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torch.compile (inductor)

ShallowWideMLP · batch_size = 128 · input_size = 16384 · fp32 · run 01a03f0e-f852…
●passedReported evidence

Not re-observed recently.

Primary measurement
20.8ms±0.08 · mean of 100

Rank 1 in its comparison group · source-native comparison · observed 2026-03-05

max ms 21.7 · min ms 20.1 · std ms 0.412 · mean ms 20.8

Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 128 · input_size = 16384 · fp32
comparison keysha256:35f5774fbaf80a8d…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level3/2_ShallowWideMLP.py
sha256:0a31f1b19b8a5290893be30…

Correctness

Marked passed by the source; the correctness policy was not published.

Workload

batch_size128
input_size16384
input_1fp32 [128, 16384]
definition comparatornot_asserted

Measurements

latency · max21.7 ms · n=100
latency · mean20.8 ms · n=100
latency · min20.1 ms · n=100
latency · std412.0 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

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Canonical manifest

Show manifest
{
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    "kind": "BenchmarkRun",
    "spec": {
      "status": "passed",
      "timing": {
        "samples": 100,
        "latencyNs": {
          "mean": 20800000,
          "maximum": 21700000,
          "minimum": 20100000,
          "confidence95": [
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            20880752
          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 412000,
          "metric": "latency",
          "statistic": "std"
        }
      ],
      "sourceNative": {
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        "metrics": {
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          "min_ms": 20.1,
          "std_ms": 0.412,
          "mean_ms": 20.8
        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
        "externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level3/2_ShallowWideMLP.py"
      },
      "protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
      "workloadDigest": "sha256:8529dd351b48f34299d22ffad36128f0d0dd70ba9d09a50617642156d69e572e",
      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:535c51ab1966c67877a306a215964873f4186080b9570c9bc51467b1c04069b2"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l3-2-shallowwidemlp",
      "title": "ShallowWideMLP · torch.compile (inductor) · Lambda Labs"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "protocol": {
    "kind": "BenchmarkProtocol",
    "spec": {
      "harness": {
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        "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"
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    "apiVersion": "kernelindex.dev/v1alpha1"
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  "environment": {
    "kind": "ExecutionEnvironment",
    "spec": {
      "hardware": {
        "vendor": "nvidia",
        "product": "NVIDIA H100",
        "formFactor": "PCIe",
        "architecture": "sm_90"
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      "software": {}
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs",
      "title": "KernelBench host · H100 PCIe (Lambda Labs)"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  }
}
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