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PyTorch eager

Gemm Add ReLU · batch_size = 1024 · in_features = 8192 · fp32 · run 01a03f0e-f83c…
●passedReported evidence

Not re-observed recently.

Primary measurement
5.11ms±0.03 · mean of 100

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

Compare with #1 →

max ms 5.19 · min ms 4.54 · std ms 0.146 · mean ms 5.11

Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 1024 · in_features = 8192 · fp32
comparison keysha256:fff155055a5aae3c…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/76_Gemm_Add_ReLU.py
sha256:f94f8b66b76b011e77e3db5…

Correctness

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

Workload

batch_size1024
in_features8192
input_1fp32 [1024, 8192]
definition comparatornot_asserted

Measurements

latency · max5.19 ms · n=100
latency · mean5.11 ms · n=100
latency · min4.54 ms · n=100
latency · std146.0 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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          "maximum": 5190000,
          "minimum": 4540000,
          "confidence95": [
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            5138616
          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 146000,
          "metric": "latency",
          "statistic": "std"
        }
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      "sourceNative": {
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        "metrics": {
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          "std_ms": 0.146,
          "mean_ms": 5.11
        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch.json",
        "externalId": "H100_PCIe_LambdaLabs/torch/level2/76_Gemm_Add_ReLU.py"
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      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:0e4717a426d81fd4c2118c74d3c12372baec02b599c10cd4d593330cdee46f3c"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-l2-76-gemm-add-relu",
      "title": "Gemm Add ReLU · PyTorch eager · Lambda Labs"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
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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"
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    },
    "metadata": {
      "name": "kernelbench-timing-v1",
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}
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