torch.compile (inductor)
LSTMHn · batch_size = 10 · input_size = 128 · num_layers = 6 · hidden_size = 256 · sequence_length = 512 · fp32 · run 01a03f0e-f6f0…
●passedReported evidence
Not re-observed recently.
Primary measurement
35.4ms±0.10 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 38.4 · min ms 34.8 · std ms 0.517 · mean ms 35.4
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 10 · input_size = 128 · num_layers = 6 · hidden_size = 256 · sequence_length = 512 · fp32
comparison keysha256:836466a17162adb5…
sourceKernelBench baseline timings
external idH100_Modal/torch-compile-inductor/level3/36_LSTMHn.py
sha256:bddcf29da12dd5ec005d213…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size10
input_size128
num_layers6
hidden_size256
sequence_length512
input_1fp32 [10, 512, 128]
input_2fp32 [6, 10, 256]
input_3fp32 [6, 10, 256]
definition comparatornot_asserted
Measurements
latency · max38.4 ms · n=100
latency · mean35.4 ms · n=100
latency · min34.8 ms · n=100
latency · std517.0 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": 35400000,
"maximum": 38400000,
"minimum": 34800000,
"confidence95": [
35298668,
35501332
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 517000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
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"metrics": {
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"min_ms": 34.8,
"std_ms": 0.517,
"mean_ms": 35.4
},
"benchmark": "H100_Modal/baseline_time_torch_compile_inductor_default.json",
"externalId": "H100_Modal/torch-compile-inductor/level3/36_LSTMHn.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:2075a8b7c2be687b7fdea73afa7c25a24455e4a760d54b9340465d1484023fb3",
"environmentDigest": "sha256:2750ae381d6de582f1eb6b9008e0987463d19ede8af127d97d76c5ae09121393",
"implementationDigest": "sha256:ded92fe0eb0fe28824fc1ea70341a9f1c7bc05c63c56e265ce9472d7c439b26c"
},
"metadata": {
"name": "kernelbench-h100-modal-torch-compile-inductor-l3-36-lstmhn",
"title": "LSTMHn · torch.compile (inductor) · 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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},
"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 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 LSTMHn →JSON