PyTorch eager
Gemm Scale BatchNorm · batch_size = 1024 · in_features = 8192 · fp32 · run 01a03f0e-f6d4…
●passedReported evidence
Not re-observed recently.
Primary measurement
2.76ms±0.00 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 2.78 · min ms 2.76 · std ms 0.00164 · mean ms 2.76
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 1024 · in_features = 8192 · fp32
comparison keysha256:d1b6b98fcc813d74…
sourceKernelBench baseline timings
external idH100_Modal/torch/level2/33_Gemm_Scale_BatchNorm.py
sha256:ef4bbf8b99b8b11bedb68ee…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size1024
in_features8192
input_1fp32 [1024, 8192]
definition comparatornot_asserted
Measurements
latency · max2.78 ms · n=100
latency · mean2.76 ms · n=100
latency · min2.76 ms · n=100
latency · std1.64 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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{
"run": {
"kind": "BenchmarkRun",
"spec": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 2760000,
"maximum": 2780000,
"minimum": 2760000,
"confidence95": [
2760000,
2760321
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 1640,
"metric": "latency",
"statistic": "std"
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],
"sourceNative": {
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},
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"metadata": {
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},
"apiVersion": "kernelindex.dev/v1alpha1"
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"protocol": {
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"spec": {
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},
"comparability": {
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"family": "kernelbench_baseline_timing"
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},
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},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}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