PyTorch eager
conv transposed 3D square input asymmetric kernel · depth = 64 · width = 64 · height = 64 · batch_size = 16 · in_channels = 32 · fp32 · run 01a03f0e-f835…
●passedReported evidence
Not re-observed recently.
Primary measurement
11.9ms±0.06 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 12.5 · min ms 11.3 · std ms 0.306 · mean ms 11.9
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 64 · width = 64 · height = 64 · batch_size = 16 · in_channels = 32 · fp32
comparison keysha256:0546c16ab360185a…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/68_conv_transposed_3D__square_input__asymmetric_kernel.py
sha256:5df298bfc7ff42a53d9b365…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth64
width64
height64
batch_size16
in_channels32
xfp32 [16, 32, 64, 64, 64]
definition comparatornot_asserted
Measurements
latency · max12.5 ms · n=100
latency · mean11.9 ms · n=100
latency · min11.3 ms · n=100
latency · std306.0 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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"observedAt": "2026-03-05T08:38:15.000Z",
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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 conv transposed 3D square input asymmetric kernel →JSON