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torch.compile (inductor)

EfficientNetB1 · batch_size = 10 · fp32 · run 01a03f0e-f853…
●passedReported evidence

Not re-observed recently.

Primary measurement
2.97ms±0.01 · mean of 100

Rank 2 in its comparison group · source-native comparison · observed 2026-03-05

Compare with #1 →

max ms 3.16 · min ms 2.87 · std ms 0.0393 · mean ms 2.97

Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 10 · fp32
comparison keysha256:58e275905225c1a8…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level3/23_EfficientNetB1.py
sha256:87d46cd657e1737a2c18ac3…

Correctness

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

Workload

batch_size10
input_1fp32 [10, 3, 240, 240]
definition comparatornot_asserted

Measurements

latency · max3.16 ms · n=100
latency · mean2.97 ms · n=100
latency · min2.87 ms · n=100
latency · std39.3 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": 2970000,
          "maximum": 3160000,
          "minimum": 2870000,
          "confidence95": [
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            2977703
          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 39300,
          "metric": "latency",
          "statistic": "std"
        }
      ],
      "sourceNative": {
        "source": "kernelbench",
        "metrics": {
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          "std_ms": 0.0393,
          "mean_ms": 2.97
        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
        "externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level3/23_EfficientNetB1.py"
      },
      "protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
      "workloadDigest": "sha256:1985f9610f3bb47928884bf3cd32ad007058f883982a265d99a611ca4ffade83",
      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:a0b197522979086777c54e3230ecc7dbdc91c1d87d96e835d9cb1e24dee8cf7c"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l3-23-efficientnetb1",
      "title": "EfficientNetB1 · torch.compile (inductor) · Lambda Labs"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "protocol": {
    "kind": "BenchmarkProtocol",
    "spec": {
      "harness": {
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      },
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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",
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  "environment": {
    "kind": "ExecutionEnvironment",
    "spec": {
      "hardware": {
        "vendor": "nvidia",
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        "formFactor": "PCIe",
        "architecture": "sm_90"
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    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs",
      "title": "KernelBench host · H100 PCIe (Lambda Labs)"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  }
}
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