torch.compile (inductor)
Matmul with large K dimension · k = 524288 · m = 256 · n = 256 · fp32 · run 01a03f0e-f843…
●passedReported evidence
Not re-observed recently.
Primary measurement
1.83ms±0.01 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 1.88 · min ms 1.73 · std ms 0.0492 · mean ms 1.83
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadk = 524288 · m = 256 · n = 256 · fp32
comparison keysha256:7758930efc4d69c4…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level1/6_Matmul_with_large_K_dimension_.py
sha256:97e87f1717d2ebf1ca82d94…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
k524288
m256
n256
afp32 [256, 524288]
bfp32 [524288, 256]
definition comparatornot_asserted
Measurements
latency · max1.88 ms · n=100
latency · mean1.83 ms · n=100
latency · min1.73 ms · n=100
latency · std49.2 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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},
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},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 49200,
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"statistic": "std"
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},
"comparability": {
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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 with large K dimension →JSON