PyTorch eager
conv standard 2D square input asymmetric kernel dilated padded · width = 512 · height = 512 · batch_size = 8 · in_channels = 32 · fp32 · run 01a03f0e-f836…
●passedReported evidence
Not re-observed recently.
Primary measurement
5.51ms±0.03 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 5.56 · min ms 4.91 · std ms 0.133 · mean ms 5.51
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadwidth = 512 · height = 512 · batch_size = 8 · in_channels = 32 · fp32
comparison keysha256:f0af7f8d921b0cc0…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/80_conv_standard_2D_square_input_asymmetric_kernel___dilated____padded__.py
sha256:2c3237933725571eb985f46…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
width512
height512
batch_size8
in_channels32
xfp32 [8, 32, 512, 512]
definition comparatornot_asserted
Measurements
latency · max5.56 ms · n=100
latency · mean5.51 ms · n=100
latency · min4.91 ms · n=100
latency · std133.0 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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}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for conv standard 2D square input asymmetric kernel dilated padded →JSON