NVIDIA 如何用推测解码协同设计 AI 模型以加速 LLM 推理
Co-Designing AI Models Using Speculative Decoding for Faster LLM Inference
NVIDIA 在 AI 模型协同设计系列第三篇中，探讨如何用推测解码在保持精度的前提下加速 LLM 推理。文章给出五条指南，用于在帕累托前沿上选择 draft 长度与 draft 机制。
This post is the third in a series on AI model co-design. It explores how to accelerate LLM inference while maintaining accuracy using speculative decoding and...
This post is the third in a series on AI model co-design. It explores how to accelerate LLM inference while maintaining accuracy using speculative decoding and offers five guidelines for selecting draft length and draft mechanism across the Pareto frontier. For a discussion of how model design choices impact both throughput and interactivity without sacrificing accuracy, see AI Model Co…
来源：NVIDIA Developer Blog · developer.nvidia.com