PyTorch eager
Tall skinny matrix multiplication · m = 32768 · n = 32 · fp32 · run 01a03f0e-f6ca…
●passedReported evidence
Not re-observed recently.
Primary measurement
2.59ms±0.02 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 4 · min ms 2.57 · std ms 0.142 · mean ms 2.59
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadm = 32768 · n = 32 · fp32
comparison keysha256:c6975f7d3935a637…
sourceKernelBench baseline timings
external idH100_Modal/torch/level1/9_Tall_skinny_matrix_multiplication_.py
sha256:f2afb329ff4d37167a57254…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
m32768
n32
afp32 [32768, 32]
bfp32 [32, 32768]
definition comparatornot_asserted
Measurements
latency · max4.00 ms · n=100
latency · mean2.59 ms · n=100
latency · min2.57 ms · n=100
latency · std142.0 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": {
"kind": "BenchmarkRun",
"spec": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 2590000,
"maximum": 4000000,
"minimum": 2570000,
"confidence95": [
2570000,
2617832
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 142000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 4,
"min_ms": 2.57,
"std_ms": 0.142,
"mean_ms": 2.59
},
"benchmark": "H100_Modal/baseline_time_torch.json",
"externalId": "H100_Modal/torch/level1/9_Tall_skinny_matrix_multiplication_.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:da79074e772998ebd75fa6199576695f03fdbe89faff6c0188cc07c81184b163",
"environmentDigest": "sha256:2750ae381d6de582f1eb6b9008e0987463d19ede8af127d97d76c5ae09121393",
"implementationDigest": "sha256:e56e42b6246545d6d3bd0afd748bf8703ee7b6f47f85eb69cce3c9d300cd5880"
},
"metadata": {
"name": "kernelbench-h100-modal-torch-l1-9-tall-skinny-matrix-multiplication",
"title": "Tall skinny matrix multiplication · PyTorch eager · Modal"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
"name": "KernelBench timing scripts",
"repository": "https://github.com/ScalingIntelligence/KernelBench"
},
"measurement": {
"timer": "cuda_events",
"primaryStatistic": "mean"
},
"comparability": {
"notes": "Mean of 100 timed forward passes (CUDA events, warm-up excluded) of the reference module on fixed inputs; the 95% interval is the mean's, from the reported standard deviation. The upstream JSON records no torch or CUDA version. Comparable only within one problem and one timing host.",
"family": "kernelbench_baseline_timing"
}
},
"metadata": {
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"title": "KernelBench baseline timing"
},
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"environment": {
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"spec": {
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"formFactor": "80GB HBM3",
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},
"software": {}
},
"metadata": {
"name": "kernelbench-h100-modal",
"title": "KernelBench host · H100 80GB HBM3 (Modal)"
},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Tall skinny matrix multiplication →JSON