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// | |
// Generated by LLVM NVPTX Back-End | |
// | |
.version 8.7 | |
.target sm_90a | |
.address_size 64 | |
// .globl _layer_norm_backward_kernel // -- Begin function _layer_norm_backward_kernel | |
.extern .shared .align 16 .b8 global_smem[]; |
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// | |
// Generated by LLVM NVPTX Back-End | |
// | |
.version 8.7 | |
.target sm_90a | |
.address_size 64 | |
// .globl _layer_norm_backward_kernel // -- Begin function _layer_norm_backward_kernel | |
.extern .shared .align 16 .b8 global_smem[]; |
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#!/usr/bin/env python3 | |
import argparse | |
import os | |
import sys | |
import stat | |
import subprocess | |
import re | |
def parse_glibcxx_version(version_string): |
We can make this file beautiful and searchable if this error is corrected: Unclosed quoted field in line 9.
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metric_id,Samples (3.3),Samples (3.4),speedup (3.3),speedup (3.4),speedup ((new-old)/old),speedup (delta) | |
tritonbench_ragged_attention_bwd[hstu]-tflops-avg,0,1,0,98.806091308594,-1,-98.806091308594 | |
"tritonbench_ragged_attention_bwd[x_(128, 4, 1024, 128, 128, 1.0, 20, 0)-hstu]_tflops",0,1,0,132.42012023926,-1,-132.42012023926 | |
"tritonbench_ragged_attention_bwd[x_(128, 4, 256, 128, 128, 1.0, 20, 0)-hstu]_tflops",0,1,0,65.420997619629,-1,-65.420997619629 | |
"tritonbench_ragged_attention_bwd[x_(128, 4, 512, 128, 128, 1.0, 20, 0)-hstu]_tflops",0,1,0,98.577156066895,-1,-98.577156066895 | |
tritonbench_ragged_attention_bwd[x_average-hstu]_tflops,0,1,0,98.806091308594,-1,-98.806091308594 | |
"tritonbench_fp8_gemm_blockwise_fwd[x_(128, 2304, 6656)-_triton]_speedup",1,1,0.60214412212372,0.79111462831497,-0.23886615090629,-0.18897050619125 | |
"tritonbench_fp8_gemm_blockwise_fwd[x_(128, 2304, 6656)-_triton]_tflops",1,1,73.069320678711,95.622283935547,-0.23585468081935,-22.552963256836 | |
"tritonbench_int4_gemm_fwd[x_(16, 1, 8192, |
We can make this file beautiful and searchable if this error is corrected: Unclosed quoted field in line 9.
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metric_id,Samples (3.3),Samples (3.4),speedup (3.3),speedup (3.4),speedup difference ((new-old)/old),speedup (delta) | |
tritonbench_fused_linear_jsd_bwd-pass,1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_ (8, 16, 8192, 16, 8192, 128) | noop-compiled]_speedup",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_ (8, 16, 8192, 16, 8192, 128) | noop-compiled]_tflops",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_ (8, 16, 8192, 16, 8192, 128) | noop-eager]_tflops",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_(8, 16, 16384, 16, 16384, 128) | noop-compiled]_speedup",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_(8, 16, 16384, 16, 16384, 128) | noop-compiled]_tflops",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_fwd[x_(8, 16, 16384, 16, 16384, 128) | noop-eager]_tflops",1,1,0,0,3.4028235e+38,0 | |
"tritonbench_flex_attention_bwd[x_ (8, 16, 8192, 16, 8192, 128) | noop-compile |
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import argparse | |
import torch | |
import triton # @manual=//triton:triton | |
import triton.language as tl # @manual=//triton:triton | |
# best config selected: BLOCK_SIZE_M: 128, BLOCK_SIZE_N: 256, BLOCK_SIZE_K: 128, GROUP_SIZE_M: 8, num_warps: 8, num_ctas: 1, num_stages: 3, maxnreg: None; | |
def get_cuda_autotune_config(): |
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#loc = loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0) | |
module { | |
tt.func public @triton_tem_fused_zeros_7(%arg0: !tt.ptr<bf16> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0), %arg1: !tt.ptr<bf16> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0), %arg2: !tt.ptr<bf16> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0), %arg3: !tt.ptr<f32> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0), %arg4: !tt.ptr<f32> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6pyu3d4c6muk2u.py":17:0), %arg5: !tt.ptr<bf16> {tt.divisibility = 16 : i32} loc("/tmp/torchinductor_dberard/gy/cgy5zvgvr3m2yfnc7jim2n7k35hawsgtqmr2ap6 |
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# AOT ID: ['0_backward'] | |
from ctypes import c_void_p, c_long, c_int | |
import torch | |
import math | |
import random | |
import os | |
import tempfile | |
from math import inf, nan | |
from cmath import nanj | |
from torch._inductor.hooks import run_intermediate_hooks |
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AUTOTUNE addmm(4096x16, 4096x3, 3x16) | |
triton_mm_4 0.0034 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=2, num_warps=4 | |
triton_mm_5 0.0035 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=3, num_warps=4 | |
triton_mm_2 0.0035 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=5, num_warps=2 | |
triton_mm_3 0.0035 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=5, num_warps=4 | |
triton_mm_6 0.0035 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=4, num_warps=4 | |
triton_mm_8 0.0035 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, num_stages=4, num_warps=8 | |
triton_mm_10 0.0035 ms 96.4% ACC_TYPE='t |
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============================= test session starts ============================== | |
platform linux -- Python 3.12.9, pytest-8.3.5, pluggy-1.5.0 | |
rootdir: /workspace/triton/python | |
configfile: pyproject.toml | |
collected 21530 items | |
unit/blackwell/test_tmem.py s [ 0%] | |
unit/cuda/test_experimental_tma.py .........F.......F................... [ 0%] | |
......................s..s................................s..s.......... [ 0%] | |
......................s..s.....s..s.....s..s.....s..s................... [ 0%] |
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