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torch.compile (inductor)

Matmul for lower triangular matrices · m = 4096 · fp32 · run 01a03f0e-f843…
●passedReported evidence

Not re-observed recently.

Primary measurement
3.77ms±0.00 · mean of 100

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

Compare with #1 →

max ms 3.82 · min ms 3.76 · std ms 0.00912 · mean ms 3.77

Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadm = 4096 · fp32
comparison keysha256:9f87314431d51a1a…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level1/15_Matmul_for_lower_triangular_matrices.py
sha256:92db3d976a487743aa4ec06…

Correctness

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

Workload

m4096
afp32 [4096, 4096]
bfp32 [4096, 4096]
definition comparatornot_asserted

Measurements

latency · max3.82 ms · n=100
latency · mean3.77 ms · n=100
latency · min3.76 ms · n=100
latency · std9.12 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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          "maximum": 3820000,
          "minimum": 3760000,
          "confidence95": [
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            3771788
          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 9120,
          "metric": "latency",
          "statistic": "std"
        }
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      "sourceNative": {
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          "std_ms": 0.00912,
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        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
        "externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level1/15_Matmul_for_lower_triangular_matrices.py"
      },
      "protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
      "workloadDigest": "sha256:519017b7f026bc9b8bf0cd085aec4b6ea4d873a37ca1ff0673356e0e83a384d2",
      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:c430cefdbfd242868317b432c2baf077a13f0f490d1316cf65b5c42d43a26be1"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l1-15-matmul-for-lower-triangular-matrices",
      "title": "Matmul for lower triangular matrices · torch.compile (inductor) · Lambda Labs"
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  "protocol": {
    "kind": "BenchmarkProtocol",
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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": {
      "name": "kernelbench-timing-v1",
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  "environment": {
    "kind": "ExecutionEnvironment",
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      "title": "KernelBench host · H100 PCIe (Lambda Labs)"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  }
}
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