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Multi-token attention · k = 3 · seq = 64 · batch = 2 · heads_in = 4 · heads_out = 4 · fp32 · run 01a0202b-21a3…
●passedReported evidence

Not re-observed recently.

Primary measurement
258.0µsmedian

Rank 1 in its comparison group · source-native comparison · observed 2025-04-30

ms 20 0.2514623999595642 · ms 50 0.25804799795150757 · ms 80 0.26668161153793335

Identity
implementationPyTorch
projectPyTorch
revisionunknown
workloadk = 3 · seq = 64 · batch = 2 · heads_in = 4 · heads_out = 4 · fp32
comparison keysha256:a1f8b3c7a1d7f939…
sourceLiger-Kernel benchmarks
external idsparse_multi_token_attention/backward/torch/nvidia-geforce-rtx-3090/batch2-heads_in4-heads_out4-k3-seq64-fp32/2025-04-30-17-22-18
sha256:89f9c8e38976727615f8338…

Correctness

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

Workload

k3
seq64
batch2
heads_in4
heads_out4
biasfp32 [4]
scoresfp32 [2, 4, 64, 64]
weightfp32 [4, 4, 3, 3]
definition comparatornot_asserted

Measurements

latency · median258.0 µs
latency · p20251.5 µs
latency · p80266.7 µs

Protocol

harnessLiger-Kernel benchmark scripts
timercuda_events
primaryStatisticmedian
comparabilityFamilyliger_kernel_bench

Environment

gpuNVIDIA GeForce RTX 3090 (sm_86)

Artifacts

No artifacts published with this run.

Replications and notes

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Canonical manifest

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{
  "run": {
    "kind": "BenchmarkRun",
    "spec": {
      "status": "passed",
      "timing": {
        "latencyNs": {
          "median": 258048
        },
        "primaryStatistic": "median"
      },
      "observedAt": "2025-04-30T17:22:18.000Z",
      "measurements": [
        {
          "unit": "ns",
          "value": 251462,
          "metric": "latency",
          "statistic": "p20"
        },
        {
          "unit": "ns",
          "value": 266682,
          "metric": "latency",
          "statistic": "p80"
        }
      ],
      "sourceNative": {
        "source": "liger-kernel-bench",
        "metrics": {
          "ms_20": 0.2514623999595642,
          "ms_50": 0.25804799795150757,
          "ms_80": 0.26668161153793335
        },
        "benchmark": "sparse_multi_token_attention/backward",
        "externalId": "sparse_multi_token_attention/backward/torch/nvidia-geforce-rtx-3090/batch2-heads_in4-heads_out4-k3-seq64-fp32/2025-04-30-17-22-18"
      },
      "protocolDigest": "sha256:080e6e66e4ec75a131aa0c9121c74b8e8eed64e7b6d621d567c6a28f79548be8",
      "workloadDigest": "sha256:d3d8424c1e4c0827e72bf29db58e6f571f03d7bd2be62be92a0202d83ea44c13",
      "environmentDigest": "sha256:b12fdfab6a337672499b10212a1e986e49e4383777bd7cbb58321b09af4bf6a3",
      "implementationDigest": "sha256:6d4198771fde93bb65a4b8958b54d34a4cf41b41ae68b21aa09bf478b4aa6660"
    },
    "metadata": {
      "name": "liger-sparse-multi-token-attention-backward-torch-nvidia-geforce-rtx-3090-batch2-heads-in4-heads-out",
      "title": "Sparse multi-token attention · torch · backward",
      "labels": {
        "liger_version": "0.5.8"
      }
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "protocol": {
    "kind": "BenchmarkProtocol",
    "spec": {
      "harness": {
        "name": "Liger-Kernel benchmark scripts",
        "repository": "https://github.com/linkedin/Liger-Kernel"
      },
      "measurement": {
        "timer": "cuda_events",
        "primaryStatistic": "median"
      },
      "comparability": {
        "notes": "Timed: the backward pass of the module output given a random upstream gradient, 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.",
        "family": "liger_kernel_bench"
      }
    },
    "metadata": {
      "name": "liger-bench-do-bench-backward",
      "title": "Liger benchmark harness · backward pass"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  },
  "environment": {
    "kind": "ExecutionEnvironment",
    "spec": {
      "hardware": {
        "vendor": "nvidia",
        "product": "NVIDIA GeForce RTX 3090",
        "architecture": "sm_86"
      },
      "software": {}
    },
    "metadata": {
      "name": "liger-bench-nvidia-geforce-rtx-3090",
      "title": "Liger benchmark host · GeForce RTX 3090"
    },
    "apiVersion": "kernelindex.dev/v1alpha1"
  }
}
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