torch.compile (inductor)
ConvTranspose3d Sum ResidualAdd Multiply ResidualAdd · depth = 16 · width = 32 · height = 32 · batch_size = 16 · in_channels = 32 · fp32 · run 01a03f0e-f6e6…
●passedReported evidence
Not re-observed recently.
Primary measurement
1.13ms±0.03 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 2.97 · min ms 1.1 · std ms 0.188 · mean ms 1.13
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloaddepth = 16 · width = 32 · height = 32 · batch_size = 16 · in_channels = 32 · fp32
comparison keysha256:2456ff3436420d18…
sourceKernelBench baseline timings
external idH100_Modal/torch-compile-inductor/level2/20_ConvTranspose3d_Sum_ResidualAdd_Multiply_ResidualAdd.py
sha256:4b54d779f20daf354595bdd…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth16
width32
height32
batch_size16
in_channels32
input_1fp32 [16, 32, 16, 32, 32]
definition comparatornot_asserted
Measurements
latency · max2.97 ms · n=100
latency · mean1.13 ms · n=100
latency · min1.10 ms · n=100
latency · std188.0 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",
"measurements": [
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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 ResidualAdd Multiply ResidualAdd →JSON