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PyTorch eager

conv depthwise 2D asymmetric input asymmetric kernel · width = 256 · height = 128 · batch_size = 32 · in_channels = 128 · fp32 · run 01a03f0e-f836…
●passedReported evidence

Not re-observed recently.

Primary measurement
3.03ms±0.00 · mean of 100

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

max ms 3.05 · min ms 3.02 · std ms 0.00298 · mean ms 3.03

Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadwidth = 256 · height = 128 · batch_size = 32 · in_channels = 128 · fp32
comparison keysha256:35fb60770db0dd9f…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/85_conv_depthwise_2D_asymmetric_input_asymmetric_kernel.py
sha256:268d686646a75d43747e769…

Correctness

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

Workload

width256
height128
batch_size32
in_channels128
xfp32 [32, 128, 128, 256]
definition comparatornot_asserted

Measurements

latency · max3.05 ms · n=100
latency · mean3.03 ms · n=100
latency · min3.02 ms · n=100
latency · std2.98 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

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{
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    "kind": "BenchmarkRun",
    "spec": {
      "status": "passed",
      "timing": {
        "samples": 100,
        "latencyNs": {
          "mean": 3030000,
          "maximum": 3050000,
          "minimum": 3020000,
          "confidence95": [
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            3030584
          ]
        },
        "primaryStatistic": "mean"
      },
      "observedAt": "2026-03-05T08:38:15.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 2980,
          "metric": "latency",
          "statistic": "std"
        }
      ],
      "sourceNative": {
        "source": "kernelbench",
        "metrics": {
          "max_ms": 3.05,
          "min_ms": 3.02,
          "std_ms": 0.00298,
          "mean_ms": 3.03
        },
        "benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch.json",
        "externalId": "H100_PCIe_LambdaLabs/torch/level1/85_conv_depthwise_2D_asymmetric_input_asymmetric_kernel.py"
      },
      "protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
      "workloadDigest": "sha256:3e693a6c42839c20ce93f1f83d19e26cfe607941e3edc944d1b75af648e0fc81",
      "environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
      "implementationDigest": "sha256:e646dcce4c61f1a3796ab71e2eafc0e2e5090df9be9fd9c872c80bdaf0985df0"
    },
    "metadata": {
      "name": "kernelbench-h100-pcie-lambdalabs-torch-l1-85-conv-depthwise-2d-asymmetric-input-asymmetric-kernel",
      "title": "conv depthwise 2D asymmetric input asymmetric kernel · PyTorch eager · Lambda Labs"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "protocol": {
    "kind": "BenchmarkProtocol",
    "spec": {
      "harness": {
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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",
      "title": "KernelBench baseline timing"
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  "environment": {
    "kind": "ExecutionEnvironment",
    "spec": {
      "hardware": {
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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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