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acbe6361ab |
@@ -643,14 +643,14 @@ jobs:
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run: BENCHMARK_LOG=openpilot_0_10_1_policy PYTHONPATH="." ASSERT_MIN_STEP_TIME=4 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/driving_policy.onnx
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- name: openpilot compile3 0.10.1 dmonitoring
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run: BENCHMARK_LOG=openpilot_0_10_1_dmonitoring PYTHONPATH="." ASSERT_MIN_STEP_TIME=10 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/dmonitoring_model.onnx
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- name: benchmark MobileNetV2 on DSP
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run: |
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# generate quantized weights
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ln -s /data/home/tiny/tinygrad/extra/datasets/imagenet extra/datasets/imagenet
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ln -s /data/home/tiny/tinygrad/testsig-*.so .
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PYTHONPATH=. CC=clang-19 CPU=1 CPU_LLVM=0 QUANT=1 CNT=0 python3 examples/test_onnx_imagenet.py https://github.com/xamcat/mobcat-samples/raw/refs/heads/master/onnx_runtime/InferencingSample/InferencingSample/mobilenetv2-7.onnx /tmp/model.quant.onnx
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# benchmark on DSP with NOOPT=1, the devectorizer has issues
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PYTHONPATH=. CC=clang-19 DSP=1 NOOPT=1 CNT=2 DEBUG=2 python3 examples/test_onnx_imagenet.py /tmp/model.quant.onnx
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# - name: benchmark MobileNetV2 on DSP
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# run: |
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# # generate quantized weights
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# ln -s /data/home/tiny/tinygrad/extra/datasets/imagenet extra/datasets/imagenet
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# ln -s /data/home/tiny/tinygrad/testsig-*.so .
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# PYTHONPATH=. CC=clang-19 CPU=1 CPU_LLVM=0 QUANT=1 CNT=0 python3 examples/test_onnx_imagenet.py https://github.com/xamcat/mobcat-samples/raw/refs/heads/master/onnx_runtime/InferencingSample/InferencingSample/mobilenetv2-7.onnx /tmp/model.quant.onnx
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# # benchmark on DSP with NOOPT=1, the devectorizer has issues
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# PYTHONPATH=. CC=clang-19 DSP=1 NOOPT=1 CNT=2 DEBUG=2 python3 examples/test_onnx_imagenet.py /tmp/model.quant.onnx
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- name: Run process replay tests
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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
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@@ -306,6 +306,7 @@ jobs:
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with:
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key: spec-unit
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deps: testing_unit
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python-version: '3.14'
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- name: Test SPEC=2
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run: IGNORE_OOB=0 SPEC=2 PYTHONPATH="." pytest --maxfail=10 -n auto --durations=30 --ignore=test/models --ignore test/unit/test_hashing.py --timeout 60 -k "not test_setitem_big" --splits 2 --group ${{ matrix.group }}
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+2
-2
@@ -1,8 +1,6 @@
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from pathlib import Path
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from typing import List
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import json, argparse, random, time, os
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import tiktoken
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from tiktoken.load import load_tiktoken_bpe
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from extra.models.llama import Transformer, convert_from_huggingface, convert_from_gguf, fix_bf16
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from tinygrad.nn.state import safe_load, torch_load, load_state_dict, get_parameters, gguf_load
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from tinygrad import Tensor, dtypes, nn, Context, Device, GlobalCounters
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@@ -12,6 +10,8 @@ from extra.bench_log import BenchEvent, WallTimeEvent
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class Tokenizer:
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pat_str = r"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"
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def __init__(self, model_path: str):
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import tiktoken
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from tiktoken.load import load_tiktoken_bpe
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mergeable_ranks = load_tiktoken_bpe(model_path)
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self.num_base_tokens = len(mergeable_ranks)
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special_tokens = [
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@@ -4,9 +4,9 @@ from tinygrad.engine.realize import ExecItem, get_runner
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from tinygrad.dtype import AddrSpace
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from tinygrad.helpers import getenv
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N = 4096
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N = getenv("N", 4096)
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M = K = N
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run_count = 5
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run_count = getenv("CNT", 5)
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# ---------------------------
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# launch/config constants
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@@ -155,14 +155,15 @@ def test_matmul(sink:UOp, N=N):
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ets.append(ei.run(wait=True))
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print(f"REAL TFLOPS {N * N * N * 2 / min(ets) * 1e-12:.2f}")
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GlobalCounters.reset()
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with Context(DEBUG=2):
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tc = (a @ b).realize()
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with Context(DEBUG=0):
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err = (hc - tc).square().mean().item()
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print(f"mean squared error {err}")
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if err > 1e-06:
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raise RuntimeError("matmul is wrong!")
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if getenv("VERIFY", 1):
|
||||
GlobalCounters.reset()
|
||||
with Context(DEBUG=2):
|
||||
tc = (a @ b).realize()
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||||
with Context(DEBUG=0):
|
||||
err = (hc - tc).square().mean().item()
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||||
print(f"mean squared error {err}")
|
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if err > 1e-06:
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raise RuntimeError("matmul is wrong!")
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||||
|
||||
if __name__ == "__main__":
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test_matmul(hand_spec_kernel3(), N=N)
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||||
@@ -1,8 +1,10 @@
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||||
import pathlib
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import os, pathlib
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||||
|
||||
# TODO: there is a timing bug without this
|
||||
os.environ["AMD_AQL"] = "1"
|
||||
|
||||
from tinygrad.device import Device
|
||||
from tinygrad.runtime.ops_amd import AMDProgram, HIPCompiler
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||||
import time
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||||
import os
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|
||||
NUM_WORKGROUPS = 96
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WAVE_SIZE = 32
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@@ -44,9 +46,9 @@ if __name__=="__main__":
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raise RuntimeError("Error while initiating AMD device")
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|
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COMPILER = HIPCompiler(DEV.arch)
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if DEV.arch in {'gfx1100', 'gfx1103'}:
|
||||
if DEV.arch == 'gfx1103':
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NUM_WORKGROUPS = 8
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||||
if DEV.arch in {'gfx1100', 'gfx1103', 'gfx1151'}:
|
||||
if DEV.arch == 'gfx1103': NUM_WORKGROUPS = 8
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||||
if DEV.arch == 'gfx1151': NUM_WORKGROUPS = 40
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||||
launchBenchmark("v_wmma_bf16_16x16x16_bf16", (7,8,15))
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launchBenchmark("v_wmma_f16_16x16x16_f16", (7,8,15))
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launchBenchmark("v_wmma_f32_16x16x16_bf16", (7,8,15))
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@@ -64,14 +64,17 @@ nvcmds = {getattr(nv_gpu, x):(x, getattr(nv_gpu, "struct_"+x+"_PARAMS", getattr(
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x.startswith("NV") and x[6:].startswith("_CTRL_") and isinstance(getattr(nv_gpu, x), int)}
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||||
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||||
def get_classes():
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hdrpy = (pathlib.Path(__file__).parent.parent.parent / "tinygrad/runtime/autogen/nv_570.py").read_text()
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||||
clss = re.search(r'NV01_ROOT.*?NV_SEMAPHORE_SURFACE = \(0x000000da\) # macro', hdrpy, re.DOTALL).group()
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||||
pattern = r'([0-9a-zA-Z_]*) = +\((0x[0-9a-fA-F]+)\)'
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||||
matches = re.findall(pattern, clss, re.MULTILINE)
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||||
return {int(num, base=16):name for name, num in matches}
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||||
res = {}
|
||||
known_classes = {"NV01_DEVICE_0", "NV01_ROOT", "NV1_MEMORY_SYSTEM", "NV01_MEMORY_VIRTUAL", "NV1_MEMORY_USER", "NV50_MEMORY_VIRTUAL", "NV_FERMI_VASPACE_A",
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||||
"NV20_SUBDEVICE_0"}
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||||
for nm,val in nv_gpu.__dict__.items():
|
||||
if not isinstance(val, int): continue
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||||
if 0x3000 < val < 0xffff: res[val] = nm
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||||
if nm in known_classes: res[val] = nm
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||||
return res
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||||
nvclasses = get_classes()
|
||||
nvuvms = {getattr(nv_gpu, x):x for x in dir(nv_gpu) if x.startswith("UVM_") and nv_gpu.__dict__.get(x+"_PARAMS")}
|
||||
nvqcmds = {int(getattr(nv_gpu, x)):x for x in dir(nv_gpu) if x[:7] in {"NVC6C0_", "NVC56F_", "NVC6B5_"} and isinstance(getattr(nv_gpu, x), int)}
|
||||
nvqcmds = {int(getattr(nv_gpu, x)):x for x in dir(nv_gpu) if x[:7] in {"NVC9B0_", "NVC6C0_", "NVC56F_", "NVC6B5_"} and isinstance(getattr(nv_gpu, x), int)}
|
||||
|
||||
global_ioctl_id = 0
|
||||
gpus_user_modes = []
|
||||
|
||||
@@ -0,0 +1,131 @@
|
||||
import os
|
||||
os.environ["PYTHONPATH"] = "."
|
||||
os.environ["SQTT"] = "1"
|
||||
if "DEV" not in os.environ: os.environ["DEV"] = "AMD"
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||||
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, ProfileDeviceEvent
|
||||
|
||||
from extra.sqtt.attempt_sqtt_parse import parse_sqtt_print_packets
|
||||
|
||||
# TODO: should really check for AM driver / USB
|
||||
if not OSX:
|
||||
def set_power(x): system(f"sudo /opt/rocm/bin/amd-smi set -l {x}")
|
||||
@atexit.register
|
||||
def reset_power(): set_power("auto")
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set_power("stable_std")
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dev = Device["AMD"]
|
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|
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@contextlib.contextmanager
|
||||
def save_sqtt():
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# clear the old traces
|
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dev.profile_events.clear()
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sqtt:dict[str, list[WaveExec]] = {}
|
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yield sqtt
|
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events = dev.profile_events+[ProfileDeviceEvent("AMD", props=dev.device_props())]
|
||||
|
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rctx = decode(events)
|
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assert len(rctx.inst_execs) > 0, "empty sqtt output"
|
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sqtt.update(rctx.inst_execs)
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||||
|
||||
for e in events:
|
||||
if isinstance(e, ProfileSQTTEvent):
|
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print(replace(e, blob=b''))
|
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if e.se == 0:
|
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parse_sqtt_print_packets(e.blob)
|
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template = """.text
|
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.globl matmul
|
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.p2align 8
|
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.type matmul,@function
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matmul:
|
||||
INSTRUCTION
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s_endpgm
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||||
|
||||
.rodata
|
||||
.p2align 6
|
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.amdhsa_kernel matmul
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.amdhsa_user_sgpr_kernarg_segment_ptr 1
|
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.amdhsa_next_free_vgpr .amdgcn.next_free_vgpr
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.amdhsa_next_free_sgpr .amdgcn.next_free_sgpr
|
||||
.amdhsa_wavefront_size32 1
|
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.end_amdhsa_kernel
|
||||
|
||||
.amdgpu_metadata
|
||||
---
|
||||
amdhsa.version:
|
||||
- 1
|
||||
- 0
|
||||
amdhsa.kernels:
|
||||
- .name: matmul
|
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.symbol: matmul.kd
|
||||
.group_segment_fixed_size: 0
|
||||
.private_segment_fixed_size: 0
|
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.wavefront_size: 32
|
||||
.sgpr_count: 8
|
||||
.vgpr_count: 32
|
||||
.max_flat_workgroup_size: 1024
|
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.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
|
||||
"""
|
||||
|
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def run_asm(src):
|
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NUM_WORKGROUPS = 1
|
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WAVE_SIZE = 32
|
||||
NUM_WAVES = 1
|
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t = Tensor.empty(0x1000).realize()
|
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buf = t.uop.buffer.ensure_allocated()
|
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lib = dev.compiler.compile(template.replace("INSTRUCTION", '\n'.join(src)))
|
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dev.compiler.disassemble(lib)
|
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fxn = AMDProgram(dev, "matmul", lib)
|
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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:
|
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#(Tensor.empty(16,16) @ Tensor.empty(16,16)).elu().realize()
|
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Tensor.empty(1).elu().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)
|
||||
@@ -0,0 +1,543 @@
|
||||
import pickle
|
||||
from tinygrad.helpers import getenv
|
||||
from extra.sqtt.roc import decode, ProfileSQTTEvent
|
||||
|
||||
# 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
|
||||
|
||||
OPCODE_NAMES = {
|
||||
# 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_VALUINST_SHIFT (but others must be enabled for it to show)
|
||||
0x01: "VALUINST",
|
||||
# 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_IMMEDIATE_SHIFT
|
||||
0x04: "IMMEDIATE_4",
|
||||
0x05: "IMMEDIATE_5",
|
||||
# some gated by SQ_TT_TOKEN_EXCLUDE_REG_SHIFT, some always there
|
||||
0x14: "REG",
|
||||
# gated by SQ_TT_TOKEN_EXCLUDE_EVENT_SHIFT
|
||||
0x12: "EVENT",
|
||||
# gated by SQ_TT_TOKEN_EXCLUDE_INST_SHIFT
|
||||
0x18: "INST",
|
||||
# gated by SQ_TT_TOKEN_EXCLUDE_UTILCTR_SHIFT
|
||||
0x19: "UTILCTR",
|
||||
|
||||
# ------------------------------------------------------------------------
|
||||
# 0x07–0x0F: pure timestamp-ish deltas
|
||||
# ------------------------------------------------------------------------
|
||||
0x07: "TS_DELTA_S8_W3", # shift=8, width=3 (small delta)
|
||||
0x0A: "TS_DELTA_S5_W2_A", # shift=5, width=2
|
||||
0x0B: "TS_DELTA_S5_W3_A", # shift=5, width=3
|
||||
0x0C: "TS_DELTA_S5_W3_B", # shift=5, width=3 (different consumer)
|
||||
0x0D: "TS_DELTA_S5_W3_C", # shift=5, width=3
|
||||
0x0E: "TS_DELTA_S7_W2", # shift=7, width=2
|
||||
0x0F: "TS_DELTA_SHORT_PLUS4", # short delta; ROCm adds +4 before accumulate
|
||||
|
||||
# ------------------------------------------------------------------------
|
||||
# 0x10–0x19: timestamps, layout headers, events, perf
|
||||
# ------------------------------------------------------------------------
|
||||
0x10: "PSEUDO_NEED_MORE_BITS", # not a real packet; decoder refill hint
|
||||
|
||||
0x11: "TS_WAVE_STATE_SAMPLE", # wave stall/termination sample (byte at +10)
|
||||
0x13: "EVT_SMALL_GENERIC", # same structural family as 0x08/0x12/0x19
|
||||
|
||||
0x15: "PERFCOUNTER_SNAPSHOT", # small delta + 50-ish bits of snapshot
|
||||
0x16: "TS_DELTA36_OR_MARK", # 36-bit long delta or 36-bit marker
|
||||
0x17: "LAYOUT_MODE_HEADER", # layout/mode/group + selectors A/B
|
||||
}
|
||||
|
||||
# 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->token table ----------
|
||||
|
||||
STATE_TO_TOKEN: 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,
|
||||
])
|
||||
|
||||
|
||||
# ---------- 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,
|
||||
]
|
||||
assert len(NIBBLE_BUDGET) == 32
|
||||
|
||||
|
||||
# ---------- 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
|
||||
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 decode_packet_fields(opcode: int, reg: int, delta: 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 ---------------------------------
|
||||
nb_bits = NIBBLE_BUDGET[opcode & 0x1F]
|
||||
if nb_bits <= 0 or nb_bits >= 64:
|
||||
pkt = reg & ((1 << 64) - 1)
|
||||
else:
|
||||
pkt = reg & ((1 << nb_bits) - 1)
|
||||
|
||||
fields: list[str] = []
|
||||
|
||||
shift, width = DELTA_MAP_DEFAULT.get(opcode, (0, 0))
|
||||
if width:
|
||||
field_mask = (1 << width) - 1
|
||||
shaped_field = (pkt >> shift) & field_mask
|
||||
else:
|
||||
field_mask = 0
|
||||
shaped_field = 0
|
||||
|
||||
# =====================================================================
|
||||
# 1. Timestamp-centric opcodes (actually drive 'time')
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x0F: # TS_DELTA_SHORT_PLUS4
|
||||
# In the caller, delta already has +4 applied.
|
||||
raw_delta = shaped_field
|
||||
fields.append(f"raw_delta={raw_delta}")
|
||||
fields.append(f"ts_short_plus4={delta}")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode == 0x11: # TS_WAVE_STATE_SAMPLE
|
||||
# DELTA_MAP_DEFAULT: shift=7, width=9 -> small delta.
|
||||
raw_delta = shaped_field
|
||||
coarse = (pkt >> (shift + width)) & 0xFF # matches byte at +10 in C
|
||||
fields.append(f"raw_delta={raw_delta}")
|
||||
if coarse:
|
||||
fields.append(f"coarse_state=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")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode == 0x16: # TS_DELTA36_OR_MARK
|
||||
# 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"
|
||||
val36 = (pkt >> 12) & ((1 << 36) - 1)
|
||||
fields.append(f"mode={mode}")
|
||||
if mode != "delta":
|
||||
fields.append(f"val36=0x{val36:x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# For 0x07, 0x0A–0x0E, we know they drive time (via DELTA_MAP_DEFAULT),
