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Author SHA1 Message Date
geohot 82aa943cd4 fix that test 2025-11-19 08:48:49 -08:00
George HotzandGitHub e16782cf9e Merge branch 'master' into python_speed 2025-11-19 08:41:40 -08:00
geohot 1c47ee729e fix names of rewrite rules 2025-11-19 08:41:34 -08:00
geohot a8f9e69bd9 work on python speed 2025-11-19 08:34:15 -08:00
George HotzandGitHub 385618d45b skip process replay by default (#13353) 2025-11-19 08:25:34 -08:00
geohot ffff194e93 skip process replay by default 2025-11-19 08:14:44 -08:00
chenyuandGitHub fba4535289 remove hacks for threefry long removal when padded [pr] (#13352) 2025-11-19 11:11:39 -05:00
George HotzandGitHub 225eb1500f generic range changes that work for str + int (#13350)
* generic range changes that work for str + int

* opt range counts up
2025-11-19 08:07:49 -08:00
chenyuandGitHub 1a72ac16a6 move where same false branch rule to symbolic_simple [pr] (#13349) 2025-11-19 10:15:38 -05:00
chenyuandGitHub 79055ddb8b clean propagate_invalid more [pr] (#13347) 2025-11-19 09:47:50 -05:00
nimlgenandGitHub 0c9fbf87e1 nvioctl: classes (#13346) 2025-11-19 16:14:15 +03:00
qazalandGitHub f2221130bb viz: pick shape by event type (#13279) 2025-11-19 20:15:52 +08:00
wozeparrotandGitHub be72b78dcb tk: small fixes (#13345)
* fix: handle case where final uop isn't a tk wrapped one

* clean: remove after from mma
2025-11-19 00:58:50 -08:00
wozeparrotandGitHub e4fbde5b3b fix: extra options need to go on second step too (#13344) 2025-11-19 00:58:09 -08:00
George HotzandGitHub 1a332afa76 spec test on 3.14 (#12957) 2025-11-19 00:43:04 -08:00
sirhcmandGitHub a438c277de autogen tests for 3.14 (#13343) 2025-11-18 22:16:59 -05:00
chenyuandGitHub 722e7a16ed remove rule in propagate_invalid [pr] (#13342) 2025-11-18 21:38:33 -05:00
George HotzandGitHub 1afa3c0877 vmap on full model (#13340)
* vmap on full model

* vmap gemm

* reduce sums on end

* outer reduce

* only if there's ranges

* put those rules in symbolic

* ranges

* do opt later

* add zero range
2025-11-18 16:06:06 -08:00
chenyuandGitHub 46cb65e692 delete rules from sym [pr] (#13339) 2025-11-18 14:57:35 -05:00
George HotzandGitHub 9c59b3d19e vmap grad needs reduce_backward (#13336)
* vmap grad needs reduce_backward

* fuse and outer
2025-11-18 10:08:30 -08:00
qazalandGitHub a647c9eca6 sqtt ui minor fixes (#13335)
* roc.py cleanups

* direct append

* viz index cleanup

* simd row details
2025-11-19 01:27:56 +08:00
George HotzandGitHub 06e39a88a9 outer vmap works (#13334)
* outer vmap works

* fuse works

* vmap outer works

* outer ranges work

* grad work

* should be good to merge
2025-11-18 09:27:48 -08:00
chenyuandGitHub 805de27e07 no load substitute in uop_given_valid [pr] (#13333) 2025-11-18 11:47:58 -05:00
chenyuandGitHub 05294bc648 fix some mypy cast [pr] (#13331) 2025-11-18 09:23:42 -05:00
qazalandGitHub 5623e765c8 VIZ=2 enables SQTT (#13330) 2025-11-18 22:20:31 +08:00
nimlgenandGitHub 331f70aa75 roc: ctrlc (#13255)
* roc: ctrl-c works

