PyTorch
GRPO loss, token-level importance sampling · seq = 1024 · batch = 8 · vocab = 128256 · bf16 · run 01a0202b-232a…
●passedReported evidence
Not re-observed recently.
Primary measurement
94.8msmedian
Rank 2 in its comparison group · source-native comparison · observed 2025-08-05
ms 20 94.83366394042969 · ms 50 94.83366394042969 · ms 80 94.83366394042969
Identity
implementationPyTorch
projectPyTorch
revisionunknown
workloadseq = 1024 · batch = 8 · vocab = 128256 · bf16
comparison keysha256:4e803a71c8a87772…
sourceLiger-Kernel benchmarks
external idfused_linear_grpo_loss_sequence/forward/torch/nvidia-a100-sxm4-80gb/batch8-seq1024-vocab128256-bf16/2025-08-05-00-08-54
sha256:fa347ab5a1849bf7c7cb77f…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
seq1024
batch8
vocab128256
logitsbf16 [8, 1025, 128256]
advantagesbf16 [8]
completion_idsint64 [8, 1024]
definition comparatornot_asserted
Measurements
latency · median94.8 ms
latency · p2094.8 ms
latency · p8094.8 ms
Protocol
harnessLiger-Kernel benchmark scripts
timercuda_events
primaryStatisticmedian
comparabilityFamilyliger_kernel_bench
Environment
gpuNVIDIA A100 (sm_80)
Artifacts
No artifacts published with this run.
Replications and notes
No attestations yet.
Community attestations. They never change the evidence level; only a KernelIndex-controlled rerun does.
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Canonical manifest
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{
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"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 · A100-SXM4-80GB"
},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}Cite this record (permalink, digest, access date)
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Published 2026-08-20 · Liger-Kernel benchmarks · BSD-2-ClauseAll results for GRPO loss, token-level importance sampling →JSON