torch.compile (inductor)
Conv3d LeakyReLU Sum Clamp GELU · depth = 16 · width = 64 · height = 64 · batch_size = 128 · in_channels = 8 · fp32 · run 01a03f0e-f6ec…
●passedReported evidence
Not re-observed recently.
Primary measurement
10.0ms±0.02 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 11.2 · min ms 9.96 · std ms 0.122 · mean ms 10
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloaddepth = 16 · width = 64 · height = 64 · batch_size = 128 · in_channels = 8 · fp32
comparison keysha256:a6332d18b8f17725…
sourceKernelBench baseline timings
external idH100_Modal/torch-compile-inductor/level2/90_Conv3d_LeakyReLU_Sum_Clamp_GELU.py
sha256:bdcab920c032647e15473c8…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth16
width64
height64
batch_size128
in_channels8
input_1fp32 [128, 8, 16, 64, 64]
definition comparatornot_asserted
Measurements
latency · max11.2 ms · n=100
latency · mean10.0 ms · n=100
latency · min9.96 ms · n=100
latency · std122.0 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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}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Conv3d LeakyReLU Sum Clamp GELU →JSON