* rm
2025-11-18 19:29:28 +08:00
George HotzandGitHub 583560ab72 this is the right way to write vmap (#13328) 2025-11-17 20:20:52 -08:00
sirhcmandGitHub 8e8e53c886 int8_t is c_byte (#13326) 2025-11-17 21:25:40 -05:00
George HotzandGitHub e4fead8a86 write scan in uops (#13321)
* write scan in uops

* ops range

* no need for variable

* meh, later

* shorter
2025-11-17 16:58:08 -08:00
wozeparrotandGitHub 8894a5409d feat: hipcc compiler (#13319) 2025-11-17 15:13:32 -08:00
George HotzandGitHub 6d3385c284 print special ops in postrange (#13318)
* print special ops in postrange

* fix on OSX
2025-11-17 14:43:23 -08:00
chenyuandGitHub b637093be9 remove a few rules in pm_lower_index_dtype [pr] (#13317) 2025-11-17 17:04:56 -05:00
geohot 98e9e73286 hotfix: amd_uop_matmul getenvs 2025-11-17 13:26:01 -08:00
qazalandGitHub e7e1935225 cleanup sqtt/test_timing (#13315) 2025-11-18 04:28:05 +08:00
wozeparrotandGitHub 33773fda87 tk initial mi350 (#13289) 2025-11-17 11:46:32 -08:00
nimlgenandGitHub e2cee64050 Revert "hcq: add tag to exec events (#13311)" (#13314)
This reverts commit f63ded5817.
2025-11-17 22:15:31 +03:00
chenyuandGitHub 646372490c move tiktoken import in llama3 (#13316)
only Tokenizer requires that
2025-11-17 14:09:37 -05:00
qazalandGitHub a37f221e44 viz: visualize waves in the timeline (#13292)
* viz: visualize waves in the timeline

* timeline in format

* per step

* rm that
2025-11-17 22:04:21 +08:00
nimlgenandGitHub f63ded5817 hcq: add tag to exec events (#13311)
* hcq: add tag to exec events

* f

* fix

* fix
2025-11-17 16:59:30 +03:00
qazalandGitHub 50a443f558 viz: add shader engine to wave exec payload (#13310)
* viz: show sqtt shader engine

* order it from smallest unit

* easier to config
2025-11-17 19:11:34 +08:00
nimlgenandGitHub 9bb17c53ea amd: timer fix (#13267) 2025-11-17 13:59:03 +03:00
George HotzandGitHub 55be95da15 cleanup sqtt raw parser (#13309)
* cleanup sqtt raw parser

* better names (don't merge yet)

* clean up amd

* a few more names

* one more filter
2025-11-16 13:11:51 -08:00
George HotzandGitHub cabd4add48 more work parsing SQTT, separate VIZ/PROFILE (#13308)
* more work parsing SQTT

* more minimal runner

* sep VIZ/PROFILE

* parse print new

* improve parser

* more filter

* that

* split them

* lil cleanup

* skip flaky test

* AQL in mmapeak
2025-11-16 10:40:39 -08:00
qazalandGitHub 13efdf8c31 test s_nop stall (#13307) 2025-11-17 00:59:39 +08:00
George HotzandGitHub 295600dc5a saturday coffee shop work parsing the att format (#13295)
* saturday coffee shop work parsing the att format

* add examples

* parser

* classes of packets

* fully vibe coded parser

* vibing

* empty

* some vibe names

* vibes

* most of these are wrong

* more vibes

* better names

* parsing

* parse

* cleanup parser

* touchups
2025-11-16 08:25:51 -08:00
sirhcmandGitHub a9ed241172 properly suppress NIRRenderer.__del__ error (#13299) 2025-11-16 18:58:04 +03:00
qazalandGitHub c70b06ec19 sqtt test_timing work (#13304)
* sqtt test_timing cleanups

