PyTorch eager
conv transposed 1D · length = 65536 · batch_size = 64 · in_channels = 128 · fp32 · run 01a03f0e-f6ce…
●passedReported evidence
Not re-observed recently.
Primary measurement
5.48ms±0.45 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 34.6 · min ms 5.16 · std ms 2.93 · mean ms 5.48
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadlength = 65536 · batch_size = 64 · in_channels = 128 · fp32
comparison keysha256:d4ca8884414d549e…
sourceKernelBench baseline timings
external idH100_Modal/torch/level1/64_conv_transposed_1D.py
sha256:7704cb5505295079d511fc1…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
length65536
batch_size64
in_channels128
xfp32 [64, 128, 65536]
definition comparatornot_asserted
Measurements
latency · max34.6 ms · n=100
latency · mean5.48 ms · n=100
latency · min5.16 ms · n=100
latency · std2.93 ms
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": 5480000,
"maximum": 34600000,
"minimum": 5160000,
"confidence95": [
5160000,
6054280
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 2930000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
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"metrics": {
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"min_ms": 5.16,
"std_ms": 2.93,
"mean_ms": 5.48
},
"benchmark": "H100_Modal/baseline_time_torch.json",
"externalId": "H100_Modal/torch/level1/64_conv_transposed_1D.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:be69239be67183a3f6bbb3fb2ee0baf0a6427b9f54e8e6fe5836b96fa58979cc",
"environmentDigest": "sha256:2750ae381d6de582f1eb6b9008e0987463d19ede8af127d97d76c5ae09121393",
"implementationDigest": "sha256:ef517a4c183d425dee303aa113167bbbf1dc3f448e1a94e458bf63bbe4cd5b9c"
},
"metadata": {
"name": "kernelbench-h100-modal-torch-l1-64-conv-transposed-1d",
"title": "conv transposed 1D · PyTorch eager · Modal"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
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"repository": "https://github.com/ScalingIntelligence/KernelBench"
},
"measurement": {
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"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": {
"name": "kernelbench-timing-v1",
"title": "KernelBench baseline timing"
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"environment": {
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},
"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 conv transposed 1D →JSON