PyTorch eager
Conv3d Multiply InstanceNorm Clamp Multiply Max · depth = 16 · width = 32 · height = 32 · batch_size = 128 · in_channels = 3 · fp32 · run 01a03f0e-f6d7…
●passedReported evidence
Not re-observed recently.
Primary measurement
965.0µs±1.69 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 1.03 · min ms 0.961 · std ms 0.00863 · mean ms 0.965
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 16 · width = 32 · height = 32 · batch_size = 128 · in_channels = 3 · fp32
comparison keysha256:b1b2741593ef857d…
sourceKernelBench baseline timings
external idH100_Modal/torch/level2/79_Conv3d_Multiply_InstanceNorm_Clamp_Multiply_Max.py
sha256:42d0a07985282352b4798bc…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth16
width32
height32
batch_size128
in_channels3
input_1fp32 [128, 3, 16, 32, 32]
definition comparatornot_asserted
Measurements
latency · max1.03 ms · n=100
latency · mean965.0 µs · n=100
latency · min961.0 µs · n=100
latency · std8.63 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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}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Conv3d Multiply InstanceNorm Clamp Multiply Max →JSON