* only the instruction

* v_mfma_f32_16x16x32_f16 16 cycles, only after second one though
2025-11-16 23:49:24 +08:00
chenyuandGitHub 8f0e747b3a Tensor._tri with arange (#13297) 2025-11-16 10:21:16 -05:00
chenyuandGitHub 6372c95094 disable benchmark MobileNetV2 on DSP (#13305)
failed on tinyc2
2025-11-16 09:42:52 -05:00
sirhcmandGitHub 61625a3898 fix objc finalizing bug (#13296) 2025-11-16 12:43:04 +03:00
nimlgenandGitHub acbe6361ab qcom: suppress_finalizing to free (#13294) 2025-11-16 11:49:23 +03:00
55 changed files with 1102 additions and 241 deletions
+8 -8
View File
@@ -643,14 +643,14 @@ jobs:
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
- name: openpilot compile3 0.10.1 dmonitoring
run: BENCHMARK_LOG=openpilot_0_10_1_dmonitoring PYTHONPATH="." ASSERT_MIN_STEP_TIME=10 DEV=QCOM FLOAT16=1 IMAGE=2 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/720392c9a5b986981fdbed1bb8c47a6c5573a50e/selfdrive/modeld/models/dmonitoring_model.onnx
- name: benchmark MobileNetV2 on DSP
run: |
# generate quantized weights
ln -s /data/home/tiny/tinygrad/extra/datasets/imagenet extra/datasets/imagenet
ln -s /data/home/tiny/tinygrad/testsig-*.so .
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
# benchmark on DSP with NOOPT=1, the devectorizer has issues
PYTHONPATH=. CC=clang-19 DSP=1 NOOPT=1 CNT=2 DEBUG=2 python3 examples/test_onnx_imagenet.py /tmp/model.quant.onnx
# - name: benchmark MobileNetV2 on DSP
# run: |
# # generate quantized weights
# ln -s /data/home/tiny/tinygrad/extra/datasets/imagenet extra/datasets/imagenet
# ln -s /data/home/tiny/tinygrad/testsig-*.so .
# 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
# # benchmark on DSP with NOOPT=1, the devectorizer has issues
# PYTHONPATH=. CC=clang-19 DSP=1 NOOPT=1 CNT=2 DEBUG=2 python3 examples/test_onnx_imagenet.py /tmp/model.quant.onnx
- name: Run process replay tests
run: cp test/external/process_replay/process_replay.py ./process_replay.py && git fetch origin master && git -c advice.detachedHead=false checkout origin/master && PYTHONPATH=. python3 process_replay.py
+1
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@@ -306,6 +306,7 @@ jobs:
with:
key: spec-unit
deps: testing_unit
python-version: '3.14'
- name: Test SPEC=2
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 }}
+2 -2
View File
@@ -1,8 +1,6 @@
from pathlib import Path
from typing import List
import json, argparse, random, time, os
import tiktoken
from tiktoken.load import load_tiktoken_bpe
from extra.models.llama import Transformer, convert_from_huggingface, convert_from_gguf, fix_bf16
from tinygrad.nn.state import safe_load, torch_load, load_state_dict, get_parameters, gguf_load
from tinygrad import Tensor, dtypes, nn, Context, Device, GlobalCounters
@@ -12,6 +10,8 @@ from extra.bench_log import BenchEvent, WallTimeEvent
class Tokenizer:
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+"
def __init__(self, model_path: str):
import tiktoken
from tiktoken.load import load_tiktoken_bpe
mergeable_ranks = load_tiktoken_bpe(model_path)
self.num_base_tokens = len(mergeable_ranks)
special_tokens = [
+11 -10
View File
@@ -4,9 +4,9 @@ from tinygrad.engine.realize import ExecItem, get_runner
from tinygrad.dtype import AddrSpace
from tinygrad.helpers import getenv
N = 4096
N = getenv("N", 4096)
M = K = N
run_count = 5
run_count = getenv("CNT", 5)
# ---------------------------
# launch/config constants
@@ -155,14 +155,15 @@ def test_matmul(sink:UOp, N=N):
ets.append(ei.run(wait=True))
print(f"REAL TFLOPS {N * N * N * 2 / min(ets) * 1e-12:.2f}")
GlobalCounters.reset()
with Context(DEBUG=2):
tc = (a @ b).realize()
with Context(DEBUG=0):
err = (hc - tc).square().mean().item()
print(f"mean squared error {err}")
if err > 1e-06:
raise RuntimeError("matmul is wrong!")
if getenv("VERIFY", 1):
GlobalCounters.reset()
with Context(DEBUG=2):
tc = (a @ b).realize()
with Context(DEBUG=0):
err = (hc - tc).square().mean().item()
print(f"mean squared error {err}")
