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Download docs/interface-audit/performance.md from humanfia-lab/inference-kernels: direct link, hf CLI and curl.
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https://huggingface.co/datasets/humanfia-lab/inference-kernels/resolve/refs%2Fpr%2F2/docs/interface-audit/performance.md
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hf download hf://datasets/humanfia-lab/inference-kernels@refs/pr/2/docs/interface-audit/performance.md
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curl -L -o performance.md https://huggingface.co/datasets/humanfia-lab/inference-kernels/resolve/refs%2Fpr%2F2/docs/interface-audit/performance.md
1.32 kB
Recorded B300 comparisons
Ratios are paired geometric-mean speedups in the recorded standalone CUDA Graph scope. Prepared launch is used where available; eager timings remain in the raw results. These are not end-to-end serving speedups or proofs of global optimality.
| Comparison | Paired workloads | Speedup |
|---|---|---|
| B300 GEMM large-M native-linear dispatch versus DeepGEMM-only | 31 | 0.44× |
| Audio final versus original FP16-conversion solution | 108 | 4.03× |
| Current fused router versus original CUTLASS/torch solution | 50 | 5.00× |
| Cached-prefix FA4 versus serving implementation adapter | 28 | 3.81× |
| QSA index final versus original on its declared TileLang 0.1.15 | 10 | 2.28× |
| Native paged sparse GQA versus FA4 sparse gather | 10 | 1.90× |
| FlashMLA CUDA 13.3 versus CUDA 13.1 compiler build | 10 | 1.01× |
| FlashMLA CUDA 13.3 versus CUDA 13.1 compiler build | 20 | 1.01× |
| FlashMLA CUDA 13.3 versus CUDA 13.1 compiler build | 42 | 1.03× |
The old QSA implementation is measured with its declared TileLang 0.1.15, rather than the incompatible 0.1.12 experiment. Current SGLang-based solutions use 0.1.12. See summary.json for ranges, source run identifiers and coverage; results.jsonl retains separate eager and prepared timings.