PyTorch

{
  "run": {
    "kind": "BenchmarkRun",
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      "status": "passed",
      "timing": {
        "latencyNs": {
          "median": 42113216
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      "sourceNative": {
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      "name": "liger-jsd-full-torch-nvidia-h100-pcie-tokens8192-vocab32768-fp32-2024-10-02-16-21-43",
      "title": "Jensen-Shannon divergence loss · torch · full",
      "labels": {
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        "repository": "https://github.com/linkedin/Liger-Kernel"
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        "notes": "Timed: the forward pass plus the backward 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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