|
||||
# but we don't see any other fields used in the decomp.
|
||||
if opcode in (0x07, 0x0A, 0x0B, 0x0C, 0x0D, 0x0E):
|
||||
if width:
|
||||
raw_delta = shaped_field
|
||||
leftover = pkt & ~(field_mask << shift)
|
||||
fields.append(f"raw_delta={raw_delta}")
|
||||
if leftover:
|
||||
fields.append(f"payload=0x{leftover:x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 2. Small "meta + tiny delta" packets (0x01–0x06)
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x01: # META_ID12_TS_SMALL
|
||||
id12 = pkt & 0xFFF
|
||||
fields.append(f"id12=0x{id12:03x}")
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode == 0x02: # META_FLAG8_TS_SMALL
|
||||
flag8 = pkt & 0xFF
|
||||
fields.append(f"flag8=0x{flag8:02x}")
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode == 0x03: # META_SUBEVENT8_TS_SMALL
|
||||
sub8 = pkt & 0xFF
|
||||
fields.append(f"subevent8=0x{sub8:02x}")
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode == 0x04: # META_BASE_INDEX12_TS
|
||||
idx12 = pkt & 0xFFF
|
||||
fields.append(f"base_index12=0x{idx12:03x}")
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
return ", ".join(fields)
|
||||
|
||||
if opcode in (0x05, 0x06): # META_DESC24_TS_A/B
|
||||
desc24 = pkt & 0xFFFFFF
|
||||
fields.append(f"desc24=0x{desc24:06x}")
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 3. Opcode 0x14: exec/config record (+ COR marker)
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x14: # INST_EXEC_OR_CFG
|
||||
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("cfg_target=local_168[slot].lo")
|
||||
elif subop == 0x000D:
|
||||
fields.append("cfg_target=local_168[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'")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 4. Opcode 0x17: layout / mode header
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x17: # LAYOUT_MODE_HEADER
|
||||
# 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
|
||||
mode = (pkt >> 13) & 0x3
|
||||
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"mode={mode}")
|
||||
fields.append(f"sel_a={sel_a}")
|
||||
fields.append(f"sel_b={sel_b}")
|
||||
if layout == 4:
|
||||
fields.append(f"layout4_flag={flag4}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 5. Opcode 0x09: state / route config record
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x09: # PERF_ROUTE_CONFIG
|
||||
# From case 9 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) & 0x1
|
||||
cls2 = (pkt >> 8) & 0x3
|
||||
slot4 = (pkt >> 10) & 0xF
|
||||
idx_lo = (pkt >> 13) & 0x1F
|
||||
idx_hi = (pkt >> 15) & 0x1F
|
||||
id7 = (pkt >> 0x19) & 0x7F
|
||||
|
||||
fields.append(f"flag7={flag7}")
|
||||
fields.append(f"cls2={cls2}")
|
||||
fields.append(f"slot4=0x{slot4:x}")
|
||||
fields.append(f"idx_lo5=0x{idx_lo:x}")
|
||||
fields.append(f"idx_hi5=0x{idx_hi:x}")
|
||||
fields.append(f"id7=0x{id7:x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 6. Opcode 0x18: perf/event selector (FUN_0010aba0)
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x18: # PERF_EVENT_SELECT
|
||||
# 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
|
||||
low3 = pkt & 0x7
|
||||
grp3_a = (pkt >> 3) & 0x7
|
||||
grp3_b = (pkt >> 4) & 0x7
|
||||
flag_b6 = (pkt >> 6) & 0x1
|
||||
flag_b7 = (pkt >> 7) & 0x1
|
||||
idx5_a = (pkt >> 7) & 0x1F
|
||||
idx5_b = (pkt >> 8) & 0x1F
|
||||
hi8 = (pkt >> 12) & 0xFF
|
||||
hi7 = (pkt >> 13) & 0x7F
|
||||
|
||||
fields.append(f"low3=0x{low3:x}")
|
||||
fields.append(f"grp3_a=0x{grp3_a:x}")
|
||||
fields.append(f"grp3_b=0x{grp3_b:x}")
|
||||
fields.append(f"flag_b6={flag_b6}")
|
||||
fields.append(f"flag_b7={flag_b7}")
|
||||
fields.append(f"idx5_a=0x{idx5_a:x}")
|
||||
fields.append(f"idx5_b=0x{idx5_b:x}")
|
||||
fields.append(f"hi8=0x{hi8:02x}")
|
||||
fields.append(f"hi7=0x{hi7:02x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 7. Opcode 0x15: perfcounter snapshot
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x15: # PERFCOUNTER_SNAPSHOT
|
||||
# NIBBLE_BUDGET gives full 64 bits here.
|
||||
# DELTA_MAP_DEFAULT: shift=7, width=3 → tiny delta field.
|
||||
raw_delta = shaped_field if width else 0
|
||||
# low bits below the delta field
|
||||
snap_low = pkt & ((1 << shift) - 1) if shift else 0
|
||||
# everything above delta field
|
||||
snap_hi = pkt >> (shift + width) if width else (pkt >> shift)
|
||||
|
||||
fields.append(f"raw_delta={raw_delta}")
|
||||
fields.append(f"snap_low_s{shift}=0x{snap_low:x}")
|
||||
fields.append(f"snap_hi=0x{snap_hi:x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 8. Small event-ish packets (0x08 / 0x12 / 0x13 / 0x19)
|
||||
# =====================================================================
|
||||
|
||||
if opcode in (0x08, 0x12, 0x13, 0x19):
|
||||
# These are all "small event / metric" style tokens. The exact semantics
|
||||
# depend on layout (0x17) and accumulated state (local_500 etc), so we
|
||||
# expose:
|
||||
# - low 8 bits as kind byte
|
||||
# - rest as opaque payload.
|
||||
kind = pkt & 0xFF
|
||||
payload = pkt >> 8
|
||||
fields.append(f"kind_byte=0x{kind:02x}")
|
||||
if payload:
|
||||
fields.append(f"payload=0x{payload:x}")
|
||||
return ", ".join(fields)
|
||||
|
||||
# =====================================================================
|
||||
# 9. Pseudo opcode 0x10: never a "real" packet
|
||||
# =====================================================================
|
||||
|
||||
if opcode == 0x10: # PSEUDO_NEED_MORE_BITS
|
||||
# The main loop never prints these; they're just a control token.
|
||||
return ""
|
||||
|
||||
# =====================================================================
|
||||
# 10. Generic fallback: expose the DELTA_MAP_DEFAULT field + leftover
|
||||
# =====================================================================
|
||||
|
||||
if width:
|
||||
fields.append(f"field_s{shift}_w{width}={shaped_field}")
|
||||
leftover = pkt & ~(field_mask << shift)
|
||||
if leftover:
|
||||
fields.append(f"payload=0x{leftover:x}")
|
||||
|
||||
return ", ".join(fields)
|
||||
|
||||
# 0xb is time something
|
||||
# 0xd is time something
|
||||
# 0xf is small time advance
|
||||
# 0x11 is time advance
|
||||
# 0x16 is big time advance + markers
|
||||
# 0x14 is REG
|
||||
DEFAULT_FILTER = (0xb, 0xd, 0xf, 0x11, 0x16, 0x14) if getenv("FILTER", 1) else None
|
||||
|
||||
def parse_sqtt_print_packets(data: bytes, max_tokens: int = 100000, filter=DEFAULT_FILTER) -> 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
|
||||
reg = 0 # shift register
|
||||
offset = 0 # bit offset, in steps of 4 (one nibble)
|
||||
nib_budget = 0x40
|
||||
flags = 0
|
||||
token_index = 0
|
||||
|
||||
while (offset >> 3) < n and token_index < max_tokens:
|
||||
# Remember where we started refilling for this step (bit offset),
|
||||
# but the *logical* start of the current packet is last_real_offset.
|
||||
refill_start = offset
|
||||
|
||||
# 1) Fill register with nibbles according to nib_budget
|
||||
if nib_budget != 0:
|
||||
target = refill_start + 4 + ((nib_budget - 1) & ~3)
|
||||
cur = refill_start
|
||||
while cur != target and (cur >> 3) < n:
|
||||
byte_index = cur >> 3
|
||||
byte = data[byte_index]
|
||||
shift = 4 if (cur & 4) else 0 # low then high nibble
|
||||
nib = (byte >> shift) & 0xF
|
||||
reg = ((reg >> 4) | (nib << 60)) & ((1 << 64) - 1)
|
||||
cur += 4
|
||||
offset = cur
|
||||
|
||||
# 2) Decode token from low 8 bits
|
||||
state = reg & 0xFF
|
||||
opcode = STATE_TO_TOKEN[state]
|
||||
|
||||
# 3) Handle pseudo-token 0x10: need more bits, don't print. Looks like a NOP.
|
||||
if opcode == 0x10:
|
||||
# "need more bits" pseudo-token: adjust nibble budget and continue
|
||||
nib_budget = 4
|
||||
if (offset >> 3) >= n:
|
||||
break
|
||||
# Do NOT count this as a real packet; do not update last_real_offset.
|
||||
continue
|
||||
|
||||
# 4) Set next nibble budget
|
||||
nb_index = opcode & 0x1F
|
||||
nib_budget = NIBBLE_BUDGET[nb_index]
|
||||
time_before = time
|
||||
note = ""
|
||||
# 5) Special opcode 0x16 (timestamp / marker)
|
||||
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
|
||||
delta = (reg >> 12) & ((1 << 36) - 1)
|
||||
time += delta
|
||||
else:
|
||||
# marker / other modes: no time advance
|
||||
if (reg & 0x100) == 0:
|
||||
# real marker: bit9=1, bit8=0, non-zero payload
|
||||
# "other" 0x16 variants, ignored for timing
|
||||
delta = 0
|
||||
else:
|
||||
# 6) Generic opcode (including 0x0F)
|
||||
shift, width = DELTA_MAP_DEFAULT[opcode]
|
||||
mask = (1 << width) - 1
|
||||
delta = (reg >> shift) & mask
|
||||
|
||||
# TODO: add more opcode parsers here that add notes to other opcodes
|
||||
if opcode == 0x0F:
|
||||
delta_with_fix = delta + 4
|
||||
time += delta_with_fix
|
||||
delta = delta_with_fix
|
||||
else:
|
||||
time += delta
|
||||
|
||||
# Append extra decoded fields into the note string
|
||||
note = decode_packet_fields(opcode, reg, delta)
|
||||
|
||||
if filter is None or opcode not in filter:
|
||||
my_reg = reg
|
||||
my_reg &= (1 << nib_budget) - 1
|
||||
print(
|
||||
f"{token_index:4d} "
|
||||
f"off={offset//4:5d} "
|
||||
f"op=0x{opcode:02x} "
|
||||
f"{OPCODE_NAMES[opcode]:24s} "
|
||||
f" time={time_before:8d}+{delta:8d} "
|
||||
f"{my_reg:16X} "
|
||||
f"{note}"
|
||||
)
|
||||
|
||||
token_index += 1
|
||||
|
||||
# Optional summary at the end
|
||||
print(f"# done: tokens={token_index}, final_time={time}, flags=0x{flags:02x}")
|
||||
|
||||
def parse(fn:str):
|
||||
dat = pickle.load(open(fn, "rb"))
|
||||
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__":
|
||||
#dat_sqtt = parse("extra/sqtt/examples/profile_empty_run_0.pkl")
|
||||
#dat_sqtt = parse("extra/sqtt/examples/profile_plus_run_0.pkl")
|
||||
dat_sqtt = parse("extra/sqtt/examples/profile_gemm_run_0.pkl")
|
||||
blob_0 = dat_sqtt[0].blob
|
||||
parse_sqtt_print_packets(blob_0[8:])
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
+15
-10
@@ -1,4 +1,4 @@
|
||||
import ctypes, pathlib, argparse, pickle, re, functools, dataclasses, itertools
|
||||
import ctypes, pathlib, argparse, pickle, re, functools, dataclasses, itertools, threading
|
||||
from tinygrad.helpers import temp, unwrap, DEBUG
|
||||
from tinygrad.device import ProfileEvent, ProfileDeviceEvent, ProfileProgramEvent
|
||||
from tinygrad.runtime.ops_amd import ProfileSQTTEvent, ProfilePMCEvent
|
||||
@@ -41,6 +41,7 @@ class WaveExec:
|
||||
wave_id:int
|
||||
cu:int
|
||||
simd:int
|
||||
se:int
|
||||
begin_time:int
|
||||
end_time:int
|
||||
insts:list[InstExec]
|
||||
@@ -63,10 +64,10 @@ class _ROCParseCtx:
|
||||
self.active_blob = (ctypes.c_ubyte * len(x.blob)).from_buffer_copy(x.blob) if x is not None else None
|
||||
return self.active_blob
|
||||
|
||||
def on_occupancy_ev(self, ev):
|
||||
def on_occupancy_ev(self, ev:rocprof.rocprofiler_thread_trace_decoder_occupancy_t):
|
||||
if DEBUG >= 5: print("OCC", ev.time, self.active_se, ev.cu, ev.simd, ev.wave_id, ev.start)
|
||||
|
||||
def on_wave_ev(self, ev):
|
||||
def on_wave_ev(self, ev:rocprof.rocprofiler_thread_trace_decoder_wave_t):
|
||||
if DEBUG >= 5: print("WAVE", ev.wave_id, self.active_se, ev.cu, ev.simd, ev.contexts, ev.begin_time, ev.end_time)
|
||||
|
||||
inst_execs:list[InstExec] = []
|
||||
@@ -75,9 +76,11 @@ class _ROCParseCtx:
|
||||
inst_typ = rocprof.enum_rocprofiler_thread_trace_decoder_inst_category_t.get(inst_ev.category)
|
||||
inst_disasm = self.disasms[(unwrap(self.active_kern), unwrap(inst_ev.pc.address))][0]
|
||||
inst_execs.append(InstExec(inst_typ, inst_disasm, inst_ev.stall, inst_ev.duration, inst_ev.time))
|
||||
if DEBUG >= 8: print(inst_execs[-1])
|
||||
|
||||
if ev.instructions_size > 0:
|
||||
self.inst_execs.setdefault(unwrap(self.active_kern), []).append(WaveExec(ev.wave_id, ev.cu, ev.simd, ev.begin_time, ev.end_time, inst_execs))
|
||||
self.inst_execs.setdefault(unwrap(self.active_kern), []).append(WaveExec(ev.wave_id, ev.cu, ev.simd, unwrap(self.active_se), ev.begin_time,
|
||||
ev.end_time, inst_execs))
|
||||
|
||||
def decode(profile:list[ProfileEvent]) -> _ROCParseCtx:
|
||||
dev_events:dict[str, ProfileDeviceEvent] = {}
|
||||
@@ -91,14 +94,14 @@ def decode(profile:list[ProfileEvent]) -> _ROCParseCtx:
|
||||
ROCParseCtx = _ROCParseCtx(dev_events, sqtt_events, prog_events)
|
||||
|
||||
@rocprof.rocprof_trace_decoder_se_data_callback_t
|
||||
def copy_cb(buf, buf_size, data_ptr):
|
||||
def copy_cb(buf, buf_size, _):
|
