PyTorch eager
GRUHidden · seq_len = 512 · batch_size = 10 · input_size = 128 · num_layers = 6 · hidden_size = 256 · fp32 · run 01a03f0e-f6dc…
●passedReported evidence
Not re-observed recently.
Primary measurement
38.5ms±0.54 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 50.7 · min ms 35.2 · std ms 2.74 · mean ms 38.5
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadseq_len = 512 · batch_size = 10 · input_size = 128 · num_layers = 6 · hidden_size = 256 · fp32
comparison keysha256:eaafac6221b592d9…
sourceKernelBench baseline timings
external idH100_Modal/torch/level3/40_GRUHidden.py
sha256:661bf968163319fab7fe5bb…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
seq_len512
batch_size10
input_size128
num_layers6
hidden_size256
input_1fp32 [512, 10, 128]
input_2fp32 [6, 10, 256]
definition comparatornot_asserted
Measurements
latency · max50.7 ms · n=100
latency · mean38.5 ms · n=100
latency · min35.2 ms · n=100
latency · std2.74 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": 38500000,
"maximum": 50700000,
"minimum": 35200000,
"confidence95": [
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39037040
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 2740000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
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"metrics": {
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"min_ms": 35.2,
"std_ms": 2.74,
"mean_ms": 38.5
},
"benchmark": "H100_Modal/baseline_time_torch.json",
"externalId": "H100_Modal/torch/level3/40_GRUHidden.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
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"environmentDigest": "sha256:2750ae381d6de582f1eb6b9008e0987463d19ede8af127d97d76c5ae09121393",
"implementationDigest": "sha256:c7f64456131cce32a290d453ddef6363ea7fc4d74b874fbab12bba976f2cb63e"
},
"metadata": {
"name": "kernelbench-h100-modal-torch-l3-40-gruhidden",
"title": "GRUHidden · PyTorch eager · Modal"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
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},
"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": {
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},
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"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 GRUHidden →JSON