Implement Flash Attention Back End in SGLang – Basics and KV Cache

Implement Flash Attention Backend in SGLang - Basics and KV Cache April 26, 2025 Authored by Biao He Qingquan Song 0x0. Introduction In the past few weeks, we’ve implemented the Flash Attention Backend end-to-end in SGLang, which is now the default attention backend as of SGLang 0.4.6 release. Throughout this journey, we learned a lot about how Attention Backend functions in modern LLM serving engines and developed a deeper understanding of Flash Attention itself. In this series, we’ll walk through the implementation details, sharing insights that we hope will benefit anyone looking to implement their own attention backend in LLM serving engines. Table of Contents for the series This series will be split into 3 parts: Part 1: Basics, KV Cache and CUDA Graph Support (this post) Basics, KV Cache and CUDA Graph Support (this post) Part 2: Speculative Decoding Support (coming soon) Speculative Decoding Support (coming soon) Part 3: MLA, Llama 4, Sliding Window and Multimodal Supp ... Read full article.