||||
if (prof_info:=ROCParseCtx.next_sqtt()) is None: return 0
|
||||
buf[0] = ctypes.cast(prof_info, ctypes.POINTER(ctypes.c_ubyte))
|
||||
buf_size[0] = len(prof_info)
|
||||
return len(prof_info)
|
||||
|
||||
@rocprof.rocprof_trace_decoder_trace_callback_t
|
||||
def trace_cb(record_type, events_ptr, n, data_ptr):
|
||||
def trace_cb(record_type, events_ptr, n, _):
|
||||
match record_type:
|
||||
case rocprof.ROCPROFILER_THREAD_TRACE_DECODER_RECORD_OCCUPANCY:
|
||||
for ev in (rocprof.rocprofiler_thread_trace_decoder_occupancy_t * n).from_address(events_ptr): ROCParseCtx.on_occupancy_ev(ev)
|
||||
@@ -109,7 +112,7 @@ def decode(profile:list[ProfileEvent]) -> _ROCParseCtx:
|
||||
return rocprof.ROCPROFILER_THREAD_TRACE_DECODER_STATUS_SUCCESS
|
||||
|
||||
@rocprof.rocprof_trace_decoder_isa_callback_t
|
||||
def isa_cb(instr_ptr, mem_size_ptr, size_ptr, pc, data_ptr):
|
||||
def isa_cb(instr_ptr, mem_size_ptr, size_ptr, pc, _):
|
||||
instr, mem_size_ptr[0] = ROCParseCtx.disasms[(unwrap(ROCParseCtx.active_kern), pc.address)]
|
||||
|
||||
# this is the number of bytes to next instruction, set to 0 for end_pgm
|
||||
@@ -123,9 +126,11 @@ def decode(profile:list[ProfileEvent]) -> _ROCParseCtx:
|
||||
|
||||
return rocprof.ROCPROFILER_THREAD_TRACE_DECODER_STATUS_SUCCESS
|
||||
|
||||
try:
|
||||
rocprof.rocprof_trace_decoder_parse_data(copy_cb, trace_cb, isa_cb, None)
|
||||
except AttributeError as e: raise RuntimeError("Failed to find rocprof-trace-decoder. Run sudo ./extra/sqtt/install_sqtt_decoder.py to install") from e
|
||||
def worker():
|
||||
try: rocprof.rocprof_trace_decoder_parse_data(copy_cb, trace_cb, isa_cb, None)
|
||||
except AttributeError as e: raise RuntimeError("Failed to find rocprof-trace-decoder. Run sudo ./extra/sqtt/install_sqtt_decoder.py to install") from e
|
||||
(t:=threading.Thread(target=worker, daemon=True)).start()
|
||||
t.join()
|
||||
return ROCParseCtx
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
+41
-20
@@ -7,11 +7,9 @@ os.environ["AMD_LLVM"] = "0"
|
||||
|
||||
import unittest
|
||||
import sys, contextlib
|
||||
from tinygrad import Tensor
|
||||
from tinygrad.dtype import dtypes
|
||||
from tinygrad.renderer import ProgramSpec
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo, AddrSpace
|
||||
from tinygrad.engine.realize import CompiledRunner
|
||||
from tinygrad import Tensor, dtypes
|
||||
from tinygrad.helpers import getenv
|
||||
from tinygrad.uop.ops import UOp, Ops, KernelInfo
|
||||
from tinygrad.device import Device, ProfileDeviceEvent
|
||||
|
||||
from extra.sqtt.roc import decode, WaveExec
|
||||
@@ -39,10 +37,10 @@ def save_sqtt():
|
||||
sqtt:dict[str, list[WaveExec]] = {}
|
||||
yield sqtt
|
||||
# decode sqtt
|
||||
if os.environ["DEV"] == "AMD":
|
||||
rctx = decode(dev.profile_events+[ProfileDeviceEvent("AMD", props=dev.device_props())])
|
||||
assert len(rctx.inst_execs) > 0, "empty sqtt output"
|
||||
sqtt.update(rctx.inst_execs)
|
||||
if os.environ["DEV"] != "AMD": return
|
||||
rctx = decode(dev.profile_events+[ProfileDeviceEvent("AMD", props=dev.device_props())])
|
||||
assert len(rctx.inst_execs) > 0, "empty sqtt output"
|
||||
sqtt.update(rctx.inst_execs)
|
||||
|
||||
class TestTiming(unittest.TestCase):
|
||||
def test_v_add(self):
|
||||
@@ -75,7 +73,6 @@ class TestTiming(unittest.TestCase):
|
||||
inp = Tensor([-2.0]).realize()
|
||||
with save_sqtt() as sqtt:
|
||||
Tensor.custom_kernel(out, inp, fxn=custom_vrcp)[0].realize()
|
||||
|
||||
wave = list(sqtt.values())[0][0]
|
||||
for i in range(len(wave.insts)):
|
||||
if wave.insts[i].inst.startswith("global_store"):
|
||||
@@ -84,13 +81,17 @@ class TestTiming(unittest.TestCase):
|
||||
|
||||
def test_wmma(self):
|
||||
with save_sqtt() as sqtt:
|
||||
asm_kernel([
|
||||
"v_wmma_f32_16x16x16_f16 v[16:23], v[0:7], v[8:15], v[16:23]",
|
||||
"v_add_f32_e32 v0 v16 v0",
|
||||
], l=32*4).realize()
|
||||
assert len(sqtt) == 2, f"expected two waves, got {len(sqtt)} {list(sqtt.keys())}"
|
||||
wmma = list(sqtt.values())[0][0]
|
||||
self.assertGreater(wmma.dur, 1) # rgp says 32 clocks
|
||||
for tc in dev.renderer.get_tensor_cores(dev.arch):
|
||||
M, K, N = tc.dims
|
||||
s = 32
|
||||
a = Tensor.empty(M*s, K*s, dtype=tc.dtype_in)@Tensor.empty(K*s, N*s, dtype=tc.dtype_in)
|
||||
a.realize()
|
||||
print(a)
|
||||
for p,waves in sqtt.items():
|
||||
for e in waves[0].insts:
|
||||
if (e.inst.startswith("v_wmma")):
|
||||
instruction = e.inst.split(" ")[0]
|
||||
print(f"{instruction:<29} : {e.dur} cycles")
|
||||
|
||||
def test_sleep(self):
|
||||
n = 1
|
||||
@@ -98,15 +99,35 @@ class TestTiming(unittest.TestCase):
|
||||
assert data0.dtype.base == dtypes.ulong
|
||||
op = custom("unsigned long long t0 = __builtin_readcyclecounter();")
|
||||
op = custom(f"__builtin_amdgcn_s_sleep({n});", op)
|
||||
op = custom(f"unsigned long long t1 = __builtin_readcyclecounter();", op)
|
||||
op = custom("unsigned long long t1 = __builtin_readcyclecounter();", op)
|
||||
op = custom(f"data0_{data0.size}[0] = t1 - t0;", op)
|
||||
return UOp.sink(data0, op, arg=KernelInfo(name=f"sleep_{n}"))
|
||||
diff_hw_reg = Tensor.empty(1, dtype=dtypes.ulong)
|
||||
diff_hw_reg = Tensor.custom_kernel(diff_hw_reg, fxn=sleep_kernel)[0]
|
||||
with save_sqtt() as sqtt:
|
||||
diff_hw_reg.realize()
|
||||
diff_sqtt = list(sqtt.values())[0][2]
|
||||
self.assertEqual(diff_sqtt.dur, diff_hw_reg.item()-1) # 1 cycle for reading the counter register
|
||||
sleep = next((e for e in sqtt[f"sleep_{n}"][0].insts if e.inst.startswith("s_sleep")))
|
||||
# cycles = sleep dur + overhead of storing hi/lo REG_SHADER_CYCLES
|
||||
self.assertGreaterEqual(diff_hw_reg.item(), sleep.dur)
|
||||
|
||||
def test_nop(self):
|
||||
with save_sqtt() as sqtt:
|
||||
asm_kernel(["s_nop 1"]*10).realize()
|
||||
wave = list(sqtt.values())[0][0]
|
||||
for e in wave.insts:
|
||||
print(f"{e.inst} {e.dur=} {e.stall=}")
|
||||
|
||||
def test_wave_sched(self):
|
||||
num_waves = getenv("NUM_WAVES", 16)
|
||||
num_wgps = getenv("NUM_WGPS", 2)
|
||||
num_vgpr = getenv("NUM_VGPR", 256)
|
||||
with save_sqtt() as sqtt:
|
||||
# 1 cycle decode, no stall
|
||||
asm_kernel([f"v_mov_b32_e32 v{i} {i}" for i in range(num_vgpr)], l=32*num_waves, g=num_wgps).realize()
|
||||
waves = list(sqtt.values())[0]
|
||||
print(len(waves), "waves decoded")
|
||||
for w in waves:
|
||||
print(f"{w.wave_id:<2} {w.simd=} {w.cu=} {w.se=} @ clk {w.begin_time}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
||||
@@ -1 +1,6 @@
|
||||
WARP_THREADS = 32
|
||||
from tinygrad.device import Device
|
||||
|
||||
if Device.DEFAULT == "AMD":
|
||||
WARP_THREADS = 64
|
||||
else:
|
||||
WARP_THREADS = 32
|
||||
|
||||
@@ -56,7 +56,7 @@ class Group:
|
||||
self.ker.push_store(dst_store, dst)
|
||||
return dst.after(dst_store).reshape(dst.shape)
|
||||
|
||||
def mma_AB(self, c:UOp|RT, a:UOp|RT, b:UOp|RT, after=True):
|
||||
def mma_AB(self, c:UOp|RT, a:UOp|RT, b:UOp|RT):
|
||||
c, a, b = cast(UOp, c), cast(UOp, a), cast(UOp, b)
|
||||
assert self.warps == 1
|
||||
|
||||
@@ -77,9 +77,9 @@ class Group:
|
||||
c_store = UOp.group(*c_i).end(height, width, inner)
|
||||
|
||||
self.ker.push_store(c_store, c)
|
||||
return c.after(c_store).reshape(c.shape) if after else c_store
|
||||
return c.after(c_store).reshape(c.shape)
|
||||
|
||||
def mma_ABt(self, c:UOp|RT, a:UOp|RT, b:UOp|RT, after=True):
|
||||
def mma_ABt(self, c:UOp|RT, a:UOp|RT, b:UOp|RT):
|
||||
c, a, b = cast(UOp, c), cast(UOp, a), cast(UOp, b)
|
||||
assert self.warps == 1
|
||||
|
||||
@@ -100,7 +100,7 @@ class Group:
|
||||
c_store = UOp.group(*c_i).end(height, width, inner)
|
||||
|
||||
self.ker.push_store(c_store, c)
|
||||
return c.after(c_store).reshape(c.shape) if after else c_store
|
||||
return c.after(c_store).reshape(c.shape)
|
||||
|
||||
map_rid = 400
|
||||
def map(self, a:ALL_TILES, op:Callable[[UOp], UOp]|Callable[[UOp, tuple], UOp]):
|
||||
@@ -162,7 +162,7 @@ class Group:
|
||||
|
||||
# ops that can work across multiple warps
|
||||
|
||||
LOAD_INNER = 8
|
||||
LOAD_INNER = 4
|
||||
def load(self, dst:ALL_TILES, src:ALL_TILES, dst_idxs:tuple[UOp|int,...]=(), idxs:tuple[UOp|int,...]=(), axis:int=0, transpose:bool=False):
|
||||
dst, src = cast(UOp, dst), cast(UOp, src)
|
||||
assert isinstance(dst.dtype, PtrDType) and isinstance(src.dtype, PtrDType)
|
||||
@@ -225,7 +225,7 @@ class Group:
|
||||
|
||||
return dst.after(dst_store.barrier()).reshape(dst.shape)
|
||||
|
||||
STORE_INNER = 8
|
||||
STORE_INNER = 4
|
||||
def store(self, dst:ALL_TILES, src:ALL_TILES, idxs:tuple[UOp|int,...]=(), src_idxs:tuple[UOp|int,...]=(), axis:int=0, transpose:bool=False):
|
||||
dst, src = cast(UOp, dst), cast(UOp, src)
|
||||
assert isinstance(dst.dtype, PtrDType) and isinstance(src.dtype, PtrDType)
|
||||
|
||||
@@ -80,7 +80,11 @@ class Kernel(AbstractContextManager):
|
||||
rngs = []
|
||||
while self.range_stack: rngs.append(self.range_stack.pop(0)._rng)
|
||||
|
||||
return self.store_stack.pop()[0]._uop.end(*rngs).sink(arg=KernelInfo(opts_to_apply=())).simplify()
|
||||
last_store = self.store_stack.pop()[0]
|
||||
if hasattr(last_store, '_uop'): uop = last_store._uop
|
||||
else: uop = last_store
|
||||
|
||||
return uop.end(*rngs).sink(arg=KernelInfo(opts_to_apply=())).simplify()
|
||||
|
||||
def endrange(self):
|
||||
last_store = self.store_stack.pop()
|
||||
|
||||
+3
-2
@@ -1,13 +1,14 @@
|
||||
import unittest
|
||||
from tinygrad import Device
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.helpers import getenv, CI
|
||||
from tinygrad.helpers import getenv, CI, OSX
|
||||
|
||||
def multidevice_test(fxn):
|
||||
exclude_devices = getenv("EXCLUDE_DEVICES", "").split(",")
|
||||
def ret(self):
|
||||
for device in Device._devices:
|
||||
if device in ["REMOTE", "DISK", "NPY", "FAKE", "DSP", "NULL"]: continue
|
||||
# broken on OSX USB AMD, why?
|
||||
if device in ["REMOTE", "DISK", "NPY", "FAKE", "DSP", "NULL"] or (OSX and device in ["AMD"]): continue
|
||||
if not CI: print(device)
|
||||
if device in exclude_devices:
|
||||
if not CI: print(f"WARNING: {device} test is excluded")
|
||||
|
||||
+3
-1
@@ -36,7 +36,9 @@ def trunc_log(x):
|
||||
logging.info("\n".join(lines))
|
||||
|
||||
# user config
|
||||
SKIP_PROCESS_REPLAY = (k:="[skip_process_replay]") in os.getenv("COMMIT_MESSAGE", "") or k in os.getenv("PR_TITLE", "")
|
||||
# NOTE: process replay is slow so it's now disabled by default. add [pr] to enable it
|
||||
#SKIP_PROCESS_REPLAY = (k:="[skip_process_replay]") in os.getenv("COMMIT_MESSAGE", "") or k in os.getenv("PR_TITLE", "")
|
||||
SKIP_PROCESS_REPLAY = not ASSERT_DIFF
|
||||
if REF == "master": SKIP_PROCESS_REPLAY = True
|
||||
class ProcessReplayWarning(Warning): pass
|
||||
|
||||
|
||||
@@ -124,6 +124,7 @@ class PM4Executor(AMDQueue):
|
||||
elif mem_data_sel == 3:
|
||||
if mem_event_type == CACHE_FLUSH_AND_INV_TS_EVENT: ptr.cast('Q')[0] = int(time.perf_counter() * 1e8)
|
||||
else: raise RuntimeError(f"Unknown {mem_data_sel=} {mem_event_type=}")
|
||||
elif mem_data_sel == 0: pass # no write
|
||||
else: raise RuntimeError(f"Unknown {mem_data_sel=}")
|
||||
|
||||
def _exec_copy_data(self, n):
|
||||
|
||||
@@ -5,6 +5,8 @@ from tinygrad.helpers import CI, Context, getenv
|
||||
from tinygrad.engine.realize import run_schedule
|
||||
from tinygrad.engine.realize import CompiledRunner, ExecItem, get_program
|
||||
from tinygrad.uop.ops import Ops
|
||||
from tinygrad.renderer import Estimates
|
||||
from tinygrad.renderer.ptx import PTXRenderer
|
||||
|
||||
class TestArange(unittest.TestCase):
|
||||
def _get_flops(self, tensor, desired):
|
||||
@@ -29,6 +31,14 @@ class TestArange(unittest.TestCase):
|
||||
# NOTE: not every backend supports CMPEQ
|
||||
self.assertLessEqual(self._get_flops(Tensor.eye(2560).contiguous(), np.eye(2560)), 2*2560*2560)
|
||||
|
||||
@unittest.skipIf(isinstance(Device[Device.DEFAULT].renderer, PTXRenderer), "PTX indexing is weird")
|
||||
def test_tri_complexity(self):
|
||||
with Context(NOOPT=1):
|
||||
t = Tensor.ones(256, 256).contiguous().realize()
|
||||
sched = t.triu().schedule()
|
||||
p = get_program(sched[-1].ast)
|
||||
self.assertLessEqual(Estimates.from_uops(p.uops).ops, 4 * 256 * 256)
|
||||
|
||||
DSET, DDIM = 2048, 32
|
||||
|
||||
class TestIndexing(unittest.TestCase):
|
||||
|
||||
@@ -102,6 +102,11 @@ def backward_gemm_custom(gradient:UOp, kernel:UOp) -> tuple[UOp, UOp]:
