PyTorch eager
Conv3d Max LogSumExp ReLU · depth = 32 · width = 128 · height = 128 · batch_size = 4 · in_channels = 32 · fp32 · run 01a03f0e-f6d4…
●passedReported evidence
Not re-observed recently.
Primary measurement
2.66ms±0.00 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 2.69 · min ms 2.63 · std ms 0.0151 · mean ms 2.66
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 32 · width = 128 · height = 128 · batch_size = 4 · in_channels = 32 · fp32
comparison keysha256:e66defccc8a9d8aa…
sourceKernelBench baseline timings
external idH100_Modal/torch/level2/43_Conv3d_Max_LogSumExp_ReLU.py
sha256:deaa2fc5633d31d850dbc76…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth32
width128
height128
batch_size4
in_channels32
input_1fp32 [4, 32, 32, 128, 128]
definition comparatornot_asserted
Measurements
latency · max2.69 ms · n=100
latency · mean2.66 ms · n=100
latency · min2.63 ms · n=100
latency · std15.1 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.
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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",
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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 Conv3d Max LogSumExp ReLU →JSON