PyTorch eager
ConvTranspose3d Sum LayerNorm AvgPool GELU · depth = 16 · width = 32 · height = 32 · batch_size = 32 · in_channels = 32 · fp32 · run 01a03f0e-f837…
●passedReported evidence
Not re-observed recently.
Primary measurement
15.6ms±0.00 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 15.7 · min ms 15.6 · std ms 0.00592 · mean ms 15.6
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 16 · width = 32 · height = 32 · batch_size = 32 · in_channels = 32 · fp32
comparison keysha256:7fdf784ca8afa928…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/3_ConvTranspose3d_Sum_LayerNorm_AvgPool_GELU.py
sha256:747407cb1845f3fb1c58af5…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth16
width32
height32
batch_size32
in_channels32
input_1fp32 [32, 32, 16, 32, 32]
definition comparatornot_asserted
Measurements
latency · max15.7 ms · n=100
latency · mean15.6 ms · n=100
latency · min15.6 ms · n=100
latency · std5.92 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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"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 ConvTranspose3d Sum LayerNorm AvgPool GELU →JSON