hi_byte = (pkt >> 8) & 0xFF # determines config vs marker
fields.append(f"subop=0x{subop:04x}")
fields.append(f"slot={slot}")
fields.append(f"val32=0x{val32:08x}")
if hi_byte & 0x80:
# Config flavour: writes config words into per-slot state arrays.
fields.append("kind=config")
if subop == 0x000C:
fields.append("slot=lo")
elif subop == 0x000D:
fields.append("slot=hi")
else:
# COR marker: subop 0xC342, payload "COR\0" → start of a COR region.
if subop == 0xC342:
fields.append("kind=cor_stream")
if val32 == 0x434F5200:
fields.append("cor_magic='COR\\0'")
case 0x16:
# Bits:
# bit8 -> 0x100
# bit9 -> 0x200
# bits 12..47 -> 36-bit field used as delta or marker
bit8 = bool(pkt & 0x100)
bit9 = bool(pkt & 0x200)
if not bit9:
mode = "delta"
elif not bit8:
mode = "marker"
else:
mode = "other"
# need to use reg here
val36 = (reg >> 12) & ((1 << 36) - 1)
fields.append(f"mode={mode}")
if mode != "delta":
fields.append(f"val36=0x{val36:x}")
case 0x17:
# From decomp (two sites with identical logic):
# layout = (w >> 7) & 0x3f
# mode = (w >> 0xd) & 3
# group = (w >> 0xf) & 7
# sel_a = (w >> 0x1c) & 0xf
# sel_b = (w >> 0x21) & 7
# flag4 = (w >> 0x3b) & 1 (only meaningful when layout == 4)
layout = (pkt >> 7) & 0x3F
simd = (pkt >> 13) & 0x3 # you can change this by changing traced simd
group = (pkt >> 15) & 0x7
sel_a = (pkt >> 0x1C) & 0xF
sel_b = (pkt >> 0x21) & 0x7
flag4 = (pkt >> 0x3B) & 0x1
fields.append(f"layout={layout}")
fields.append(f"group={group}")
fields.append(f"simd={simd}")
fields.append(f"sel_a={sel_a}")
fields.append(f"sel_b={sel_b}")
if layout == 4:
fields.append(f"layout4_flag={flag4}")
case _:
fields.append(f"{pkt:X} & {reg_mask(opcode):X}")
return ",".join(fields)
FILTER_LEVEL = getenv("FILTER", 1)
DEFAULT_FILTER: tuple[int, ...] = tuple()
# NOP + pure time + "sample"
if FILTER_LEVEL >= 0: DEFAULT_FILTER += (0x10, 0xf, 0x11)
# reg + event + sample + marker
# TODO: events are probably good
if FILTER_LEVEL >= 1: DEFAULT_FILTER += (0x14, 0x12, 0x16)
# instruction runs + valuinst
if FILTER_LEVEL >= 2: DEFAULT_FILTER += (0x01, 0x02, 0x03)
# instructions dispatch (inst, immed)
if FILTER_LEVEL >= 3: DEFAULT_FILTER += (0x4, 0x5, 0x18)
# waves
if FILTER_LEVEL >= 4: DEFAULT_FILTER += (0x6, 0x8, 0x9)
def parse_sqtt_print_packets(data: bytes, filter=DEFAULT_FILTER, verbose=True) -> None:
"""
Minimal debug: print ONE LINE per decoded token (packet).
Now prints only the actual nibbles that belong to each packet, instead of
the full 64-bit shift register.
