PyTorch eager
Gemm Scale BatchNorm · batch_size = 16384 · in_features = 4096 · fp32 · run 01a03f0e-f83a…
●passedReported evidence
Not re-observed recently.
Primary measurement
16.9ms±0.11 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 18.2 · min ms 15.8 · std ms 0.582 · mean ms 16.9
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 16384 · in_features = 4096 · fp32
comparison keysha256:3bbda2f81219fdaa…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/39_Gemm_Scale_BatchNorm.py
sha256:ecf0f5a89becdfecd0ef157…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size16384
in_features4096
input_1fp32 [16384, 4096]
definition comparatornot_asserted
Measurements
latency · max18.2 ms · n=100
latency · mean16.9 ms · n=100
latency · min15.8 ms · n=100
latency · std582.0 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.
Add a reproduction or note
Canonical manifest
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{
"run": {
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"spec": {
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"timing": {
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"latencyNs": {
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"confidence95": [
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]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
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"sourceNative": {
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},
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"metadata": {
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"title": "Gemm Scale BatchNorm · PyTorch eager · Lambda Labs"
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"apiVersion": "kernelindex.dev/v1alpha1"
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"protocol": {
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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 Gemm Scale BatchNorm →JSON