torch.compile (inductor)
Gemm Subtract GlobalAvgPool LogSumExp GELU ResidualAdd · batch_size = 2048 · in_features = 8192 · fp32 · run 01a03f0e-f84e…
●passedReported evidence
Not re-observed recently.
Primary measurement
8.04ms±0.04 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 8.7 · min ms 7.71 · std ms 0.224 · mean ms 8.04
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 2048 · in_features = 8192 · fp32
comparison keysha256:31c70068b0fd4791…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level2/51_Gemm_Subtract_GlobalAvgPool_LogSumExp_GELU_ResidualAdd.py
sha256:5cb3c32a37f3dd060baf7cc…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size2048
in_features8192
input_1fp32 [2048, 8192]
definition comparatornot_asserted
Measurements
latency · max8.70 ms · n=100
latency · mean8.04 ms · n=100
latency · min7.71 ms · n=100
latency · std224.0 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
Show manifestHide manifest
{
"run": {
"kind": "BenchmarkRun",
"spec": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 8040000,
"maximum": 8700000,
"minimum": 7710000,
"confidence95": [
7996096,
8083904
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 224000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 8.7,
"min_ms": 7.71,
"std_ms": 0.224,
"mean_ms": 8.04
},
"benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
"externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level2/51_Gemm_Subtract_GlobalAvgPool_LogSumExp_GELU_ResidualAdd.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:0edfac16d56e826b56b269f78eee5dc5116bcc41090fef4f52eaf4c54d61f3eb",
"environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
"implementationDigest": "sha256:a06b5ca3daf02eb6dac3ad01ae31e966ca0b4adf1390d69a2451b3c943b4819a"
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l2-51-gemm-subtract-globalavgpool-logsumexp-",
"title": "Gemm Subtract GlobalAvgPool LogSumExp GELU ResidualAdd · torch.compile (inductor) · Lambda Labs"
},
"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": {
"name": "kernelbench-timing-v1",
"title": "KernelBench baseline timing"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"environment": {
"kind": "ExecutionEnvironment",
"spec": {
"hardware": {
"vendor": "nvidia",
"product": "NVIDIA H100",
"formFactor": "PCIe",
"architecture": "sm_90"
},
"software": {}
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs",
"title": "KernelBench host · H100 PCIe (Lambda Labs)"
},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}Cite this record (permalink, digest, access date)
Report an issue with this run
Published 2026-08-26 · KernelBench baseline timings · MITAll results for Gemm Subtract GlobalAvgPool LogSumExp GELU ResidualAdd →JSON