|
||||
# **** tests ****
|
||||
|
||||
class TestCustomKernel(unittest.TestCase):
|
||||
def test_empty(self):
|
||||
a = Tensor.empty(1)
|
||||
a = Tensor.custom_kernel(a, fxn=lambda _: UOp.sink())[0]
|
||||
a.realize()
|
||||
|
||||
def test_simple(self):
|
||||
a = Tensor.ones(16, 16).contiguous()
|
||||
b = Tensor.ones(16, 16).contiguous()
|
||||
|
||||
+108
-33
@@ -1,5 +1,6 @@
|
||||
import unittest
|
||||
from tinygrad import Tensor, UOp
|
||||
import numpy as np
|
||||
from tinygrad import Tensor, UOp, nn
|
||||
from tinygrad.uop.ops import AxisType, Ops
|
||||
|
||||
class TestOuterworldReduce(unittest.TestCase):
|
||||
@@ -50,47 +51,41 @@ class TestOuterRange(unittest.TestCase):
|
||||
# 3 matmuls with outer world range
|
||||
i = UOp.range(3, -100, AxisType.OUTER)
|
||||
vec_i = Tensor(vec.uop.after(i))
|
||||
vi = UOp.variable("i", i.vmin, i.vmax).bind(i)
|
||||
out = Tensor(vec.uop.after(vec_i.uop.store((vec_i.contiguous() @ mats[vi]).uop).end(i)))
|
||||
comp = vec_i.contiguous() @ mats[i]
|
||||
store = vec_i.uop.store(comp.uop).end(i)
|
||||
out = Tensor(vec.uop.after(store))
|
||||
out.realize()
|
||||
|
||||
# TODO: testing allclose
|
||||
assert Tensor.allclose(ref, out, atol=1e-6), f"{ref.numpy()=}, {out.numpy()=}"
|
||||
|
||||
def test_range_grad(self):
|
||||
def range_matmul(vec, mats):
|
||||
# vec: (1, 10), mats: (3, 10, 10)
|
||||
# assume vec, mats already have requires_grad set however you like
|
||||
class TestOuterScan(unittest.TestCase):
|
||||
def _test_scan(self):
|
||||
vec = Tensor.randn(1, 10).realize()
|
||||
mats = Tensor.randn(3, 10, 10).realize()
|
||||
|
||||
i = UOp.range(3, -100, AxisType.OUTER) # loop axis
|
||||
vec_i = Tensor(vec.uop.after(i)) # "loop-carried" vector
|
||||
vi = UOp.variable("i", i.vmin, i.vmax).bind(i)
|
||||
# 3 matmuls in "scan"
|
||||
vec1 = vec @ mats[0]
|
||||
vec2 = vec1 @ mats[1]
|
||||
vec3 = vec2 @ mats[2]
|
||||
ref = Tensor.stack(vec1, vec2, vec3)
|
||||
ref.realize()
|
||||
return vec, mats, ref
|
||||
|
||||
body = (vec_i.contiguous() @ mats[vi]) # matmul using loop index
|
||||
out = Tensor(vec.uop.after(vec_i.uop.store(body.uop).end(i)))
|
||||
return out
|
||||
def test_uop_scan_matmul(self):
|
||||
vec, mats, ref = self._test_scan()
|
||||
|
||||
vec = Tensor.randn(1, 3, requires_grad=True)
|
||||
mats = Tensor.randn(3, 3, 3, requires_grad=True)
|
||||
Tensor.realize(vec, mats)
|
||||
# 3 matmuls with SCAN
|
||||
i = UOp.range(3, -100, AxisType.OUTER)
|
||||
out = Tensor.empty(3, 1, 10)
|
||||
phi = Tensor(i.eq(0).where(vec.uop, out[(i-1).maximum(0)].uop))
|
||||
comp = phi @ mats[i]
|
||||
store = out[i].uop.store(comp.uop).end(i)
|
||||
out = Tensor(out.uop.after(store))
|
||||
out.realize()
|
||||
|
||||
ref = ((vec @ mats[0]) @ mats[1]) @ mats[2]
|
||||
loss = (1.0 - ref).square().mean()
|
||||
loss.backward()
|
||||
Tensor.realize(vec.grad, mats.grad)
|
||||
print(vec.grad.numpy())
|
||||
print(mats.grad.numpy())
|
||||
vec.grad = None
|
||||
mats.grad = None
|
||||
|
||||
out = range_matmul(vec, mats)
|
||||
loss = (1.0 - out).square().mean()
|
||||
loss.backward()
|
||||
Tensor.realize(vec.grad, mats.grad)
|
||||
|
||||
print(vec.grad, mats.grad) # should be non-None and finite
|
||||
print(vec.grad.numpy())
|
||||
print(mats.grad.numpy())
|
||||
# TODO: testing allclose
|
||||
assert Tensor.allclose(ref, out, atol=1e-6), f"{ref.numpy()=}, {out.numpy()=}"
|
||||
|
||||
class TestOuterworld(unittest.TestCase):
|
||||
def test_range_plus_1(self):
|
||||
@@ -151,5 +146,85 @@ class TestOuterworld(unittest.TestCase):
|
||||
out = out.reshape(1, 3).expand(a, 3).contiguous().realize()
|
||||
self.assertListEqual([[0,4,8],[4,8,12],[8,12,16]], out.tolist())
|
||||
|
||||
class TestVmap(unittest.TestCase):
|
||||
def test_vmap_inner(self, axis_type=AxisType.LOOP, fuse=False, grad=False):
|
||||
x = Tensor.ones(1, 10).contiguous().requires_grad_()
|
||||
mats = Tensor.ones(3, 10, 10).contiguous().requires_grad_()
|
||||
|
||||
ref = x @ mats
|
||||
if fuse: ref = ref * 2
|
||||
|
||||
# vmap across axis 0
|
||||
a = UOp.range(3, -1, axis_type)
|
||||
out = x @ mats[a]
|
||||
out = out.reshape(1, 10).pad(((a,(3-a)-1), None))
|
||||
out = Tensor(out.uop.reduce(a, arg=Ops.ADD))
|
||||
if fuse: out = out * 2
|
||||
if grad:
|
||||
out.mean().backward()
|
||||
np.testing.assert_allclose(mats.grad.numpy(), (2./30) if fuse else (1./30))
|
||||
out.realize()
|
||||
|
||||
# TODO: testing allclose
|
||||
assert Tensor.allclose(ref, out, atol=1e-6), f"{ref.numpy()=}, {out.numpy()=}"
|
||||
def test_vmap_inner_fuse(self): self.test_vmap_inner(fuse=True)
|
||||
def test_vmap_outer(self): self.test_vmap_inner(AxisType.OUTER)
|
||||
def test_vmap_outer_fuse(self): self.test_vmap_inner(AxisType.OUTER, fuse=True)
|
||||
|
||||
def test_vmap_inner_grad(self): self.test_vmap_inner(grad=True)
|
||||
def test_vmap_inner_fuse_grad(self): self.test_vmap_inner(fuse=True, grad=True)
|
||||
def test_vmap_outer_grad(self): self.test_vmap_inner(AxisType.OUTER, grad=True)
|
||||
|
||||
def test_vmap_convs(self):
|
||||
layers = [
|
||||
nn.Conv2d(1, 8, 3), Tensor.relu,
|
||||
nn.Conv2d(8, 8, 3), Tensor.relu]
|
||||
img = Tensor.randn(4, 1, 16, 16).realize(*nn.state.get_parameters(layers))
|
||||
a = UOp.range(4, -1, AxisType.OUTER)
|
||||
out = img[a:a+1].sequential(layers)
|
||||
out = out.pad(((a,(4-a)-1), None, None, None))
|
||||
out = Tensor(out.uop.reduce(a, arg=Ops.ADD))
|
||||
out.realize()
|
||||
np.testing.assert_allclose(out.numpy(), img.sequential(layers).numpy(), atol=1e-6)
|
||||
|
||||
def test_vmap_gemm(self):
|
||||
layers = [
|
||||
nn.Linear(16, 16, bias=False), Tensor.relu,
|
||||
nn.Linear(16, 16, bias=False), Tensor.relu]
|
||||
img = Tensor.randn(4, 16).realize(*nn.state.get_parameters(layers))
|
||||
a = UOp.range(4, -1, AxisType.OUTER)
|
||||
out = img[a:a+1].sequential(layers)
|
||||
out = out.pad(((a,(4-a)-1), None))
|
||||
out = Tensor(out.uop.reduce(a, arg=Ops.ADD))
|
||||
out.realize()
|
||||
np.testing.assert_allclose(out.numpy(), img.sequential(layers).numpy(), atol=1e-6)
|
||||
|
||||
@unittest.skip("this is broken, we need to lower the outer reduce in the outer graph")
|
||||
def test_vmap_gemm_grad(self):
|
||||
layers = [
|
||||
nn.Linear(16, 16, bias=False), Tensor.relu,
|
||||
nn.Linear(16, 16, bias=False), Tensor.relu]
|
||||
layer_tensors = nn.state.get_parameters(layers)
|
||||
img = Tensor.randn(4, 16).realize(*layer_tensors)
|
||||
for l in layer_tensors: l.requires_grad_()
|
||||
a = UOp.range(4, -1, AxisType.OUTER)
|
||||
out = img[a:a+1].sequential(layers)
|
||||
out = out.pad(((a,(4-a)-1), None))
|
||||
out = Tensor(out.uop.reduce(a, arg=Ops.ADD))
|
||||
out.mean().backward()
|
||||
grads = [l.grad for l in layer_tensors]
|
||||
out.realize(*grads)
|
||||
out_grads = [x.numpy() for x in grads]
|
||||
|
||||
# compute reference grads
|
||||
for l in layer_tensors: l.grad = None
|
||||
img.sequential(layers).mean().backward()
|
||||
grads = [l.grad for l in layer_tensors]
|
||||
out.realize(*grads)
|
||||
ref_grads = [x.numpy() for x in grads]
|
||||
|
||||
# compare
|
||||
for o,r in zip(out_grads, ref_grads): np.testing.assert_allclose(o, r, atol=1e-6)
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
@@ -17,7 +17,7 @@ def helper_collect_profile(*devs):
|
||||
cpu_events.clear()
|
||||
|
||||
profile_list = []
|
||||
with Context(VIZ=1):
|
||||
with Context(VIZ=1, PROFILE=1):
|
||||
yield profile_list
|
||||
for dev in devs: dev.synchronize()
|
||||
for dev in devs: dev._at_profile_finalize()
|
||||
|
||||
+1
-1
@@ -517,7 +517,7 @@ class TestUOpStr(unittest.TestCase):
|
||||
|
||||
class TestUPatHelpers(unittest.TestCase):
|
||||
def test_location(self):
|
||||
self.assertEqual(sym.patterns[-1][0].location[0].replace("\\", "/").split("/")[-1], "math.py")
|
||||
self.assertEqual(sym.patterns[-1][0].location[0].replace("\\", "/").split("/")[-1], "symbolic.py")
|
||||
self.assertEqual(shared_spec.patterns[0][0].location[0].replace("\\", "/").split("/")[-1], "spec.py")
|
||||
test_upat = UPat(Ops.CONST, dtypes.bool)
|
||||
self.assertEqual(test_upat.location[0].split("/")[-1], __file__.replace("\\", "/").split("/")[-1])
|
||||
|
||||
@@ -9,7 +9,7 @@ import numpy as np
|
||||
from extra.thunder.tiny.tk import WARP_THREADS
|
||||
from extra.thunder.tiny.tk.kernel import Kernel
|
||||
|
||||
@unittest.skipUnless(Device.DEFAULT in ["CUDA", "NV"], "only cuda")
|
||||
@unittest.skipIf(CI and Device.DEFAULT not in ["CUDA", "NV"], "only cuda")
|
||||
@unittest.skipIf(isinstance(Device[Device.DEFAULT].renderer, PTXRenderer), "no ptx")
|
||||
class TestTK(unittest.TestCase):
|
||||
@unittest.skipIf(CI, "no wmma in ci")
|
||||
|
||||
@@ -5,16 +5,16 @@ from tinygrad.runtime.support.c import Struct
|
||||
class TestAutogen(unittest.TestCase):
|
||||
def test_packed_struct_sizeof(self):
|
||||
layout = [('a', ctypes.c_char), ('b', ctypes.c_int, 5), ('c', ctypes.c_char)]
|
||||
class X(ctypes.Structure): _fields_, _layout_ = layout, 'gcc-sysv'
|
||||
class Y(ctypes.Structure): _fields_, _pack_, _layout_ = layout, 1, 'ms'
|
||||
class Z(Struct): _packed_, _fields_ = True, layout
|
||||
self.assertNotEqual(ctypes.sizeof(X), 4) # ctypes bug! gcc-13.3.0 says this should have size 4
|
||||
class Z(Struct): pass
|
||||
Z._packed_, Z._fields_ = True, layout
|
||||
self.assertEqual(ctypes.sizeof(Y), 6)
|
||||
self.assertEqual(ctypes.sizeof(Z), 3)
|
||||
layout = [('a', ctypes.c_int, 31), ('b', ctypes.c_int, 31), ('c', ctypes.c_int, 1), ('d', ctypes.c_int, 1)]
|
||||
class Foo(ctypes.Structure): _fields_, _layout_ = layout, 'gcc-sysv'
|
||||
class Bar(ctypes.Structure): _fields_, _pack_, _layout_ = layout, 1, 'ms'
|
||||
class Baz(Struct): _fields_, _packed_ = layout, True
|
||||
class Baz(Struct): pass
|
||||
Baz._packed_, Baz._fields_ = True, layout
|
||||
self.assertEqual(ctypes.sizeof(Foo), 12)
|
||||
self.assertEqual(ctypes.sizeof(Bar), 12)
|
||||
self.assertEqual(ctypes.sizeof(Baz), 8)
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import unittest, time
|
||||
from tinygrad.helpers import Profiling
|
||||
from tinygrad.uop.ops import UOp
|
||||
from tinygrad.dtype import dtypes
|
||||
|
||||
@@ -38,6 +39,14 @@ class TestMicrobenchmarks(unittest.TestCase):
|
||||
a = UOp.const(dtypes.int, 2)
|
||||
for _ in range(N): (a+a).simplify()
|
||||
|
||||
class TestMicroprofile(unittest.TestCase):
|
||||
def test_uop_simplify_complex(self):
|
||||
x = UOp.variable("x", 0, 10)
|
||||
y = UOp.variable("y", 0, 10)
|
||||
expr = (x*2)+5+(x*4)+(y*2)+y
|
||||
with Profiling():
|
||||
for _ in range(1000): expr.simplify()
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
|
||||
|
||||
@@ -66,6 +66,7 @@ class TestProgressBar(unittest.TestCase):
|
||||
tqdm_output = tqdm.format_meter(n=total, total=total, elapsed=elapsed, ncols=ncols, prefix="Test")
|
||||
self._compare_bars(tinytqdm_output, tqdm_output)
|
||||
|
||||
@unittest.skip("this is flaky")
|
||||
@patch('sys.stderr', new_callable=StringIO)
|
||||
@patch('shutil.get_terminal_size')
|
||||
def test_unit_scale(self, mock_terminal_size, mock_stderr):
|
||||
|
||||
@@ -6,6 +6,7 @@ from tinygrad.uop.ops import UOp, UPat, Ops, PatternMatcher, TrackedPatternMatch
|
||||
from tinygrad.uop.symbolic import sym
|
||||
from tinygrad.dtype import dtypes
|
||||
from tinygrad.helpers import PROFILE, colored, ansistrip, flatten, TracingKey, ProfileRangeEvent, ProfileEvent, Context, cpu_events, profile_marker
|
||||
from tinygrad.helpers import VIZ
|
||||
from tinygrad.device import Buffer
|
||||
|
||||
@track_rewrites(name=True)
|
||||
@@ -33,11 +34,14 @@ class BaseTestViz(unittest.TestCase):
|
||||
cpu_events.clear()
|
||||
self.tms = TRACK_MATCH_STATS.value
|
||||
self.profile = PROFILE.value
|
||||
self.viz = VIZ.value
|
||||
TRACK_MATCH_STATS.value = 2
|
||||
PROFILE.value = 1
|
||||
VIZ.value = 1
|
||||
def tearDown(self):
|
||||
TRACK_MATCH_STATS.value = self.tms
|
||||
PROFILE.value = self.profile
|
||||
VIZ.value = self.viz
|
||||
|
||||
class TestViz(BaseTestViz):
|
||||
def test_simple(self):
|
||||
|
||||
@@ -18,6 +18,7 @@ class Scheduler:
|
||||
self.ast, self.ren = ast, ren
|
||||
self.dont_use_locals = self.ast.arg.dont_use_locals if self.ast.arg is not None else False
|
||||
self.applied_opts = list(self.ast.arg.applied_opts) if self.ast.arg is not None else []
|
||||
