PyTorch eager
Matmul Dropout Softmax · batch_size = 128 · in_features = 16384 · fp32 · run 01a03f0e-f83c…
●passedReported evidence
Not re-observed recently.
Primary measurement
2.17ms±0.01 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 2.19 · min ms 2.1 · std ms 0.0354 · mean ms 2.17
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 128 · in_features = 16384 · fp32
comparison keysha256:a60dee467f5af014…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/66_Matmul_Dropout_Softmax.py
sha256:c54a65530c45f69394210ab…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size128
in_features16384
input_1fp32 [128, 16384]
definition comparatornot_asserted
Measurements
latency · max2.19 ms · n=100
latency · mean2.17 ms · n=100
latency · min2.10 ms · n=100
latency · std35.4 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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}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Matmul Dropout Softmax →JSON