用NVIDIA Transformer Engine加速Transformer训练：融合内核与FP8实操指南

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想让你自己训练的Transformer跑得更快？这篇手把手教你用NVIDIA Transformer Engine和FP8，还有代码和GPU跑分对比。

AI 摘要

教程演示如何在PyTorch中配置NVIDIA Transformer Engine的融合GPU内核。使用FP8延迟缩放和BF16混合精度训练GPT风格因果语言模型。文章提供了可运行的代码示例，并给出不同GPU上的基准测试对比。还解释了FP8延迟缩放的数值稳定性调参方法。

用NVIDIA Transformer Engine加速Transformer训练：融合内核与FP8实操指南 — 图片来源 · marktechpost

原文 · marktechpost

Accelerating Transformer Training with NVIDIA Transformer Engine, Fused Kernels, BF16, FP8, and GPU Benchmarking

Discover how to optimize transformer workloads using the NVIDIA Transformer Engine. This tutorial guides you through configuring fused GPU kernels, implementing FP8 delayed scaling, and benchmarking model performance. Learn to build and train efficient GPT-style causal language models in PyTorch with practical code examples and performance analysis. The post Accelerating Transformer Training with NVIDIA Transformer Engine, Fused Kernels, BF16, FP8, and GPU Benchmarking appeared first on MarkTechPost .

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