self.opt_range = itertools.count(start=max([x.arg[0] for x in self.rngs], default=0)+1)
|
||||
|
||||
@property
|
||||
def rngs(self):
|
||||
@@ -29,8 +30,6 @@ class Scheduler:
|
||||
def full_shape(self): return [ssimplify(x.src[0]) for x in self.rngs]
|
||||
@property
|
||||
def axis_types(self): return [x.arg[-1] for x in self.rngs]
|
||||
@property
|
||||
def maxarg(self): return max([x.arg[0] for x in self.rngs], default=0)
|
||||
|
||||
# strings like ['g0', 'g1', 'l0', 'l1', 'l2', 'l3', 'l4', 'l5', 'R0', 'r0', 'r1', 'r2', 'u0', 'u1', 'u2']
|
||||
def shape_str(self) -> list[str]:
|
||||
@@ -52,8 +51,10 @@ class Scheduler:
|
||||
def get_optimized_ast(self, name_override:str|None=None):
|
||||
if name_override is not None: name = name_override
|
||||
else:
|
||||
kernel_type = "r" if self.reduceop is not None else "E"
|
||||
name = kernel_type + colored('_', 'BLACK').join(['']+[colored(x.src[0].render(), color) for x,color in zip(self.rngs, self.colors())])
|
||||
k_type = "r" if self.reduceop is not None else "E"
|
||||
special_uops = sorted([x for x in self.ast.toposort() if x.op is Ops.SPECIAL], key=lambda x: x.arg)
|
||||
special_ops = [colored(str(x.vmax+1), "blue" if x.arg[0] == "g" else "cyan") for x in special_uops]
|
||||
name = k_type + colored('_', 'BLACK').join(['']+special_ops+[colored(x.src[0].render(), color) for x,color in zip(self.rngs, self.colors())])
|
||||
Scheduler.kernel_cnt[(function_name := to_function_name(name))] += 1
|
||||
num = f"n{Scheduler.kernel_cnt[function_name]-1}" if Scheduler.kernel_cnt[function_name] > 1 else ""
|
||||
name += colored(num, 'BLACK')
|
||||
@@ -93,7 +94,7 @@ class Scheduler:
|
||||
def shift_to(self, rng:UOp, amount:int, new_type:AxisType, top:bool=False, input_new_rng=None):
|
||||
if (old_sz:=rng.src[0].divides(amount)) is None:
|
||||
raise KernelOptError(f"{amount} can't divide {rng.src[0]} in {self.colored_shape()}")
|
||||
new_rng = UOp.range(amount, self.maxarg+1, new_type) if input_new_rng is None else input_new_rng
|
||||
new_rng = UOp.range(amount, next(self.opt_range), new_type) if input_new_rng is None else input_new_rng
|
||||
replaced_rng = rng.replace(src=(UOp.const(dtypes.int, old_sz),))
|
||||
sub_axis = (new_rng * old_sz + replaced_rng) if top else (replaced_rng * amount + new_rng)
|
||||
self.ast = self.ast.substitute({rng:sub_axis}, name=f"shift {rng.arg[:-1]} {amount} {str(new_type).split('.')[1].lower()}")
|
||||
@@ -229,9 +230,9 @@ class Scheduler:
|
||||
for tc in tensor_cores:
|
||||
if tc.dtype_in == in0.dtype.scalar() and tc.dtype_in == in1.dtype.scalar() and tc.dtype_out == reduceop.dtype.scalar():
|
||||
# tensor cores have three ranges. X, Y, and REDUCE
|
||||
in0_ranges = sorted([u for u in in0.ranges if u not in in1.ranges], key=lambda x: -x.arg[0])
|
||||
in1_ranges = sorted([u for u in in1.ranges if u not in in0.ranges], key=lambda x: -x.arg[0])
|
||||
red_ranges = sorted(reduceop.src[1:], key=lambda x: -x.arg[0])
|
||||
in0_ranges = sorted([u for u in in0.ranges if u not in in1.ranges], key=lambda x: x.arg[0], reverse=True)
|
||||
in1_ranges = sorted([u for u in in1.ranges if u not in in0.ranges], key=lambda x: x.arg[0], reverse=True)
|
||||
red_ranges = sorted(reduceop.src[1:], key=lambda x: x.arg[0], reverse=True)
|
||||
if DEBUG >= 3:
|
||||
print(f"TC({axis}): {[(x.arg[0],x.vmax+1) for x in in0_ranges]}",
|
||||
f"{[(x.arg[0],x.vmax+1) for x in in1_ranges]} {[(x.arg[0],x.vmax+1) for x in red_ranges]}")
|
||||
|
||||
+4
-3
@@ -5,7 +5,7 @@ from typing import Any, Generic, TypeVar, Iterator, Sequence, cast, Generator
|
||||
import importlib, inspect, functools, pathlib, os, platform, contextlib, sys, re, atexit, pickle, decimal
|
||||
from tinygrad.helpers import CI, OSX, LRU, getenv, diskcache_get, diskcache_put, DEBUG, GlobalCounters, flat_mv, PROFILE, temp, colored, CPU_LLVM
|
||||
from tinygrad.helpers import Context, CCACHE, ALLOW_DEVICE_USAGE, MAX_BUFFER_SIZE, cpu_events, ProfileEvent, ProfilePointEvent, dedup
|
||||
from tinygrad.helpers import unwrap_class_type, suppress_finalizing, AMD_LLVM, select_first_inited
|
||||
from tinygrad.helpers import unwrap_class_type, suppress_finalizing, AMD_LLVM, select_first_inited, VIZ
|
||||
from tinygrad.dtype import DType, ImageDType, PtrDType, dtypes, _to_np_dtype
|
||||
from tinygrad.renderer import Renderer
|
||||
|
||||
@@ -355,8 +355,9 @@ if PROFILE:
|
||||
|
||||
with open(fn:=temp("profile.pkl", append_user=True), "wb") as f: pickle.dump(cpu_events+Compiled.profile_events+Buffer.profile_events, f)
|
||||
|
||||
from tinygrad.uop.ops import launch_viz
|
||||
launch_viz("PROFILE", fn)
|
||||
if VIZ:
|
||||
from tinygrad.uop.ops import launch_viz
|
||||
launch_viz("PROFILE", fn)
|
||||
|
||||
def enumerate_devices_str() -> Generator[str, None, None]:
|
||||
from tinygrad import Tensor, Device
|
||||
|
||||
@@ -23,10 +23,12 @@ def create_schedule_with_vars(sched_sink:UOp) -> tuple[list[ScheduleItem], dict[
|
||||
in_degree: dict[UOp, int] = {}
|
||||
var_vals: dict[str, int] = {}
|
||||
for u in sched_sink.toposort():
|
||||
if u.op is not Ops.AFTER: continue # anything that's not an ASSIGN doesn't write a kernel, so we can skip
|
||||
if u.op is Ops.RANGE:
|
||||
in_degree.setdefault(u, 0)
|
||||
continue
|
||||
if u.op is not Ops.AFTER or u.src[1].op is Ops.RANGE: continue
|
||||
k = u.src[1]
|
||||
in_degree.setdefault(k, 0)
|
||||
if k.op is Ops.RANGE: continue
|
||||
for s in k.src[0].src if k.op is Ops.END else k.src:
|
||||
if s.op is Ops.AFTER:
|
||||
children[s.src[1]].append(k)
|
||||
@@ -88,7 +90,7 @@ def create_schedule_with_vars(sched_sink:UOp) -> tuple[list[ScheduleItem], dict[
|
||||
if rk.op is Ops.END: schedule.append(rk)
|
||||
else:
|
||||
raise RuntimeError(f"can't schedule {k.op}")
|
||||
for x in children[k]:
|
||||
for x in children[rk]:
|
||||
in_degree[x] -= 1
|
||||
if in_degree[x] == 0: queues[_heuristic(x)].append(x)
|
||||
|
||||
|
||||
+11
-16
@@ -3,14 +3,15 @@ import math, dataclasses
|
||||
from tinygrad.uop.ops import UOp, PatternMatcher, UPat, Ops, all_metadata
|
||||
from tinygrad.helpers import argsort
|
||||
|
||||
def reduce_gradient(ctx:UOp, ret:UOp):
|
||||
def reduce_gradient(ctx:UOp, ret:UOp, op:Ops):
|
||||
def broadcast_to_input(x): return x.reshape(x.shape+(1,)*(len(ret.src[0].shape)-len(x.shape))).expand(ret.src[0].shape)
|
||||
if ret.arg[0] == Ops.ADD: return (broadcast_to_input(ctx),)
|
||||
if ret.arg[0] == Ops.MAX:
|
||||
if op == Ops.ADD: return (broadcast_to_input(ctx),)
|
||||
if op == Ops.MAX:
|
||||
assert ret.op is Ops.REDUCE_AXIS, "only works on REDUCE_AXIS"
|
||||
mask = ret.src[0].eq(broadcast_to_input(ret)).cast(ctx.dtype)
|
||||
count = mask.r(Ops.ADD, ret.arg[1])
|
||||
return ((mask/broadcast_to_input(count)) * broadcast_to_input(ctx),)
|
||||
if ret.arg[0] == Ops.MUL: return (broadcast_to_input(ctx * ret) / ret.src[0],)
|
||||
if op == Ops.MUL: return (broadcast_to_input(ctx * ret) / ret.src[0],)
|
||||
|
||||
# ctx is grad_output
|
||||
pm_gradient = PatternMatcher([
|
||||
@@ -28,7 +29,8 @@ pm_gradient = PatternMatcher([
|
||||
((x>y).where(ctx, (x.eq(y)).where(ctx * 0.5, 0)), (x<y).where(ctx, (x.eq(y)).where(ctx * 0.5, 0)))),
|
||||
(UPat(Ops.MUL, name="ret"), lambda ctx, ret: (ret.src[1]*ctx, ret.src[0]*ctx)),
|
||||
(UPat(Ops.WHERE, name="ret"), lambda ctx, ret: (None, ret.src[0].where(ctx, ctx.const_like(0)), ret.src[0].where(ctx.const_like(0), ctx))),
|
||||
(UPat(Ops.REDUCE_AXIS, name="ret"), reduce_gradient),
|
||||
(UPat(Ops.REDUCE_AXIS, name="ret"), lambda ctx, ret: reduce_gradient(ctx, ret, ret.arg[0])),
|
||||
(UPat(Ops.REDUCE, name="ret"), lambda ctx, ret: reduce_gradient(ctx, ret, ret.arg) + (None,)*(len(ret.src)-1)),
|
||||
(UPat(Ops.CONTIGUOUS), lambda ctx: (ctx,)),
|
||||
(UPat(Ops.CONTIGUOUS_BACKWARD), lambda ctx: (ctx.contiguous(),)),
|
||||
(UPat(Ops.RESHAPE, name="ret"), lambda ctx, ret: (ctx.reshape(ret.src[0].shape), None)),
|
||||
@@ -43,17 +45,6 @@ pm_gradient = PatternMatcher([
|
||||
(UPat(Ops.KERNEL, name="k"), lambda ctx, k: k.arg.grad_fxn(ctx, k)),
|
||||
# there's no gradient for bitcast
|
||||
(UPat(Ops.BITCAST), lambda: (None,)),
|
||||
|
||||
# RANGE: loop index / axis, not a differentiable quantity
|
||||
(UPat(Ops.RANGE), lambda: (None,)),
|
||||
|
||||
# STORE: buffer write. Gradient flows only into the value being stored.
|
||||
# src layout is roughly (buffer, value, *axes_or_indices)
|
||||
(UPat(Ops.STORE), lambda ctx: (None, ctx)),
|
||||
|
||||
# END: loop terminator / "end of range" node.
|
||||
# Just pass the gradient into the body (first src), ignore the ranges.
|
||||
(UPat(Ops.END, name="ret"), lambda ctx, ret: (ctx, *[None]*(len(ret.src) - 1))),
|
||||
])
|
||||
|
||||
def _deepwalk(root:UOp, targets:set[UOp]) -> list[UOp]:
|
||||
@@ -79,4 +70,8 @@ def compute_gradient(root:UOp, root_grad:UOp, targets:set[UOp]) -> dict[UOp, UOp
|
||||
# we add the backward metadata to everything new in the graph
|
||||
for bw_uop in v.toposort(lambda x: x not in (t0, *t0.src, grads[t0])):
|
||||
all_metadata[bw_uop] = all_metadata.get(bw_uop, ())+backward_metadata
|
||||
# end any ranges on grads with a reduce sum
|
||||
for k,v in grads.items():
|
||||
if len(v.ranges):
|
||||
grads[k] = v.reduce(*v.ranges, arg=Ops.ADD)
|
||||
return grads
|
||||
|
||||
+3
-1
@@ -179,7 +179,9 @@ ALLOW_DEVICE_USAGE, MAX_BUFFER_SIZE = ContextVar("ALLOW_DEVICE_USAGE", 1), Conte
|
||||
EMULATE = ContextVar("EMULATE", "")
|
||||
CPU_COUNT = ContextVar("CPU_COUNT", max(1, len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else (os.cpu_count() or 1)))
|
||||
CPU_LLVM, CPU_LVP, AMD_LLVM = ContextVar("CPU_LLVM", 0), ContextVar("CPU_LVP", 0), ContextVar("AMD_LLVM", 0)
|
||||
VIZ = PROFILE = ContextVar("VIZ", 0)
|
||||
# VIZ implies PROFILE, but you can run PROFILE without VIZ
|
||||
VIZ = ContextVar("VIZ", 0)
|
||||
PROFILE = ContextVar("PROFILE", VIZ.value)
|
||||
SPEC = ContextVar("SPEC", 1)
|
||||
# TODO: disable by default due to speed
|
||||
IGNORE_OOB = ContextVar("IGNORE_OOB", 1)
|
||||
|
||||
@@ -5,7 +5,7 @@ from tinygrad.renderer import Renderer
|
||||
from tinygrad.renderer.cstyle import CUDARenderer
|
||||
from tinygrad.uop.ops import GroupOp, Ops, UOp, PatternMatcher, UPat, range_str
|
||||
from tinygrad.runtime.autogen import mesa
|
||||
import base64, ctypes, ctypes.util, struct, functools, inspect
|
||||
import base64, contextlib, ctypes, ctypes.util, struct, functools, inspect
|
||||
|
||||
def g(s:str): return getattr(mesa, s)
|
||||
def nsrc(d:mesa.nir_def) -> mesa.nir_src: return mesa.nir_src(ssa=ctypes.pointer(d))
|
||||
@@ -157,8 +157,7 @@ class NIRRenderer(Renderer):
|
||||
def __init__(self): mesa.glsl_type_singleton_init_or_ref()
|
||||
|
||||
def __del__(self):
|
||||
try: mesa.glsl_type_singleton_decref()
|
||||
except FileNotFoundError: pass
|
||||
with contextlib.suppress(AttributeError):mesa.glsl_type_singleton_decref()
|
||||
|
||||
@property
|
||||
def nir_options(self): raise NotImplementedError("needs nir_options")
|
||||
|
||||
@@ -476,7 +476,7 @@ PP_GRTAVFS_FW_SEP_FUSE_FREQUENCY_TO_COUNT_SCALER_4 = PP_GRTAVFS_FW_SEP_FUSE_e.de
|
||||
PP_GRTAVFS_FW_SEP_FUSE_COUNT = PP_GRTAVFS_FW_SEP_FUSE_e.define('PP_GRTAVFS_FW_SEP_FUSE_COUNT', 19)
|
||||
|
||||
class SviTelemetryScale_t(Struct): pass
|
||||
int8_t = ctypes.c_char
|
||||
int8_t = ctypes.c_byte
|
||||
SviTelemetryScale_t._fields_ = [
|
||||
('Offset', int8_t),
|
||||
('Padding', uint8_t),
|
||||
|
||||
@@ -89,7 +89,7 @@ NIR_CMAT_C_SIGNED = nir_cmat_signed.define('NIR_CMAT_C_SIGNED', 4)
|
||||
NIR_CMAT_RESULT_SIGNED = nir_cmat_signed.define('NIR_CMAT_RESULT_SIGNED', 8)
|
||||
|
||||
class nir_const_value(ctypes.Union): pass
|
||||
int8_t = ctypes.c_char
|
||||
int8_t = ctypes.c_byte
|
||||
uint8_t = ctypes.c_ubyte
|
||||
int16_t = ctypes.c_int16
|
||||
uint16_t = ctypes.c_uint16
|
||||
@@ -3723,7 +3723,7 @@ struct__IO_FILE._fields_ = [
|
||||
('_flags2', ctypes.c_int32),
|
||||
('_old_offset', ctypes.c_int64),
|
||||
('_cur_column', ctypes.c_uint16),
|
||||
('_vtable_offset', ctypes.c_char),
|
||||
('_vtable_offset', ctypes.c_byte),
|
||||
('_shortbuf', (ctypes.c_char * 1)),
|
||||
('_lock', ctypes.POINTER(_IO_lock_t)),
|
||||
('_offset', ctypes.c_int64),
|
||||
|
||||
@@ -8,18 +8,19 @@ from tinygrad.runtime.support.hcq import MMIOInterface, BumpAllocator, hcq_filte
|
||||
from tinygrad.uop.ops import sint
|
||||
from tinygrad.device import Compiled, DMAFdRef, BufferSpec, CompilerPairT