if err > 1e-06:
raise RuntimeError("matmul is wrong!")
if __name__ == "__main__":
test_matmul(hand_spec_kernel3(), N=N)
+8 -6
View File
@@ -1,8 +1,10 @@
import pathlib
import os, pathlib
# 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
import time
import os
NUM_WORKGROUPS = 96
WAVE_SIZE = 32
@@ -44,9 +46,9 @@ if __name__=="__main__":
raise RuntimeError("Error while initiating AMD device")
COMPILER = HIPCompiler(DEV.arch)
if DEV.arch in {'gfx1100', 'gfx1103'}:
if DEV.arch == 'gfx1103':
NUM_WORKGROUPS = 8
if DEV.arch in {'gfx1100', 'gfx1103', 'gfx1151'}:
if DEV.arch == 'gfx1103': NUM_WORKGROUPS = 8
if DEV.arch == 'gfx1151': NUM_WORKGROUPS = 40
launchBenchmark("v_wmma_bf16_16x16x16_bf16", (7,8,15))
launchBenchmark("v_wmma_f16_16x16x16_f16", (7,8,15))
launchBenchmark("v_wmma_f32_16x16x16_bf16", (7,8,15))
+9 -6
View File
@@ -64,14 +64,17 @@ nvcmds = {getattr(nv_gpu, x):(x, getattr(nv_gpu, "struct_"+x+"_PARAMS", getattr(
x.startswith("NV") and x[6:].startswith("_CTRL_") and isinstance(getattr(nv_gpu, x), int)}
def get_classes():
hdrpy = (pathlib.Path(__file__).parent.parent.parent / "tinygrad/runtime/autogen/nv_570.py").read_text()
clss = re.search(r'NV01_ROOT.*?NV_SEMAPHORE_SURFACE = \(0x000000da\) # macro', hdrpy, re.DOTALL).group()
pattern = r'([0-9a-zA-Z_]*) = +\((0x[0-9a-fA-F]+)\)'
matches = re.findall(pattern, clss, re.MULTILINE)
return {int(num, base=16):name for name, num in matches}
res = {}
known_classes = {"NV01_DEVICE_0", "NV01_ROOT", "NV1_MEMORY_SYSTEM", "NV01_MEMORY_VIRTUAL", "NV1_MEMORY_USER", "NV50_MEMORY_VIRTUAL", "NV_FERMI_VASPACE_A",
"NV20_SUBDEVICE_0"}
for nm,val in nv_gpu.__dict__.items():
if not isinstance(val, int): continue
if 0x3000 < val < 0xffff: res[val] = nm
if nm in known_classes: res[val] = nm
return res
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 = []
+131
View File
@@ -0,0 +1,131 @@
import os
os.environ["PYTHONPATH"] = "."
os.environ["SQTT"] = "1"
if "DEV" not in os.environ: os.environ["DEV"] = "AMD"
os.environ["PROFILE"] = "1"
os.environ["AMD_LLVM"] = "0"
from dataclasses import replace
import atexit, contextlib
from tinygrad import Tensor
from tinygrad.helpers import system, OSX
from tinygrad.runtime.ops_amd import AMDProgram
from extra.sqtt.roc import decode, WaveExec, ProfileSQTTEvent
from tinygrad.device import Device, 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")
set_power("stable_std")
dev = Device["AMD"]
@contextlib.contextmanager
def save_sqtt():
# clear the old traces
dev.profile_events.clear()
sqtt:dict[str, list[WaveExec]] = {}
yield sqtt
events = dev.profile_events+[ProfileDeviceEvent("AMD", props=dev.device_props())]
rctx = decode(events)
assert len(rctx.inst_execs) > 0, "empty sqtt output"
sqtt.update(rctx.inst_execs)
for e in events:
if isinstance(e, ProfileSQTTEvent):
print(replace(e, blob=b''))
if e.se == 0:
parse_sqtt_print_packets(e.blob)
template = """.text
.globl matmul
.p2align 8
.type matmul,@function
matmul:
INSTRUCTION
s_endpgm
.rodata
.p2align 6
.amdhsa_kernel matmul
.amdhsa_user_sgpr_kernarg_segment_ptr 1
.amdhsa_next_free_vgpr .amdgcn.next_free_vgpr
.amdhsa_next_free_sgpr .amdgcn.next_free_sgpr
.amdhsa_wavefront_size32 1
.end_amdhsa_kernel
.amdgpu_metadata
---
amdhsa.version:
- 1
- 0
amdhsa.kernels:
- .name: matmul
.symbol: matmul.kd
.group_segment_fixed_size: 0
.private_segment_fixed_size: 0
.wavefront_size: 32
.sgpr_count: 8
.vgpr_count: 32
.max_flat_workgroup_size: 1024
.kernarg_segment_align: 8
.kernarg_segment_size: 8
.args:
- .address_space: global
.name: a
.offset: 0
.size: 8
.type_name: 'float*'
.value_kind: global_buffer
...
.end_amdgpu_metadata
"""
def run_asm(src):
NUM_WORKGROUPS = 1
WAVE_SIZE = 32
NUM_WAVES = 1
t = Tensor.empty(0x1000).realize()
buf = t.uop.buffer.ensure_allocated()
lib = dev.compiler.compile(template.replace("INSTRUCTION", '\n'.join(src)))
dev.compiler.disassemble(lib)
fxn = AMDProgram(dev, "matmul", lib)
fxn(buf._buf, global_size=(NUM_WORKGROUPS,1,1), local_size=(WAVE_SIZE*NUM_WAVES,1,1), wait=True)
