PyTorch

{
  "run": {
    "kind": "BenchmarkRun",
    "spec": {
      "status": "passed",
      "timing": {
        "latencyNs": {
          "median": 12288
        },
        "primaryStatistic": "median"
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      "observedAt": "2025-04-30T16:11:07.000Z",
      "measurements": [
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          "metric": "latency",
          "statistic": "p20"
        },
        {
          "unit": "ns",
          "value": 13312,
          "metric": "latency",
          "statistic": "p80"
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      "sourceNative": {
        "source": "liger-kernel-bench",
        "metrics": {
          "ms_20": 0.01228800043463707,
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        "benchmark": "softmax/forward",
        "externalId": "softmax/forward/torch/nvidia-geforce-rtx-3090/hidden512-rows2048-fp32/2025-04-30-16-11-07"
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      "workloadDigest": "sha256:b9ec914a8b198f4ffdffd04d7b9efe3ad317f05936ff8618d7c72a83f6b275a4",
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      "implementationDigest": "sha256:643178d96c20c26e7a3c3c424ad25f85170a76224689482539da1059ff9aacea"
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    "metadata": {
      "name": "liger-softmax-forward-torch-nvidia-geforce-rtx-3090-hidden512-rows2048-fp32-2025-04-30-16-11-07",
      "title": "Softmax · torch · forward",
      "labels": {
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    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "protocol": {
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        "repository": "https://github.com/linkedin/Liger-Kernel"
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      "measurement": {
        "timer": "cuda_events",
        "primaryStatistic": "median"
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      "comparability": {
        "notes": "Timed: the module forward pass, via triton.testing.do_bench with quantiles 0.5/0.2/0.8 (median with p20/p80 spread). The upstream CSV records no CUDA, driver, or torch version; the Liger release rides each run's labels. Comparable only within one kernel, workload, timed pass, and GPU.",
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      "title": "Liger benchmark host · GeForce RTX 3090"
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    "apiVersion": "kernelindex.dev/v1alpha1"
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}