PyTorch eager
conv transposed 2D asymmetric input square kernel · width_in = 1024 · height_in = 512 · batch_size = 8 · in_channels = 32 · fp32 · run 01a03f0e-f6cf…
●passedReported evidence
Not re-observed recently.
Primary measurement
1.58ms±0.00 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 1.59 · min ms 1.57 · std ms 0.00415 · mean ms 1.58
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadwidth_in = 1024 · height_in = 512 · batch_size = 8 · in_channels = 32 · fp32
comparison keysha256:ca147c6c7756130f…
sourceKernelBench baseline timings
external idH100_Modal/torch/level1/71_conv_transposed_2D__asymmetric_input__square_kernel.py
sha256:65c32945b66475223a6cf03…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
width_in1024
height_in512
batch_size8
in_channels32
xfp32 [8, 32, 512, 1024]
definition comparatornot_asserted
Measurements
latency · max1.59 ms · n=100
latency · mean1.58 ms · n=100
latency · min1.57 ms · n=100
latency · std4.15 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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"timing": {
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"latencyNs": {
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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 conv transposed 2D asymmetric input square kernel →JSON