|
||||
from tinygrad.helpers import getenv, round_up, data64_le, DEBUG, PROFILE, ProfileEvent, suppress_finalizing, lo32, hi32, colored, prod, ContextVar
|
||||
from tinygrad.helpers import VIZ
|
||||
from tinygrad.renderer.cstyle import AMDRenderer
|
||||
from tinygrad.renderer.llvmir import AMDLLVMRenderer
|
||||
from tinygrad.runtime.autogen import kfd, hsa, pci, sqtt
|
||||
from tinygrad.runtime.autogen.am import am
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler, AMDLLVMCompiler
|
||||
from tinygrad.runtime.support.compiler_amd import HIPCompiler, HIPCCCompiler, AMDLLVMCompiler
|
||||
from tinygrad.runtime.support.elf import elf_loader
|
||||
from tinygrad.runtime.support.am.amdev import AMDev, AMMemoryManager
|
||||
from tinygrad.runtime.support.amd import AMDReg, AMDIP, import_module, import_soc, import_ip_offsets, import_pmc
|
||||
from tinygrad.runtime.support.system import System, PCIIfaceBase, PCIAllocationMeta, PCIDevice, USBPCIDevice, MAP_FIXED, MAP_NORESERVE
|
||||
if getenv("IOCTL"): import extra.hip_gpu_driver.hip_ioctl # noqa: F401 # pylint: disable=unused-import
|
||||
|
||||
SQTT, SQTT_ITRACE_SE_MASK, PMC = ContextVar("SQTT", 0), ContextVar("SQTT_ITRACE_SE_MASK", 0b11), ContextVar("PMC", 0)
|
||||
SQTT, SQTT_ITRACE_SE_MASK, PMC = ContextVar("SQTT", VIZ.value>=2), ContextVar("SQTT_ITRACE_SE_MASK", 0b11), ContextVar("PMC", 0)
|
||||
EVENT_INDEX_PARTIAL_FLUSH = 4 # based on a comment in nvd.h
|
||||
WAIT_REG_MEM_FUNCTION_EQ = 3 # ==
|
||||
WAIT_REG_MEM_FUNCTION_NEQ = 4 # !=
|
||||
@@ -357,6 +358,7 @@ class AMDComputeQueue(HWQueue):
|
||||
|
||||
def timestamp(self, signal:AMDSignal):
|
||||
with self.pred_exec(xcc_mask=0b1):
|
||||
self.release_mem(cache_flush=False) # ensure all prior writes are done
|
||||
self.release_mem(signal.timestamp_addr, 0, self.pm4.data_sel__mec_release_mem__send_gpu_clock_counter, self.pm4.int_sel__mec_release_mem__none)
|
||||
self.acquire_mem() # ensure timestamp is written
|
||||
return self
|
||||
@@ -908,7 +910,8 @@ class AMDDevice(HCQCompiled):
|
||||
self.sdma_queue = self.create_queue(kfd.KFD_IOC_QUEUE_TYPE_SDMA, 0x200 if self.is_usb() else (16 << 20))
|
||||
|
||||
compilers:list[CompilerPairT] = [(functools.partial(AMDRenderer, self.arch), functools.partial(HIPCompiler, self.arch)),
|
||||
(functools.partial(AMDLLVMRenderer, self.arch), functools.partial(AMDLLVMCompiler, self.arch))]
|
||||
(functools.partial(AMDLLVMRenderer, self.arch), functools.partial(AMDLLVMCompiler, self.arch)),
|
||||
(functools.partial(AMDRenderer, self.arch), functools.partial(HIPCCCompiler, self.arch))]
|
||||
|
||||
super().__init__(device, AMDAllocator(self), compilers, functools.partial(AMDProgram, self), AMDSignal,
|
||||
functools.partial(AMDComputeAQLQueue if self.is_aql else AMDComputeQueue, self),
|
||||
|
||||
@@ -9,7 +9,7 @@ from tinygrad.runtime.support.hcq import FileIOInterface, MMIOInterface
|
||||
from tinygrad.runtime.autogen import kgsl, adreno
|
||||
from tinygrad.runtime.ops_cl import CLCompiler, CLDevice
|
||||
from tinygrad.renderer.cstyle import QCOMRenderer
|
||||
from tinygrad.helpers import getenv, mv_address, to_mv, round_up, data64_le, prod, fromimport, cpu_profile, lo32, PROFILE
|
||||
from tinygrad.helpers import getenv, mv_address, to_mv, round_up, data64_le, prod, fromimport, cpu_profile, lo32, PROFILE, suppress_finalizing
|
||||
from tinygrad.runtime.support.system import System
|
||||
if getenv("IOCTL"): import extra.qcom_gpu_driver.opencl_ioctl # noqa: F401 # pylint: disable=unused-import
|
||||
|
||||
@@ -317,6 +317,7 @@ class QCOMAllocator(HCQAllocatorBase):
|
||||
self.dev.synchronize()
|
||||
return to_mv(cast(int, src.va_addr), src.size)
|
||||
|
||||
@suppress_finalizing
|
||||
def _free(self, opaque, options:BufferSpec):
|
||||
self.dev.synchronize()
|
||||
self.dev._gpu_free(opaque)
|
||||
|
||||
@@ -103,7 +103,7 @@ def gen(dll, files, args=[], prolog=[], rules=[], epilog=[], recsym=False, use_e
|
||||
suggested_name = anon_names.get(f"{loc_file(loc(decl:=clang.clang_getTypeDeclaration(t)))}:{loc_line(loc(decl))}", suggested_name)
|
||||
nonlocal lines, types, anoncnt, objc
|
||||
tmap = {clang.CXType_Void:"None", clang.CXType_Char_U:"ctypes.c_ubyte", clang.CXType_UChar:"ctypes.c_ubyte", clang.CXType_Char_S:"ctypes.c_char",
|
||||
clang.CXType_SChar:"ctypes.c_char",
|
||||
clang.CXType_SChar:"ctypes.c_byte",
|
||||
**{getattr(clang, f'CXType_{k}'):f"ctypes.c_{k.lower()}" for k in ["Bool", "WChar", "Float", "Double", "LongDouble"]},
|
||||
**{getattr(clang, f'CXType_{k}'):f"ctypes.c_{'u' if 'U' in k else ''}int{sz}" for sz,k in
|
||||
[(16, "UShort"), (16, "Short"), (32, "UInt"), (32, "Int"), (64, "ULong"), (64, "Long"), (64, "ULongLong"), (64, "LongLong")]}}
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
import ctypes
|
||||
import ctypes, hashlib, tempfile, subprocess, pathlib
|
||||
from tinygrad.helpers import system
|
||||
from tinygrad.runtime.autogen import comgr
|
||||
try:
|
||||
@@ -13,7 +13,7 @@ from tinygrad.runtime.support.compiler_cpu import LLVMCompiler
|
||||
from tinygrad.helpers import OSX, to_char_p_p
|
||||
|
||||
def amdgpu_disassemble(lib:bytes):
|
||||
asm = system(f"{'llvm-objdump' if OSX else '/opt/rocm/llvm/bin/llvm-objdump'} -d -", input=lib).splitlines()
|
||||
asm = system(f"{'/opt/homebrew/opt/llvm/bin/llvm-objdump' if OSX else '/opt/rocm/llvm/bin/llvm-objdump'} -d -", input=lib).splitlines()
|
||||
while asm and ("s_nop 0" in asm[-1] or "s_code_end" in asm[-1]): asm.pop()
|
||||
print("\n".join(asm))
|
||||
|
||||
@@ -90,6 +90,24 @@ class HIPCompiler(Compiler):
|
||||
except RuntimeError as e: raise CompileError(e) from e
|
||||
def disassemble(self, lib:bytes): amdgpu_disassemble(lib)
|
||||
|
||||
class HIPCCCompiler(Compiler):
|
||||
def __init__(self, arch:str, extra_options:list[str]=[]):
|
||||
self.arch, self.extra_options = arch, extra_options
|
||||
super().__init__(f"compile_hipcc_{self.arch}_{hashlib.sha256(' '.join(extra_options).encode()).hexdigest()[:8]}")
|
||||
def compile(self, src:str) -> bytes:
|
||||
with tempfile.NamedTemporaryFile(suffix=".cpp") as srcf, tempfile.NamedTemporaryFile(suffix=".bc") as bcf:
|
||||
with tempfile.NamedTemporaryFile(suffix=".hsaco") as libf:
|
||||
srcf.write(src.encode())
|
||||
srcf.flush()
|
||||
|
||||
subprocess.run(["hipcc", "-c", "-emit-llvm", "--cuda-device-only", "-O3", "-mcumode",
|
||||
f"--offload-arch={self.arch}", "-I/opt/rocm/include/hip", "-o", bcf.name, srcf.name] + self.extra_options, check=True)
|
||||
subprocess.run(["hipcc", "-target", "amdgcn-amd-amdhsa", f"-mcpu={self.arch}",
|
||||
"-O3", "-mllvm", "-amdgpu-internalize-symbols", "-c", "-o", libf.name, bcf.name] + self.extra_options, check=True)
|
||||
|
||||
return pathlib.Path(libf.name).read_bytes()
|
||||
def disassemble(self, lib:bytes): amdgpu_disassemble(lib)
|
||||
|
||||
class AMDLLVMCompiler(LLVMCompiler):
|
||||
jit = False
|
||||
target_arch = "AMDGPU"
|
||||
|
||||
@@ -4,12 +4,14 @@ from typing import TYPE_CHECKING, Any
|
||||
if TYPE_CHECKING: id_ = ctypes.c_void_p
|
||||
else:
|
||||
class id_(ctypes.c_void_p):
|
||||
_is_finalizing = sys.is_finalizing # FIXME: why is this needed
|
||||
|
||||
retain: bool = False
|
||||
# This prevents ctypes from converting response to plain int, and dict.fromkeys() can use it to dedup
|
||||
def __hash__(self): return hash(self.value)
|
||||
def __eq__(self, other): return self.value == other.value
|
||||
def __del__(self):
|
||||
if self.retain and not sys.is_finalizing(): self.release()
|
||||
if self.retain and not self._is_finalizing(): self.release()
|
||||
def release(self): msg("release")(self)
|
||||
def retained(self):
|
||||
setattr(self, 'retain', True)
|
||||
|
||||
@@ -26,6 +26,8 @@ pm_generate_realize_map = PatternMatcher([
|
||||
(UPat(Ops.SINK, name="s"), lambda ctx,s: ctx.update((x.base, None) for x in s.src if x.base.op not in ALWAYS_CONTIGUOUS)),
|
||||
# always realize COPY/BUFFER_VIEW/CONTIGUOUS/STORE
|
||||
(UPat({Ops.COPY, Ops.BUFFER_VIEW, Ops.CONTIGUOUS, Ops.STORE}, name="tr"), realize),
|
||||
# always realize REDUCE on outer ranges
|
||||
(UPat(Ops.REDUCE, name="r"), lambda ctx,r: realize(ctx, r) if any(tr.arg[-1] == AxisType.OUTER for tr in r.src[1:]) else None),
|
||||
# realize srcs of COPY, MSELECT, MSTACK
|
||||
(UPat((Ops.COPY, Ops.MSELECT, Ops.MSTACK), name="rb"), realize_srcs),
|
||||
# realize ASSIGN and input to assign (might be optimized out)
|
||||
|
||||
@@ -2,7 +2,7 @@ from dataclasses import dataclass, field
|
||||
import itertools
|
||||
from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
|
||||
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, _substitute, ssimplify, KernelInfo
|
||||
from tinygrad.uop.ops import track_rewrites, graph_rewrite, identity_element, sint, AxisType, BottomUpGate, Kernel, _remove_all_tags
|
||||
from tinygrad.uop.ops import track_rewrites, graph_rewrite, identity_element, sint, AxisType, BottomUpGate, Kernel, _remove_all_tags, range_str
|
||||
from tinygrad.uop.symbolic import symbolic
|
||||
from tinygrad.helpers import argsort, prod, all_same, pluralize, getenv, flatten, dedup, all_int, DEBUG, SPLIT_REDUCEOP, DEBUG_RANGEIFY
|
||||
from tinygrad.helpers import PCONTIG, partition, get_single_element, unwrap, disable_gc
|
||||
@@ -325,6 +325,18 @@ def bufferize_to_store(ctx:itertools.count|None, x:UOp, idx:UOp, allow_locals=Tr
|
||||
for m in mops[::-1]: ret = ret._mop(*m)
|
||||
return ret
|
||||
|
||||
# lower outerworld reduce here
|
||||
if x.src[0].op is Ops.REDUCE and len(x.src[0].src) == 2 and x.src[0].src[1].arg[-1] == AxisType.OUTER:
|
||||
assert sdtype.addrspace == AddrSpace.GLOBAL
|
||||
outer_range = x.src[0].src[1]
|
||||
buf = UOp.new_buffer(x.arg.device, size, x.dtype)
|
||||
# NOTE: this has the same number as the outer range, we need string ranges!
|
||||
zero_range = outer_range.replace(src=(UOp.const(dtypes.index, size),), arg=outer_range.arg[:-1]+(AxisType.LOOP,))
|
||||
buf = buf.after(buf.index(zero_range).store(0).end(zero_range))
|
||||
bufi = buf.index(idx, dtype=sdtype)
|
||||
do_store = bufi.store(bufi.load() + x.src[0].src[0], tag=x.tag).end(*rngs).end(outer_range)
|
||||
return buf.after(do_store)
|
||||
|
||||
# NOTE: the DEFINE_LOCAL needs to be disambiguated here
|
||||
if sdtype.addrspace == AddrSpace.GLOBAL:
|
||||
buf = UOp.new_buffer(x.arg.device, size, x.dtype)
|
||||
@@ -397,6 +409,9 @@ def handle_after(ctx:LocalAddBufferContext, after:UOp):
|
||||
|
||||
def renumber_range(ctx:LocalAddBufferContext, r:UOp):
|
||||
if r.tag != (): return None
|
||||
if r.arg[-1] == AxisType.OUTER:
|
||||
# for outer range, we replace with a bound variable
|
||||
return UOp.variable("range_"+range_str(r), r.vmin, r.vmax).bind(r.replace(tag=None))
|
||||
ret = r.replace(arg=(ctx.range,)+r.arg[1:], tag=None)
|
||||
ctx.range += 1
|
||||
return ret
|
||||
@@ -469,6 +484,7 @@ pm_add_range_tags = PatternMatcher([
|
||||
])
|
||||
|
||||
def split_store(ctx:list[UOp], x:UOp) -> UOp|None:
|
||||
# if we have any outer ranges open here, we don't split
|
||||
if len([r for r in x.ranges if r.arg[-1] != AxisType.OUTER]): return None
|
||||
|
||||
# ends of outer range don't go in kernels
|
||||
@@ -540,7 +556,7 @@ def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
|
||||
# convert movement ops to ranges
|
||||
tsink, rctx = run_rangeify(tsink, DEBUG_RANGEIFY)
|
||||
|
||||
tsink = graph_rewrite(tsink, symbolic+pm_reduce_simplify+pm_const_buffer_folding, name="symbolic+reduce_collapse") # this does const folding
|
||||
tsink = graph_rewrite(tsink, symbolic+pm_reduce_simplify+pm_const_buffer_folding, name="symbolic+reduce_collapse")
|
||||
tsink = graph_rewrite(tsink, pm_remove_bufferize, bottom_up=True, name="remove bufferize with cost function")
|
||||
tsink = graph_rewrite(tsink, symbolic+pm_reduce_simplify+pm_const_buffer_folding, name="symbolic+reduce_collapse pt 2")
|
||||
tsink = graph_rewrite(tsink, pm_limit_bufs, ctx=rctx, name="limit buffers")
|
||||
@@ -571,12 +587,12 @@ def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
|
||||
assign_rep[a] = kernel_assign[s] = a.replace(src=a.src+(u,))
|
||||
if assign_rep: tsink = graph_rewrite(tsink, _substitute, ctx=assign_rep, bottom_up=True, name="fix_assign")
|
||||
|
||||
if getenv("VIZ"): graph_rewrite(tsink, PatternMatcher([]), name="View Kernel Graph")
|
||||
|
||||
# TODO: we can probably get this earlier
|
