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torch.compile (inductor)

Matmul Scaling ResidualAdd · batch_size = 16384 · in_features = 4096 · fp32 · run 01a03f0e-f84d…
●passedReported evidence

Not re-observed recently.

Primary measurement
16.2ms±0.12 · mean of 100

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

max ms 17.1 · min ms 15.2 · std ms 0.609 · mean ms 16.2

Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 16384 · in_features = 4096 · fp32
comparison keysha256:de10ac5101d50da9…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level2/40_Matmul_Scaling_ResidualAdd.py
sha256:417963e8b2946d1d242dc58…

Correctness

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

Workload

batch_size16384
in_features4096
input_1fp32 [16384, 4096]
definition comparatornot_asserted

Measurements

latency · max17.1 ms · n=100
latency · mean16.2 ms · n=100
latency · min15.2 ms · n=100
latency · std609.0 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": {
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          "confidence95": [
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          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 609000,
          "metric": "latency",
          "statistic": "std"
        }
      ],
      "sourceNative": {
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        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
        "externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level2/40_Matmul_Scaling_ResidualAdd.py"
      },
      "protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
      "workloadDigest": "sha256:429b25653cbbe5857d2cf947e33feb6183b4a568d970326182407b27e7a77148",
      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:39126e2a0fbc3ab25d08bdba99032089c5d8f4204075875467f69850348f078b"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l2-40-matmul-scaling-residualadd",
      "title": "Matmul Scaling ResidualAdd · torch.compile (inductor) · Lambda Labs"
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  "protocol": {
    "kind": "BenchmarkProtocol",
    "spec": {
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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"
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    },
    "metadata": {
      "name": "kernelbench-timing-v1",
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  "environment": {
    "kind": "ExecutionEnvironment",
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}
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