"""
n = len(data)
time = 0
last_printed_time = 0
reg = 0 # shift register
offset = 0 # bit offset, in steps of 4 (one nibble)
nib_budget = 0x40
flags = 0
token_index = 0
opcodes_seen = set()
while (offset >> 3) < n:
# 1) Fill register with nibbles according to nib_budget
if nib_budget != 0:
target = offset + 4 + ((nib_budget - 1) & ~3)
while offset != target and (offset >> 3) < n:
byte = data[offset >> 3]
nib = (byte >> (offset & 4)) & 0xF
reg = ((reg >> 4) | (nib << 60)) & ((1 << 64) - 1)
offset += 4
if offset != target: break # don't parse past the end
# 2) Decode token from low 8 bits
opcode = STATE_TO_OPCODE[reg & 0xFF]
opcodes_seen.add(opcode)
# 4) Set next nibble budget based on opcode
nib_budget = NIBBLE_BUDGET[opcode & 0x1F]
# 5) Get delta
shift, width = DELTA_MAP_DEFAULT[opcode]
delta = (reg >> shift) & ((1 << width) - 1)
# 6) Update time and handle special opcodes 0xF/0x16
if opcode == 0x16:
two_bits = (reg >> 8) & 0x3
if two_bits == 1:
flags |= 0x01
# Common 36-bit field at bits [12..47]
if (reg & 0x200) == 0:
# delta mode: add 36-bit delta to time
pass
elif (reg & 0x100) == 0:
# marker / other modes: no time advance
# real marker: bit9=1, bit8=0, non-zero payload
# "other" 0x16 variants, ignored for timing
delta = 0
else:
raise RuntimeError("unknown 0x16 delta")
elif opcode == 0x0F:
# opcode 0x0F has an offset of 4 to the delta
# update: it's actually computed to be 8 to match WAVESTART
delta = delta + 8
# Append extra decoded fields into the note string
note = decode_packet_fields(opcode, reg)
# this delta happens before the instruction
time += delta
token_index += 1
if verbose and (filter is None or opcode not in filter):
print(f"{time:8d} +{time-last_printed_time:8d} : "+colored(f"{OPCODE_NAMES[opcode]:18s} ", OPCODE_COLORS.get(opcode, "white"))+f"{note}")
last_printed_time = time
# Optional summary at the end
print(f"# done: tokens={token_index:_}, final_time={time}, flags=0x{flags:02x}")
if verbose:
print(f"opcodes({len(opcodes_seen):2d}):",
' '.join([colored(f"{op:2X}", "WHITE" if op in opcodes_seen else "BLACK") for op in sorted(opcode_mask)]))
def parse(fn:str):
with Timing(f"unpickle {fn}: "): dat = pickle.load(open(fn, "rb"))
#if getenv("ROCM", 0):
# with Timing(f"decode {fn}: "): ctx = decode(dat)
dat_sqtt = [x for x in dat if isinstance(x, ProfileSQTTEvent)]
print(f"got {len(dat_sqtt)} SQTT events in {fn}")
return dat_sqtt
if __name__ == "__main__":
fn = "extra/sqtt/examples/profile_gemm_run_0.pkl"
dat_sqtt = parse(sys.argv[1] if len(sys.argv) > 1 else fn)
for i,dat in enumerate(dat_sqtt):
with Timing(f"decode pkt {i} with len {len(dat.blob):_}: "):
parse_sqtt_print_packets(dat.blob, verbose=getenv("V", 1))
-148
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@@ -1,148 +0,0 @@
#!/usr/bin/env python3
# Run all ALU and memory instructions in the ISA
import functools, inspect
from enum import Enum
from tinygrad import Tensor, Device, dtypes
from tinygrad.uop.ops import UOp, Ops, KernelInfo, AddrSpace
from tinygrad.renderer.amd.dsl import Inst, Reg, OPERANDS, SrcField, VGPRField, SGPRField, SSrcField, SBaseField, AlignedSGPRField, BitField
from tinygrad.renderer.amd.dsl import FixedBitField, EnumBitField, s, v, NULL, VCC_LO
from extra.gemm.amd_asm_matmul import Kernel
# skip instructions that mutate wave state (PC, EXEC, allocations, signals)
SKIP = {"S_SETPC_B64", "S_SWAPPC_B64", "S_RFE_B64", "S_BARRIER_SIGNAL_ISFIRST", "S_GET_BARRIER_STATE", "S_ALLOC_VGPR", "S_SLEEP_VAR", "S_GETPC_B64",
"S_SENDMSG_RTN_B32", "S_SENDMSG_RTN_B64"}