||||
sink_tags = [s.tag for s in tsink.src]
|
||||
tsink = graph_rewrite(tsink, _remove_all_tags, name="remove all tags")
|
||||
|
||||
if getenv("VIZ"): graph_rewrite(tsink, PatternMatcher([]), name="View Kernel Graph")
|
||||
|
||||
becomes_map: dict[UOp, UOp] = {}
|
||||
for tag, s in zip(sink_tags, tsink.src):
|
||||
assert tag is not None
|
||||
|
||||
+4
-9
@@ -2456,14 +2456,9 @@ class Tensor(OpMixin):
|
||||
return self._split_cumalu(axis, Ops.MAX)
|
||||
|
||||
@staticmethod
|
||||
def _tri(r:sint, c:sint, diagonal:int=0, **kwargs) -> Tensor:
|
||||
def _tri(r:sint, c:sint, diagonal:int=0, device=None, requires_grad:bool|None=None) -> Tensor:
|
||||
assert isinstance(r, int) and isinstance(c, int), f"does not support symbolic, getting {r=}, {c=}"
|
||||
if r == 0 or c == 0 or diagonal >= c: return Tensor.zeros(r,c,**kwargs)
|
||||
if r+diagonal <= 0: return Tensor.ones(r,c,**kwargs)
|
||||
s = r+c-1
|
||||
# build a (s, s) upper triangle
|
||||
t = Tensor.ones(s,s,**kwargs).pad((None,(0,s))).flatten().shrink(((0,s*(2*s-1)),)).reshape(s,-1).shrink((None,(0,s)))
|
||||
return t[:r,-diagonal:c-diagonal] if diagonal <= 0 else t[diagonal:r+diagonal,:c]
|
||||
return (Tensor.arange(r, device=device).unsqueeze(-1) + diagonal <= Tensor.arange(c, device=device)).requires_grad_(requires_grad)
|
||||
|
||||
def triu(self, diagonal:int=0) -> Tensor:
|
||||
"""
|
||||
@@ -2486,7 +2481,7 @@ class Tensor(OpMixin):
|
||||
print(t.triu(diagonal=-1).numpy())
|
||||
```
|
||||
"""
|
||||
return Tensor._tri(self.shape[-2], self.shape[-1], diagonal=diagonal, device=self.device, dtype=dtypes.bool).where(self, self.zeros_like())
|
||||
return Tensor._tri(self.shape[-2], self.shape[-1], diagonal=diagonal, device=self.device).where(self, self.zeros_like())
|
||||
|
||||
def tril(self, diagonal:int=0) -> Tensor:
|
||||
"""
|
||||
@@ -2509,7 +2504,7 @@ class Tensor(OpMixin):
|
||||
print(t.tril(diagonal=-1).numpy())
|
||||
```
|
||||
"""
|
||||
return Tensor._tri(self.shape[-2], self.shape[-1], diagonal=diagonal+1, device=self.device, dtype=dtypes.bool).where(self.zeros_like(), self)
|
||||
return Tensor._tri(self.shape[-2], self.shape[-1], diagonal=diagonal+1, device=self.device).where(self.zeros_like(), self)
|
||||
|
||||
def interpolate(self, size:tuple[int, ...], mode:str="linear", align_corners:bool=False) -> Tensor:
|
||||
"""
|
||||
|
||||
+19
-20
@@ -89,8 +89,8 @@ class UOpMetaClass(type):
|
||||
if SPEC > 1:
|
||||
from tinygrad.uop.spec import full_spec, test_pyrender
|
||||
if SPEC > 2: test_pyrender(created)
|
||||
with Context(IGNORE_OOB=1): ret = full_spec.rewrite(created)
|
||||
if cast(bool|None, ret) is not True: raise RuntimeError(f"SPEC ISSUE {ret}: {created}")
|
||||
with Context(IGNORE_OOB=1): fret = cast(bool|None, full_spec.rewrite(created))
|
||||
if fret is not True: raise RuntimeError(f"SPEC ISSUE {fret}: {created}")
|
||||
return created
|
||||
|
||||
# some uops map to other stuff
|
||||
@@ -583,7 +583,7 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
|
||||
def new_buffer(device:str|tuple[str, ...], size:int, dtype:DType, num=None):
|
||||
return UOp(Ops.BUFFER, dtype, (UOp.unique(num), UOp(Ops.DEVICE, arg=device)), size)
|
||||
@property
|
||||
def device(self) -> str|tuple[str, ...]: return cast(str|tuple[str, ...], unwrap(self._device))
|
||||
def device(self) -> str|tuple[str, ...]: return unwrap(self._device)
|
||||
@recursive_property
|
||||
def _device(self) -> str|tuple[str, ...]|None:
|
||||
if self.op is Ops.DEVICE: return self.arg
|
||||
@@ -866,8 +866,8 @@ def print_uops(uops:list[UOp]):
|
||||
|
||||
def get_location() -> tuple[str, int]:
|
||||
frm = sys._getframe(1)
|
||||
# skip over ops.py/mathtraits.py (unless there's nothing but ops.py/mathtraits.py)
|
||||
while pathlib.Path(frm.f_code.co_filename).name in ("ops.py", "mathtraits.py") and frm.f_back is not None and \
|
||||
# skip over ops.py and anything in mixin
|
||||
while ((codepath:=pathlib.Path(frm.f_code.co_filename)).name == "ops.py" or codepath.parent.name == "mixin") and frm.f_back is not None and \
|
||||
not frm.f_back.f_code.co_filename.startswith("<frozen"):
|
||||
frm = frm.f_back
|
||||
return frm.f_code.co_filename, frm.f_lineno
|
||||
@@ -1077,20 +1077,22 @@ def track_rewrites(name:Callable[..., str|TracingKey]|bool=True, replay:bool=Fal
|
||||
|
||||
active_rewrites:list[TrackedGraphRewrite] = []
|
||||
def profile_matches(fxn:Callable):
|
||||
def wrap(*args, **kwargs):
|
||||
name = str(kwargs.get("name", None) or fxn.__name__)
|
||||
assert args and isinstance(args[0], UOp), f"invalid match tracing inputs for {name} with {args}"
|
||||
if tracking:=(TRACK_MATCH_STATS >= 2):
|
||||
def wrap_profile_matches(*args, **kwargs):
|
||||
if TRACK_MATCH_STATS >= 2:
|
||||
name = str(kwargs.get("name", None) or fxn.__name__)
|
||||
assert args and isinstance(args[0], UOp), f"invalid match tracing inputs for {name} with {args}"
|
||||
loc = ((frm:=sys._getframe(1)).f_code.co_filename, frm.f_lineno)
|
||||
depth = len(active_rewrites)
|
||||
if not tracked_ctxs: add_trace_group(TracingKey(f"default {fxn.__name__}"))
|
||||
tracked_ctxs[-1].append(ctx:=TrackedGraphRewrite(loc, args[0].trace_num, [], name, depth, kwargs.get("bottom_up", False)))
|
||||
active_rewrites.append(ctx)
|
||||
with cpu_profile(name, "TINY", display=tracking):
|
||||
ret = fxn(*args, **kwargs)
|
||||
if tracking: active_rewrites.pop()
|
||||
return ret
|
||||
return wrap
|
||||
with cpu_profile(name, "TINY"):
|
||||
ret = fxn(*args, **kwargs)
|
||||
active_rewrites.pop()
|
||||
return ret
|
||||
# without tracking, we just call the function
|
||||
return fxn(*args, **kwargs)
|
||||
return wrap_profile_matches
|
||||
|
||||
class TrackedPatternMatcher(PatternMatcher):
|
||||
def rewrite(self, uop:UOp, ctx=None) -> UOp|None:
|
||||
@@ -1164,12 +1166,12 @@ class RewriteContext:
|
||||
|
||||
def cached_pm_rewrite(self, x:UOp):
|
||||
if (ret:=self.pm_cache.get(x,SENTINEL)) is not SENTINEL: return ret
|
||||
ret = self.pm_cache[x] = cast(PatternMatcher, self.pm).rewrite(x, self.ctx)
|
||||
ret = self.pm_cache[x] = unwrap(self.pm).rewrite(x, self.ctx)
|
||||
return ret
|
||||
|
||||
def cached_bpm_rewrite(self, x:UOp):
|
||||
if (ret:=self.bpm_cache.get(x,SENTINEL)) is not SENTINEL: return ret
|
||||
ret = self.bpm_cache[x] = cast(PatternMatcher, self.bpm).rewrite(x, self.ctx)
|
||||
ret = self.bpm_cache[x] = unwrap(self.bpm).rewrite(x, self.ctx)
|
||||
return ret
|
||||
|
||||
def unified_rewrite(self, root:UOp) -> UOp:
|
||||
@@ -1265,15 +1267,12 @@ pm_lower_index_dtype = PatternMatcher([
|
||||
(UPat(Ops.SPECIAL, src=(UPat.var("var").cast(dtypes.index),), name="u"), lambda u,var: u.replace(dtype=dtypes.int, src=(var,)).cast(dtypes.index)),
|
||||
(UPat(Ops.DEFINE_VAR, dtype=dtypes.index, name="u"), lambda u: u.replace(dtype=dtypes.int).cast(dtypes.index)),
|
||||
(UPat(Ops.BIND, src=(UPat.var("var").cast(dtypes.index), UPat.cvar("val").cast(dtypes.index))), lambda var,val: var.bind(val).cast(dtypes.index)),
|
||||
(UPat(Ops.CAST, src=(UPat(name="x").cast(dtypes.index),), name="c"), lambda x,c: x.cast(c.dtype)),
|
||||
# lower Invalid
|
||||
(UPat.var("buf").index(UPat.var("cond").where(UPat.var("idx"), UPat(Ops.CONST, arg=Invalid))), lambda buf,idx,cond: buf.index(idx, cond, ptr=True)),
|
||||
# remove hanging casts
|
||||
(UPat(Ops.INDEX, src=(UPat.var("buf"), UPat.var("idx", dtypes.ints).cast()),), lambda buf,idx: buf.index(idx, ptr=True)),
|
||||
(UPat(Ops.INDEX, src=(UPat.var("buf"), UPat.var("idx", dtypes.ints).cast(), UPat.var("valid"))),
|
||||
lambda buf,idx,valid: buf.index(idx, valid, ptr=True)),
|
||||
(UPat((Ops.STORE, Ops.LOAD), src=(UPat(), UPat(), UPat().cast(dtypes.index)), allow_any_len=True, name="s"),
|
||||
lambda s: s.replace(src=s.src[:2]+tuple(u.src[0] for u in s.src[2:]))),
|
||||
(UPat((Ops.SINK, Ops.NOOP, Ops.END), name="n"),
|
||||
lambda n: n.replace(src=tuple(s.src[0] if s.op is Ops.CAST and s.dtype == dtypes.index else s for s in n.src))),
|
||||
])
|
||||
@@ -1353,7 +1352,7 @@ pm_pyrender_extra = PatternMatcher([
|
||||
(UPat(Ops.REDUCE_AXIS, name="r"), lambda ctx,r: f"{ctx[r.src[0]]}.r({r.arg[0]}, {r.arg[1]})"),
|
||||
# NOTE: range has srcs sometimes after control flow
|
||||
(UPat(Ops.RANGE, src=(UPat(Ops.CONST, name="c"),), allow_any_len=True, name="x"), lambda ctx,x,c:
|
||||
"UOp.range("+', '.join([str(c.arg)] + [str(y) for y in x.arg])+
|
||||
"UOp.range("+', '.join([str(c.arg)] + [repr(y) for y in x.arg])+
|
||||
(f', src={srcs(ctx, x.src[1:])}' if len(x.src) > 1 else '')+(', dtype='+str(x.dtype) if x.dtype is not dtypes.index else '')+")"),
|
||||
# TODO: index shouldn't mismatch dtype
|
||||
(UPat(Ops.INDEX, src=(UPat(), UPat()), allow_any_len=True, name="x"), lambda ctx,x:
|
||||
|
||||
@@ -42,7 +42,7 @@ shared_spec = PatternMatcher([
|
||||
(UPat(Ops.INDEX, src=(UPat(),), allow_any_len=True, name="x"), lambda x: all(y.dtype == dtypes.index for y in x.src[1:]) or None),
|
||||
|
||||
# RANGE/SPECIAL define loops, END closes them
|
||||
(UPat(Ops.END, src=(UPat(), UPat(Ops.RANGE)), dtype=dtypes.void), lambda: True),
|
||||
(UPat(Ops.END, src=(UPat(), UPat(Ops.RANGE))), lambda: True),
|
||||
])
|
||||
|
||||
# ***** UOp spec in the Tensor graph *****
|
||||
@@ -171,7 +171,7 @@ kernel_spec = PatternMatcher([
|
||||
(UPat(Ops.UNROLL, name="x"), lambda x: x.src[0].dtype.count == prod(y[1] for y in x.arg)),
|
||||
|
||||
# END can end multiple axes here
|
||||
(UPat(Ops.END, src=(UPat(), UPat()), allow_any_len=True, dtype=dtypes.void), lambda: True),
|
||||
(UPat(Ops.END, src=(UPat(), UPat()), allow_any_len=True), lambda: True),
|
||||
|
||||
# bufferize can be on anything
|
||||
(UPat(Ops.BUFFERIZE, src=(UPat(),), allow_any_len=True, name="x"), lambda x: True),
|
||||
|
||||
+10
-24
@@ -2,7 +2,7 @@
|
||||
import math, operator, struct, functools
|
||||
from collections import defaultdict
|
||||
from tinygrad.uop.ops import Ops, PatternMatcher, UPat, UOp, GroupOp, exec_alu
|
||||
from tinygrad.dtype import ConstType, dtypes, PtrDType, AddrSpace, can_safe_cast, Invalid
|
||||
from tinygrad.dtype import ConstType, dtypes, PtrDType, can_safe_cast, Invalid
|
||||
from tinygrad.helpers import partition, all_same, prod, flatten, get_single_element, cdiv, cmod, CORRECT_DIVMOD_FOLDING, unwrap
|
||||
from tinygrad.uop.decompositions import xpow
|
||||
|
||||
@@ -24,19 +24,16 @@ def fold_bitcast(root:UOp, c:UOp) -> UOp|None:
|
||||
invalid_pat = UPat(Ops.CONST, arg=Invalid, name="i")
|
||||
invalid_gate = UPat.var("cond").where(UPat.var("x"), invalid_pat)
|
||||
|
||||
# this needs to be before symbolic so that 0*something_that_might_be_invalid doesnt become 0
|
||||
propagate_invalid = PatternMatcher([
|
||||
# this needs to be before symbolic so that 0*something_that_might_be_invalid doesnt become 0
|
||||
# propagate invalid, push it past children
|
||||
(invalid_gate.cast(name="cast"), lambda i,x,cond,cast: x.cast(cast.dtype) if cast.dtype is not dtypes.index else None),
|
||||
(invalid_gate.cast(name="cast"), lambda i,x,cond,cast: x.cast(cast.dtype)),
|
||||
*((invalid_gate.alu(op, UPat.var("y")).named("alu"), lambda cond,x,y,alu,i: cond.where(x.alu(alu.op,y), i))
|
||||
for op in GroupOp.Binary-GroupOp.Comparison),
|
||||
# TODO: when can this happen? and is it always safe to just drop invalid?
|
||||
*((invalid_gate.alu(op, UPat.var("y")).named("alu"), lambda cond,x,y,alu,i: x.alu(alu.op,y)) for op in GroupOp.Comparison),
|
||||
# invalid + y -> y same for other ops
|
||||
# invalid + y -> invalid same for other ops
|
||||
*((invalid_pat.alu(op, UPat(dtype=dtypes.index)).named("alu"), lambda alu,i: i) for op in GroupOp.Binary-GroupOp.Comparison),
|
||||
# i < y -> a_bool_value_that_will_never_be_used: we choose a random bool const
|
||||
*((invalid_pat.alu(op, UPat(dtype=dtypes.index)), lambda i: UOp.const(dtypes.bool, True)) for op in GroupOp.Comparison),
|
||||
# a.where(b.where(c, d), d) -> (a & b).where(c, d)
|
||||
(UPat.var("a").where(UPat.var("b").where(UPat.var("c"), UPat.var("d")), UPat.var("d")), lambda a,b,c,d: (a&b).where(c,d)),
|
||||
])
|
||||
|
||||
symbolic_simple = propagate_invalid + PatternMatcher([
|
||||
@@ -108,11 +105,6 @@ symbolic_simple = propagate_invalid + PatternMatcher([
|
||||
((UPat.var('x', dtypes.uint64)&0xFFFFFFFF).cast(dtypes.uint32), lambda x: x.cast(dtypes.uint32)&0xFFFFFFFF), # TODO: why is the and needed?
