新FFT方法利用FP8张量核心实现高精度GPU计算

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-24 04:00

一篇新的研究论文提出了一种使用NVIDIA Blackwell Ultra (B300) GPU计算快速傅里叶变换 (FFT) 的高效方法。Ozaki-Bailey FFT技术利用FP8张量核心进行密集矩阵乘法，并通过Garner重构方法实现FP64精度。该方法旨在使B300 GPU能够胜任完整的FP64 FFT工作负载，从而可能为内存密集型应用带来显著的性能提升。 AI

影响这项研究可能使在专用硬件上进行更高效的高精度计算成为可能，从而可能使依赖FFT的AI工作负载受益。

排序理由该条目是一篇学术论文，详细介绍了一种新的FFT计算方法。[lever_c_demoted from research: ic=1 ai=0.7]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Satoshi Matsuoka · 2026-06-24 04:00

FP8 is All You Need (Part 2): Efficient Ozaki-Bailey Style FFT Through Tensor-core Garner Reformulation and Kulisch Escape Route

arXiv:2606.23698v1 Announce Type: cross Abstract: NVIDIA's Blackwell Ultra (B300) cuts FP64 vector throughput to ~1.3 TFLOPS per GPU, roughly 30x below B200 and well below the level at which bandwidth-limited FP64 workloads stay memory-bound. The Ozaki Scheme II framework recover…

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FP8 is All You Need (Part 2): Efficient Ozaki-Bailey Style FFT Through Tensor-core Garner Reformulation and Kulisch Escape Route

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