PyTorch eager
RMSNorm · dim1 = 512 · dim2 = 512 · features = 64 · batch_size = 112 · fp32 · run 01a03f0e-f832…
●passedReported evidence
Not re-observed recently.
Primary measurement
21.7ms±0.01 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 21.8 · min ms 21.6 · std ms 0.0477 · mean ms 21.7
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddim1 = 512 · dim2 = 512 · features = 64 · batch_size = 112 · fp32
comparison keysha256:998ffa61f4c855f7…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/36_RMSNorm_.py
sha256:e419b5cb835d30068e27ed9…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
dim1512
dim2512
features64
batch_size112
xfp32 [112, 64, 512, 512]
definition comparatornot_asserted
Measurements
latency · max21.8 ms · n=100
latency · mean21.7 ms · n=100
latency · min21.6 ms · n=100
latency · std47.7 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": {
"kind": "BenchmarkRun",
"spec": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 21700000,
"maximum": 21800000,
"minimum": 21600000,
"confidence95": [
21690651,
21709349
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 47700,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 21.8,
"min_ms": 21.6,
"std_ms": 0.0477,
"mean_ms": 21.7
},
"benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch.json",
"externalId": "H100_PCIe_LambdaLabs/torch/level1/36_RMSNorm_.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:411aad815c3684ff087c6c156438eff3f6845e6cba26a140fd43323feef8b0c6",
"environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
"implementationDigest": "sha256:e1c667b4fd8bb3f0ba3b645b30129691e3d856a90671fde39c13dff29265124b"
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs-torch-l1-36-rmsnorm",
"title": "RMSNorm · PyTorch eager · Lambda Labs"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
"name": "KernelBench timing scripts",
"repository": "https://github.com/ScalingIntelligence/KernelBench"
},
"measurement": {
"timer": "cuda_events",
"primaryStatistic": "mean"
},
"comparability": {
"notes": "Mean of 100 timed forward passes (CUDA events, warm-up excluded) of the reference module on fixed inputs; the 95% interval is the mean's, from the reported standard deviation. The upstream JSON records no torch or CUDA version. Comparable only within one problem and one timing host.",
"family": "kernelbench_baseline_timing"
}
},
"metadata": {
"name": "kernelbench-timing-v1",
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},
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"environment": {
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"spec": {
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},
"software": {}
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"title": "KernelBench host · H100 PCIe (Lambda Labs)"
},
"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 RMSNorm →JSON