PyTorch eager
Matmul GroupNorm LeakyReLU Sum · batch_size = 1024 · input_size = 8192 · fp32 · run 01a03f0e-f6d6…
●passedReported evidence
Not re-observed recently.
Primary measurement
3.09ms±0.00 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 3.09 · min ms 3.08 · std ms 0.00155 · mean ms 3.09
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 1024 · input_size = 8192 · fp32
comparison keysha256:45e19d954badfc4e…
sourceKernelBench baseline timings
external idH100_Modal/torch/level2/62_Matmul_GroupNorm_LeakyReLU_Sum.py
sha256:cf9e9ddb341e26aea439dd7…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size1024
input_size8192
input_1fp32 [1024, 8192]
definition comparatornot_asserted
Measurements
latency · max3.09 ms · n=100
latency · mean3.09 ms · n=100
latency · min3.08 ms · n=100
latency · std1.55 µs
Protocol
harnessKernelBench timing scripts
timercuda_events
primaryStatisticmean
comparabilityFamilykernelbench_baseline_timing
Environment
gpuNVIDIA H100 (sm_90)
Artifacts
No artifacts published with this run.
Replications and notes
No attestations yet.
Community attestations. They never change the evidence level; only a KernelIndex-controlled rerun does.
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Canonical manifest
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{
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"spec": {
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"timing": {
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"latencyNs": {
"mean": 3090000,
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"minimum": 3080000,
"confidence95": [
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]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
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},
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"metadata": {
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"title": "Matmul GroupNorm LeakyReLU Sum · PyTorch eager · Modal"
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"comparability": {
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}
}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Matmul GroupNorm LeakyReLU Sum →JSON