submission 529363
ry2009 · python · License unknown
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Vendorable · source mirrored · license unknownView source →
No package. Vendor the mirrored source: 36 lines, June 9 Researcher Reciprocity License v1.0.
submission_tunedcsv_real_v46.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-amd-mxfp4-mm-529363?include=source"interfacepython
Compatibility
measured onAMD Instinct MI355X
declared hardwareAMD Instinct MI355X
architecturesgfx950
dtypesbf16, mxfp4
Benchmark evidence
1 measurement across 1 GPU, fastest first.
Operation / workload
Hardware
Latency
Rank
Observed
Reported · How evidence levels are derived →
Source and license
sourceavailable
revision digestsha256:634020d953a9d7a16579464a8286c216cd3244380061e54207b097c19e683f2e
license declaredunknown
license concludedunknown
authorsry2009
imported2026-08-26
Techniques
Extracted from the mirrored source by pattern, never inferred. Each row cites its line.
split-k
'cu_num,M,N,K,kernelId,splitK,us,kernelName,tflops,bw,errRatio\n'Kernel source
submission_tunedcsv_real_v46.py36 lines
#!POPCORN leaderboard amd-mxfp4-mm
#!POPCORN gpu MI355X
import os
from pathlib import Path
_CFG = Path('/tmp/submission_tunedcsv_real_v46.csv')
if not _CFG.exists():
_CFG.write_text(
'cu_num,M,N,K,kernelId,splitK,us,kernelName,tflops,bw,errRatio\n'
'256,4,2880,512,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,8,2112,7168,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,16,2112,7168,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,16,3072,1536,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,32,4096,512,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,32,2880,512,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,64,7168,2048,21,1,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,64,3072,1536,21,0,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
'256,256,3072,1536,21,1,0.0,_ZN5aiter41f4gemm_bf16_per1x32Fp4_BpreShuffle_32x128E,0.0,0.0,0.0\n'
)
os.environ['AITER_CONFIG_GEMM_A4W4'] = str(_CFG)
import torch
from task import input_t, output_t
import aiter
from aiter import QuantType, dtypes
QF = aiter.get_triton_quant(QuantType.per_1x32)
GEMM = aiter.gemm_a4w4
@torch.inference_mode()
def custom_kernel(data: input_t) -> output_t:
A, _B, _B_q, B_shuffle, B_scale_sh = data
A_q, A_scale_sh = QF(A, shuffle=True)
return GEMM(A_q, B_shuffle, A_scale_sh, B_scale_sh, dtype=dtypes.bf16, bpreshuffle=True)
scrolls · 36 lines total
Source code from GPU Mode and the KernelBot dataset · June 9 Researcher Reciprocity License v1.0
Best evidence level for this revision: reported
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