|
||||
(((UPat.var(None, dtypes.uint64)*(1<<32)) | UPat.var('y', dtypes.uint32).cast(dtypes.uint64)).cast(dtypes.uint32), lambda y: y),
|
||||
(((UPat.var('x', dtypes.uint64)*(1<<32)) | UPat.var(None, dtypes.uint32).cast(dtypes.uint64))//(1<<32), lambda x: x),
|
||||
# hacks for threefry long removal when padded (TODO: genericize)
|
||||
(UPat.var('x', dtypes.uint32).cast(dtypes.uint64) * UPat.var('y').where(UPat.const(dtypes.uint64, 1<<32), UPat.const(dtypes.uint64, 0)),
|
||||
lambda x,y: y.where(x, 0).cast(dtypes.uint64) * (1<<32)),
|
||||
((UPat.var('x', dtypes.uint64)&(UPat.var('y').where(UPat.const(dtypes.uint64, 0xFFFFFFFF), UPat.const(dtypes.uint64, 0)))).cast(dtypes.uint32),
|
||||
lambda x,y: y.where(x.cast(dtypes.uint32), 0)),
|
||||
# new decomp rules for threefry
|
||||
(((UPat.var(None, dtypes.uint64)<<32) | UPat.var('y', dtypes.uint32).cast(dtypes.uint64)).cast(dtypes.uint32), lambda y: y),
|
||||
(((UPat.var('x', dtypes.uint64)<<32) | UPat.var(None, dtypes.uint32).cast(dtypes.uint64))>>32, lambda x: x),
|
||||
@@ -121,6 +113,8 @@ symbolic_simple = propagate_invalid + PatternMatcher([
|
||||
# a conditional with the same results either way is a noop, also fold const conditionals
|
||||
(UPat.var().where(UPat.var("val"), UPat.var("val")), lambda val: val),
|
||||
(UPat.cvar("gate", vec=False).where(UPat.var("c0"), UPat.var("c1")), lambda gate, c0, c1: c0 if gate.arg else c1),
|
||||
# a.where(b.where(c, d), d) -> (a & b).where(c, d)
|
||||
(UPat.var("a").where(UPat.var("b").where(UPat.var("c"), UPat.var("d")), UPat.var("d")), lambda a,b,c,d: (a&b).where(c,d)),
|
||||
])
|
||||
|
||||
# ******** phase 2 builds on phase 1, it includes the old "symbolic", rules that match deeper ********
|
||||
@@ -407,14 +401,10 @@ def uop_given_valid(valid:UOp, uop:UOp, try_simplex=True) -> UOp:
|
||||
expr, is_upper, c = res
|
||||
bounds[expr][int(is_upper)] = c
|
||||
|
||||
# don't simplify any other gates, can lead to OOB, we substitute them back later
|
||||
uop = uop.substitute((load_subs:={u: UOp(Ops.NOOP, dtype=u.dtype, arg=u) for u in uop.toposort() if u.op is Ops.INDEX}))
|
||||
|
||||
# simplify uop given that valid is True
|
||||
all_candidates = []
|
||||
for i,(expr,v) in enumerate(bounds.items()):
|
||||
v0, v1 = (expr.vmin if v[0] is None else v[0], expr.vmax if v[1] is None else v[1])
|
||||
expr = expr.substitute(load_subs) # make sure expr appears in same form in the uop
|
||||
# try checking the whole clause
|
||||
all_candidates.append((expr, UOp.variable(f"fake{i}", v0, v1, expr.dtype)))
|
||||
|
||||
@@ -438,8 +428,6 @@ def uop_given_valid(valid:UOp, uop:UOp, try_simplex=True) -> UOp:
|
||||
# try all the valids together (but only the whole expressions)
|
||||
if (s_uop:=uop.substitute(sub_dict:=dict(all_candidates))) is not uop:
|
||||
uop = s_uop.simplify().substitute({newX:X for X,newX in sub_dict.items()}).simplify(full_symbolic=False)
|
||||
# put the loads back in
|
||||
uop = uop.substitute({v:k for k,v in load_subs.items()})
|
||||
return uop
|
||||
|
||||
def _valid_priority(v: UOp, valids:list[UOp]):
|
||||
@@ -456,7 +444,7 @@ def simplify_valid(valid:UOp) -> UOp|None:
|
||||
if ret[-1] is not stmt: something_changed = True
|
||||
return UOp.prod(*ret) if something_changed else None
|
||||
|
||||
# ******** phase 3 is the complete symbolic, and deals with very complex things like loop rewriting and threefry transform ********
|
||||
# ******** phase 3 is the complete symbolic ********
|
||||
|
||||
def reduce_mul_chain(r:UOp):
|
||||
if r.arg not in {Ops.ADD, Ops.MAX}: return None
|
||||
@@ -485,6 +473,8 @@ def where_on_load(c1, buf, x):
|
||||
# aditionally we can drop the clause on the where if it already exists in the load
|
||||
remaining_clause = UOp.const(dtypes.bool, True).prod(*[c for c in c1.split_uop(Ops.AND) if c not in removed])
|
||||
return remaining_clause.where(buf.index(x.get_idx().valid(functools.reduce(operator.and_, moved_clauses, c2))), 0)
|
||||
|
||||
# where after gated load becomes alt value, TODO: this is sort of duplicated with rules in devectorizer
|
||||
pm_move_where_on_load = PatternMatcher([
|
||||
(UPat.var("c1").where(UPat.var("buf").index(UPat.var("x")), 0), where_on_load),
|
||||
(UPat.var("c1").where(0, UPat.var("buf").index(UPat.var("x"))), lambda c1,buf,x: where_on_load(c1.logical_not(),buf,x)),
|
||||
@@ -500,9 +490,6 @@ pm_simplify_valid = PatternMatcher([
|
||||
# this is symbolic 2.0
|
||||
REMOVE_FROM_SINK_LIKE = {Ops.UNROLL, Ops.NOOP, Ops.VECTORIZE, Ops.SINK}
|
||||
sym = symbolic+pm_simplify_valid+PatternMatcher([
|
||||
# LOAD/STORE -> NOOP
|
||||
(UPat.var('x').store(UPat.var('x').load(), allow_any_len=True), lambda x: None if x.dtype.addrspace != AddrSpace.REG else x.src[0].src[0]),
|
||||
(UPat(Ops.LOAD, src=(UPat.cvar('c'))), lambda c: c),
|
||||
# VECTORIZE/GEP
|
||||
(UPat(Ops.VECTORIZE, src=UPat(Ops.GEP, src=(UPat.var("x"),)), name="vec"), lambda vec,x: x.gep(tuple(y.arg[0] for y in vec.src))),
|
||||
# reorder ALU/VECTORIZE
|
||||
@@ -531,7 +518,6 @@ sym = symbolic+pm_simplify_valid+PatternMatcher([
|
||||
# fold gated LOAD/STORE
|
||||
(UPat((Ops.LOAD, Ops.STORE), src=(UPat().index(UPat.const(dtypes.index, Invalid)).or_casted(),), allow_any_len=True, name="x"),
|
||||
lambda x: UOp(Ops.NOOP) if x.op is Ops.STORE else x.const_like(0)), # invalid store does nothing. invalid load produces 0
|
||||
# # Where after gated load becomes alt value, TODO: this is sort of duplicated with rules in devectorizer
|
||||
((UPat.var("x") * UPat.var("x")).reciprocal(), lambda x: x.reciprocal()*x.reciprocal()), # 1/(x^c) -> (1/x)^c
|
||||
((UPat.var("x") * UPat.var("x") * UPat.var("x")).reciprocal(), lambda x: x.reciprocal()*x.reciprocal()*x.reciprocal()),
|
||||
((UPat.var("x") * UPat.cvar("c")).reciprocal(), lambda x,c: x.reciprocal()*c.reciprocal()), # 1/(x*c) -> (1/c)*(1/x)
|
||||
|
||||
@@ -271,7 +271,7 @@
|
||||
}
|
||||
#device-list > div {
|
||||
min-height: 32px;
|
||||
width: 132px;
|
||||
width: 134px;
|
||||
overflow-x: auto;
|
||||
overflow-y: hidden;
|
||||
white-space: nowrap;
|
||||
|
||||
+20
-14
@@ -36,7 +36,7 @@ const updateProgress = ({ start, err }) => {
|
||||
d3.select("#custom").html("");
|
||||
if (err) {
|
||||
displaySelection("#custom");
|
||||
d3.select("#custom").append(() => d3.create("div").classed("raw-text", true).call(s => s.append(() => codeBlock(err, "txt"))).node());
|
||||
d3.select("#custom").append("div").classed("raw-text", true).call(s => s.append(() => codeBlock(err, "txt"))).node();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -149,7 +149,7 @@ function renderDag(graph, additions, recenter, layoutOpts) {
|
||||
|
||||
// ** profiler graph
|
||||
|
||||
function formatTime(ts, dur=ts) {
|
||||
function formatMicroseconds(ts, dur=ts) {
|
||||
if (dur<=1e3) return `${ts.toFixed(2)}us`;
|
||||
if (dur<=1e6) return `${(ts*1e-3).toFixed(2)}ms`;
|
||||
return `${(ts*1e-6).toFixed(2)}s`;
|
||||
@@ -158,7 +158,7 @@ const formatUnit = (d, unit="") => d3.format(".3~s")(d)+unit;
|
||||
|
||||
const colorScheme = {TINY:["#1b5745", "#354f52", "#354f52", "#1d2e62", "#63b0cd"],
|
||||
DEFAULT:["#2b2e39", "#2c2f3a", "#31343f", "#323544", "#2d303a", "#2e313c", "#343746", "#353847", "#3c4050", "#404459", "#444862", "#4a4e65"],
|
||||
BUFFER:["#342483", "#3E2E94", "#4938A4", "#5442B4", "#5E4CC2", "#674FCA"],
|
||||
BUFFER:["#342483", "#3E2E94", "#4938A4", "#5442B4", "#5E4CC2", "#674FCA"], SIMD:["#3600f0"],
|
||||
CATEGORICAL:["#ff8080", "#F4A261", "#C8F9D4", "#8D99AE", "#F4A261", "#ffffa2", "#ffffc0", "#87CEEB"],}
|
||||
const cycleColors = (lst, i) => lst[i%lst.length];
|
||||
|
||||
@@ -198,13 +198,17 @@ function focusShape(shape) {
|
||||
return metadata.replaceChildren(shapeMetadata.get(focusedShape) ?? "");
|
||||
}
|
||||
|
||||
async function renderProfiler() {
|
||||
const EventTypes = { EXEC:0, BUF:1 };
|
||||
|
||||
async function renderProfiler(path, unit) {
|
||||
displaySelection("#profiler");
|
||||
metadata.replaceChildren(shapeMetadata.get(focusedShape) ?? "");
|
||||
// layout once!
|
||||
if (data != null) return updateProgress({ start:false });
|
||||
if (data != null && data.path === path) return updateProgress({ start:false });
|
||||
// support non realtime x axis units
|
||||
const formatTime = unit === "realtime" ? formatMicroseconds : (s) => `${s} ${unit}`;
|
||||
const profiler = d3.select("#profiler").html("");
|
||||
const buf = await (await fetch("/get_profile")).arrayBuffer();
|
||||
const buf = await (await fetch(path)).arrayBuffer();
|
||||
const view = new DataView(buf);
|
||||
let offset = 0;
|
||||
const u8 = () => { const ret = view.getUint8(offset); offset += 1; return ret; }
|
||||
@@ -227,7 +231,7 @@ async function renderProfiler() {
|
||||
const colorMap = new Map();
|
||||
// map shapes by event key
|
||||
const shapeMap = new Map();
|
||||
data = {tracks:new Map(), axes:{}};
|
||||
data = {tracks:new Map(), axes:{}, path};
|
||||
const heightScale = d3.scaleLinear().domain([0, tracePeak]).range([4,maxheight=100]);
|
||||
for (let i=0; i<layoutsLen; i++) {
|
||||
const nameLen = view.getUint8(offset, true); offset += 1;
|
||||
@@ -236,12 +240,11 @@ async function renderProfiler() {
|
||||
const { y:baseY, height:baseHeight } = rect(div.node());
|
||||
const offsetY = baseY-canvasTop+padding/2;
|
||||
const shapes = [], visible = [];
|
||||
const EventTypes = {TIMELINE:0, MEMORY:1};
|
||||
const eventType = u8(), eventsLen = u32();
|
||||
if (eventType === EventTypes.TIMELINE) {
|
||||
if (eventType === EventTypes.EXEC) {
|
||||
const levelHeight = baseHeight-padding;
|
||||
const levels = [];
|
||||
data.tracks.set(k, { shapes, visible, offsetY, pcolor:"#9ea2ad" });
|
||||
data.tracks.set(k, { shapes, eventType, visible, offsetY, pcolor:"#9ea2ad" });
|
||||
let colorKey, ref;
|
||||
for (let j=0; j<eventsLen; j++) {
|
||||
const e = {name:strings[u32()], ref:optional(u32()), key:optional(u32()), st:u32(), dur:f32(), info:strings[u32()] || null};
|
||||
@@ -364,7 +367,8 @@ async function renderProfiler() {
|
||||
sum.x.push(allX[i], allX[i+1]);
|
||||
const y = maxY.get(allX[i]); sum.y1.push(y, y); sum.y0.push(base0, base0);
|
||||
}
|
||||
data.tracks.set(k, { shapes:[sum], visible, offsetY, pcolor:"#c9a8ff", height, peak, scaleFactor:maxheight*4/height, views:[[sum], shapes], valueMap });
|
||||
data.tracks.set(k, { shapes:[sum], eventType, visible, offsetY, pcolor:"#c9a8ff", height, peak, scaleFactor:maxheight*4/height,
|
||||
views:[[sum], shapes], valueMap });
|
||||
div.style("height", height+padding+"px").style("cursor", "pointer").on("click", (e) => {
|
||||
const newFocus = e.currentTarget.id === focusedDevice ? null : e.currentTarget.id;
|
||||
let offset = 0;
|
||||
@@ -394,11 +398,11 @@ async function renderProfiler() {
|
||||
xscale.domain(visibleX);
|
||||
// draw shapes
|
||||
const paths = [];
|
||||
for (const [_, { offsetY, shapes, visible, valueMap, pcolor }] of data.tracks) {
|
||||
for (const [_, { shapes, eventType, visible, offsetY, valueMap, pcolor }] of data.tracks) {
|
||||
visible.length = 0;
|
||||
for (const e of shapes) {
|
||||
const p = new Path2D();
|
||||
if (e.width == null) { // generic polygon
|
||||
if (eventType === EventTypes.BUF) { // generic polygon
|
||||
if (e.x[0]>et || e.x.at(-1)<st) continue;
|
||||
const x = e.x.map(xscale);
|
||||
p.moveTo(x[0], offsetY+e.y0[0]);
|
||||
@@ -479,6 +483,7 @@ async function renderProfiler() {
|
||||
d3.select(canvas).call(canvasZoom.transform, zoomLevel);
|
||||
}
|
||||
|
||||
zoomLevel = d3.zoomIdentity;
|
||||
canvasZoom = d3.zoom().filter(vizZoomFilter).scaleExtent([1, Infinity]).translateExtent([[0,0], [Infinity,0]]).on("zoom", e => render(e.transform));
|
||||
d3.select(canvas).call(canvasZoom);
|
||||
document.addEventListener("contextmenu", e => e.ctrlKey && e.preventDefault());
|
||||
@@ -691,13 +696,14 @@ async function main() {
|
||||
if (url.pathname+url.search !== ckey) e.close();
|
||||
else if (e.readyState === EventSource.OPEN) activeSrc = e;
|
||||
}
|
||||
if (ctx.name === "Profiler") return renderProfiler();
|
||||
if (ctx.name === "Profiler") return renderProfiler("/get_profile", "realtime");
|
||||
if (workerUrl == null) await initWorker();
|
||||
if (ckey in cache) {
|
||||
ret = cache[ckey];
|
||||
}
|
||||
// ** Disassembly view
|
||||
if (ckey.startsWith("/render")) {
|
||||
if (step.fmt === "timeline") return renderProfiler(ckey, "clk"); // cycles on the x axis
|
||||
if (!(ckey in cache)) cache[ckey] = ret = await (await fetch(ckey)).json();
|
||||
displaySelection("#custom");
|
||||
metadata.innerHTML = "";
|
||||
|
||||
+18
-9
@@ -215,10 +215,12 @@ def load_sqtt(profile:list[ProfileEvent]) -> None:
|
||||
except Exception: return err("DECODER ERROR")
|
||||
if not rctx.inst_execs: return err("EMPTY SQTT OUTPUT", f"{len(sqtt_events)} SQTT events recorded, none got decoded")
|
||||
steps:list[dict] = []
|
||||
units:set[str] = set()
|
||||
for name,waves in rctx.inst_execs.items():
|
||||
events:list[ProfileEvent] = []
|
||||
prg = trace.keys[r].ret if (r:=ref_map.get(name)) else None
|
||||
steps.append({"name":prg.name if prg is not None else name, "query":f"/render?ctx={len(ctxs)}&step={len(steps)}&fmt=counters",
|
||||
"depth":0, "data":{"src":prg.src if prg is not None else name, "lang":"cpp"}})
|
||||
steps.append(first:={"name":prg.name if prg is not None else name, "query":f"/render?ctx={len(ctxs)}&step={len(steps)}&fmt=counters",
|
||||
"depth":0, "fmt":"timeline"})
|
||||
|
||||
# Idle: The total time gap between the completion of previous instruction and the beginning of the current instruction.
|
||||
# The idle time can be caused by:
|
||||
@@ -228,14 +230,18 @@ def load_sqtt(profile:list[ProfileEvent]) -> None:
|
||||
# Stall: The total number of cycles the hardware pipe couldn't issue an instruction.
|
||||
# Duration: Total latency in cycles, defined as "Stall time + Issue time" for gfx9 or "Stall time + Execute time" for gfx10+.
|
||||
for w in waves:
|
||||
units.add(row:=f"SIMD:{w.simd} CU:{w.cu} SE:{w.se}")
|
||||
events.append(ProfileRangeEvent(row, wave_name:=f"wave {w.wave_id}", Decimal(w.begin_time), Decimal(w.end_time)))
|
||||
rows, prev_instr = [], w.begin_time
|
||||
for i,e in enumerate(w.insts):
|
||||
rows.append((e.inst, e.time, max(0, e.time-prev_instr), e.dur, e.stall, str(e.typ).split("_")[-1]))
|
||||
prev_instr = max(prev_instr, e.time + e.dur)
|
||||
summary = [{"label":"Total Cycles", "value":w.end_time-w.begin_time}, {"label":"CU", "value":w.cu},
|
||||
{"label":"SIMD", "value":w.simd}]
|
||||
steps.append({"name":f"Wave {w.wave_id}", "depth":1, "query":f"/render?ctx={len(ctxs)}&step={len(steps)}&fmt=counters",
|
||||
summary = [{"label":"Total Cycles", "value":w.end_time-w.begin_time}, {"label":"SIMD", "value":w.simd}, {"label":"CU", "value":w.cu},
|
||||
{"label":"SE", "value":w.se}]
|
||||
steps.append({"name":wave_name, "depth":1, "query":f"/render?ctx={len(ctxs)}&step={len(steps)}&fmt=counters",
|
||||
"data":{"rows":rows, "cols":["Instruction", "Clk", "Idle", "Duration", "Stall", "Type"], "summary":summary}})
|
||||
events = [ProfilePointEvent(unit, "start", unit, ts=Decimal(0)) for unit in units]+events
|
||||
first["data"] = {"value":get_profile(events), "content_type":"application/octet-stream"}
|
||||
ctxs.append({"name":"Counters", "steps":steps})
|
||||
|
||||
def get_profile(profile:list[ProfileEvent]) -> bytes|None:
|
||||
@@ -302,9 +308,9 @@ def get_stdout(f: Callable) -> str:
|
||||
except Exception: traceback.print_exc(file=buf)
|
||||
return buf.getvalue()
|
||||
|
||||
def get_render(i:int, j:int, fmt:str) -> dict|None:
|
||||
def get_render(i:int, j:int, fmt:str) -> dict:
|
||||
if fmt == "counters": return ctxs[i]["steps"][j]["data"]
|
||||
if not isinstance(prg:=trace.keys[i].ret, ProgramSpec): return None
|
||||
if not isinstance(prg:=trace.keys[i].ret, ProgramSpec): return {}
|
||||
if fmt == "uops": return {"src":get_stdout(lambda: print_uops(prg.uops or [])), "lang":"txt"}
|
||||
if fmt == "src": return {"src":prg.src, "lang":"cpp"}
|
||||
compiler = Device[prg.device].compiler
|
||||
@@ -336,11 +342,14 @@ class Handler(BaseHTTPRequestHandler):
|
||||
elif (query:=parse_qs(url.query)):
|
||||
if url.path == "/render":
|
||||
render_src = get_render(get_int(query, "ctx"), get_int(query, "step"), query["fmt"][0])
|
||||
ret, content_type = json.dumps(render_src).encode(), "application/json"
|
||||
if "content_type" in render_src: ret, content_type = render_src["value"], render_src["content_type"]
|
||||
else: ret, content_type = json.dumps(render_src).encode(), "application/json"
|
||||
else:
|
||||
try: return self.stream_json(get_full_rewrite(trace.rewrites[i:=get_int(query, "ctx")][get_int(query, "idx")], i))
|
||||
except (KeyError, IndexError): status_code = 404
|
||||
elif url.path == "/ctxs": ret, content_type = json.dumps(ctxs).encode(), "application/json"
|
||||
elif url.path == "/ctxs":
|
||||
lst = [{**c, "steps":[{k:v for k, v in s.items() if k != "data"} for s in c["steps"]]} for c in ctxs]
|
||||
ret, content_type = json.dumps(lst).encode(), "application/json"
|
||||
elif url.path == "/get_profile" and profile_ret: ret, content_type = profile_ret, "application/octet-stream"
|
||||
else: status_code = 404
|
||||
|
||||
|
||||
Reference in New Issue
Block a user