PyTorch eager
Gemm Scaling Hardtanh GELU · batch_size = 2048 · in_features = 8192 · fp32 · run 01a03f0e-f83b…
●passedReported evidence
Not re-observed recently.
Primary measurement
8.20ms±0.04 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 8.87 · min ms 7.81 · std ms 0.196 · mean ms 8.2
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 2048 · in_features = 8192 · fp32
comparison keysha256:72b28e9aba01c8c0…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/53_Gemm_Scaling_Hardtanh_GELU.py
sha256:7b3b753dd7a1e0ac026c5ff…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size2048
in_features8192
input_1fp32 [2048, 8192]
definition comparatornot_asserted
Measurements
latency · max8.87 ms · n=100
latency · mean8.20 ms · n=100
latency · min7.81 ms · n=100
latency · std196.0 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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{
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},
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"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
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},
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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 Scaling Hardtanh GELU →JSON