# skip barriers, s_waits, wrap level atomics, and ray tracing (bvh)
SKIP_SUBSTR = ["SAVEEXEC", "CMPX", "WREXEC", "MOVREL", "ATOMIC", "S_BUFFER_", "S_ATC_PROBE", "BARRIER", "S_WAITCNT", "BVH",
"DS_CMPSTORE_RTN", "DS_WRAP_RTN_B32", "DS_ORDERED_COUNT", "DS_GWS", "GS_REG", "GLOBAL_LOAD_LDS", "GLOBAL_STORE_BLOCK"]
ALU_FORMATS = {"VOP1", "VOP1_LIT", "VOP1_SDST", "VOP2", "VOP2_LIT", "VOP3", "VOP3_SDST", "VOP3SD", "VOP3P", "VOP3P_MFMA", "VOP3PX2",
"VOPC", "SOP1", "SOP1_LIT", "SOP2", "SOP2_LIT", "SOPC", "SOPC_LIT", "SOPK", "SOPK_LIT", "VINTERP"}
# intentionally not testing scratch memory ops
MEM_FORMATS = {"VGLOBAL", "GLOBAL", "SMEM", "DS"}
def should_skip(op:Enum) -> bool: return (name:=op.name) in SKIP or any(sub in name for sub in SKIP_SUBSTR)
# ** named register assignments
# ALU operands
ALU_VGPR_STRIDE = 16 # v[0], v[16], v[32], ... per ALU operand slot
ALU_SGPR_STRIDE = 4 # s[0], s[4], s[8], ... per ALU operand slot
# memory address registers
S_KERNARG_PTR = (0, 1)
S_BUF_PTR = (2, 3)
V_VADDR = (0, 1)
V_DS_ADDR = 0
# memory data registers
MEM_VGPR_BASE = 32 # v[32], v[48], ... for vdst/vdata/vsrc
MEM_VGPR_STRIDE = 16 # spacing between memory data vgpr slots
MEM_SGPR_BASE = 8 # s[8], s[10], ... for SMEM sdata
MEM_SGPR_STRIDE = 2 # spacing between memory data sgpr slots
# ** create an ALU instruction based on the operands
def create_alu_inst(op:Enum, builder:functools.partial[Inst]) -> Inst:
inst_cls, operands, slot = builder.func, OPERANDS[op], 0
kwargs:dict[str, Reg|int] = {}
for name, field in inst_cls._fields:
if isinstance(field, (FixedBitField, EnumBitField)): continue
nregs = max(1, operands[name][1] // 32) if name in operands else 1
is_sreg = name in operands and "SREG" in str(operands[name][2])
base_v, base_s = slot * ALU_VGPR_STRIDE, slot * ALU_SGPR_STRIDE
if name == "sdst" and isinstance(field, SGPRField): reg = VCC_LO
elif is_sreg and not isinstance(field, VGPRField): reg = VCC_LO
elif isinstance(field, VGPRField): reg = v[base_v:base_v+nregs-1] if nregs > 1 else v[base_v]
elif isinstance(field, SSrcField): reg = VCC_LO if nregs <= 2 else s[base_s:base_s+nregs-1] if nregs > 1 else s[base_s]
elif isinstance(field, SGPRField): reg = s[base_s:base_s+nregs-1] if nregs > 1 else s[base_s]
elif isinstance(field, SrcField): reg = v[base_v:base_v+nregs-1] if nregs > 1 else v[base_v]
else: reg = None
if reg is not None: kwargs[name] = reg; slot += 1
elif isinstance(field, BitField): kwargs[name] = field.default
return builder(**kwargs)
# ** create a memory instruction with pre set address registers
MEM_PRESET_REGS:dict[str, dict[str, Reg]] = {
"VGLOBAL":{"saddr":s[S_BUF_PTR[0]:S_BUF_PTR[1]], "vaddr":v[V_VADDR[0]:V_VADDR[1]]},
"GLOBAL":{"saddr":s[S_BUF_PTR[0]:S_BUF_PTR[1]], "addr":v[V_DS_ADDR]}, # addr is 32-bit offset when saddr is valid SGPR
"DS":{"addr":v[V_DS_ADDR]},
"SMEM":{"sbase":s[S_KERNARG_PTR[0]:S_KERNARG_PTR[1]], "soffset":NULL},
}
def create_mem_inst(op:Enum, builder:functools.partial[Inst]) -> Inst:
inst_cls, operands, field_map = builder.func, OPERANDS.get(op, {}), MEM_PRESET_REGS.get(builder.func.__name__, {})
kwargs:dict[str, Reg|int] = {}
vslot, sslot = 0, 0
for name, field in inst_cls._fields:
if isinstance(field, (FixedBitField, EnumBitField)): continue
if name in field_map:
kwargs[name] = field_map[name]
continue
nregs = max(1, operands[name][1] // 32) if name in operands else 1
if isinstance(field, VGPRField):
vi = MEM_VGPR_BASE + vslot * MEM_VGPR_STRIDE
kwargs[name] = v[vi:vi+nregs-1] if nregs > 1 else v[vi]
vslot += 1
elif isinstance(field, (SGPRField, AlignedSGPRField, SBaseField)):
si = MEM_SGPR_BASE + sslot * MEM_SGPR_STRIDE
kwargs[name] = s[si:si+nregs-1] if nregs > 1 else s[si]
sslot += 1