if __name__ == "__main__":
with save_sqtt() as sqtt:
#(Tensor.empty(16,16) @ Tensor.empty(16,16)).elu().realize()
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)
+543
View File
@@ -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",
# ------------------------------------------------------------------------
# 0x070x0F: 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
# ------------------------------------------------------------------------
# 0x100x19: 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, 0x0A0x0E, 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 (0x010x06)
# =====================================================================
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:])
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+15 -10
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@@ -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
View File
@@ -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()
+6 -1
View File
@@ -1 +1,6 @@
WARP_THREADS = 32
from tinygrad.device import Device
if Device.DEFAULT == "AMD":
WARP_THREADS = 64
else:
WARP_THREADS = 32
+6 -6
View File
@@ -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)
+5 -1
View File
@@ -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
View File
@@ -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
View File
@@ -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
+1
View File
@@ -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):
+10
View File
@@ -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):
+5
View File
@@ -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
View File
@@ -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()
+1 -1
View File
@@ -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
View File
@@ -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])
View File
+1 -1
View File
@@ -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")
+4 -4
View File
@@ -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)
+9
View File
@@ -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()
+1
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@@ -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):
+4
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@@ -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):
+9 -8
View File
@@ -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
View File
@@ -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
+5 -3
View File
@@ -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
View File
@@ -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
View File
@@ -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)
+2 -3
View File
@@ -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")
+1 -1
View File
@@ -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),
+2 -2
View File
@@ -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),
+6 -3
View File
@@ -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),
+2 -1
View File
@@ -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)
+1 -1
View File
@@ -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")]}}
+20 -2
View File
@@ -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"
+3 -1
View File
@@ -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)
+2
View File
@@ -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)
+20 -4
View File
@@ -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
View File
@@ -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
View File
@@ -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:
+2 -2
View File
@@ -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
View File
@@ -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)
+1 -1
View File
@@ -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
View File
@@ -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
View File
@@ -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