torch.compile (inductor)
Matmul MaxPool Sum Scale · batch_size = 128 · in_features = 32768 · fp32 · run 01a03f0e-f6e9…
●passedReported evidence
Not re-observed recently.
Primary measurement
5.33ms±0.00 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 5.39 · min ms 5.3 · std ms 0.019 · mean ms 5.33
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 128 · in_features = 32768 · fp32
comparison keysha256:7c2ca7de8e39d139…
sourceKernelBench baseline timings
external idH100_Modal/torch-compile-inductor/level2/55_Matmul_MaxPool_Sum_Scale.py
sha256:997eb21d78a18898c17b8c0…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size128
in_features32768
input_1fp32 [128, 32768]
definition comparatornot_asserted
Measurements
latency · max5.39 ms · n=100
latency · mean5.33 ms · n=100
latency · min5.30 ms · n=100
latency · std19.0 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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{
"run": {
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"spec": {
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"timing": {
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"latencyNs": {
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},
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"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
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"metadata": {
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"title": "Matmul MaxPool Sum Scale · torch.compile (inductor) · Modal"
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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 Matmul MaxPool Sum Scale →JSON