elif isinstance(field, BitField): kwargs[name] = field.default
return builder(**kwargs)
# ** collect all memory and ALU instructions from the ISA autogen
def collect_instructions() -> tuple[list[Inst], list[Inst], list[str]]:
op_map:dict[Enum, functools.partial[Inst]] = {}
for name, obj in inspect.getmembers(all_insts):
if isinstance(obj, functools.partial) and len(obj.args) == 1: op_map[obj.args[0]] = obj
alu_insts:list[Inst] = []
mem_insts:list[Inst] = []
skipped:list[str] = []
for op_enum, builder in op_map.items():
if should_skip(op_enum) or op_enum not in OPERANDS: skipped.append(op_enum.name); continue
fmt = builder.func.__name__
if fmt in ALU_FORMATS: alu_insts.append(create_alu_inst(op_enum, builder))
elif fmt in MEM_FORMATS: mem_insts.append(create_mem_inst(op_enum, builder))
return alu_insts, mem_insts, skipped
def exec_insts(insts:list):
k = Kernel(arch)
# ** prologue for global memory
k.emit(s_load_b64(sdata=s[S_BUF_PTR[0]:S_BUF_PTR[1]], sbase=s[S_KERNARG_PTR[0]:S_KERNARG_PTR[1]], soffset=NULL))
k.waitcnt(lgkm=0)
k.emit(v_mov_b32_e32(v[V_VADDR[0]], 0))
k.emit(v_mov_b32_e32(v[V_VADDR[1]], 0))
# ** emit
for inst in insts: k.emit(inst)
k.emit(s_endpgm())
# ** run
NUM_THREADS, NUM_GRIDS, BUF_SIZE = 32, 1, 1024*1024
def fxn(A:UOp, B:UOp, C:UOp) -> UOp:
lidx, gidx = UOp.special(NUM_THREADS, "lidx0"), UOp.special(NUM_GRIDS, "gidx0")
lds = UOp(Ops.DEFINE_LOCAL, dtypes.uint8.ptr(size=BUF_SIZE, addrspace=AddrSpace.LOCAL), (), "lds")
sink = UOp.sink(A.base, B.base, C.base, lds, lidx, gidx, arg=KernelInfo(name="discover_ops"))
return UOp(Ops.PROGRAM, src=(sink, UOp(Ops.DEVICE, arg="AMD"), UOp(Ops.LINEAR, src=tuple(UOp(Ops.INS, arg=x) for x in k.finalize()))))
A = Tensor.empty(BUF_SIZE, dtype=dtypes.uint8)
B = Tensor.empty(1, dtype=dtypes.uint8)
C = Tensor.empty(1, dtype=dtypes.uint8)
Tensor.custom_kernel(A, B, C, fxn=fxn)[0].realize()
if __name__ == "__main__":
import sys
arch = Device[Device.DEFAULT].renderer.arch
if arch.startswith("gfx12"):
from tinygrad.runtime.autogen.amd.rdna4.ins import *
import tinygrad.runtime.autogen.amd.rdna4.ins as all_insts
elif arch.startswith("gfx11"):
from tinygrad.runtime.autogen.amd.rdna3.ins import *
import tinygrad.runtime.autogen.amd.rdna3.ins as all_insts
# these don"t exist in RDNA3, only RDNA3.5 and above
SKIP.update(["S_FMAAK_F32", "S_FMAMK_F32"])
else:
print(f"{arch} not supported yet")
sys.exit(0)
alu_insts, mem_insts, skipped = collect_instructions()
print(f"collected {len(alu_insts)} ALU + {len(mem_insts)} memory instructions ({len(skipped)} skipped)")
exec_insts(mem_insts+alu_insts)
+10 -12
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@@ -1,25 +1,23 @@
import os, subprocess, sys, shlex
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 = {
"empty":"test/backend/test_custom_kernel.py TestCustomKernel.test_empty",
"plus":"test/test_tiny.py TestTiny.test_plus",
"gemm":"-c \"from tinygrad import Tensor; (Tensor.empty(N:=64, N)@Tensor.empty(N, N)).realize()\"",
"ops":"extra/sqtt/examples/discover_ops.py"
}
EXAMPLES = [
"test.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 name,test in EXAMPLES.items():
for test in EXAMPLES:
for i in range(2):
# AM_RESET=1 gets a clear trace, does not work on mi300 machines
subprocess.run([sys.executable, *shlex.split(test)], cwd=EXAMPLES_DIR.parent.parent.parent,
env={**os.environ, "AMD":"1", "AM_RESET":"1" if not arch.startswith("gfx9") else "0", "VIZ":"-2", "PYTHONPATH":"."})
PROFILE_PATH.rename(dest:=EXAMPLES_DIR/arch/f"profile_{name}_run_{i}.pkl")
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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