SGLang: Efficient Language Model Program Execution

This June 2024 paper introduces SGLang, a framework designed to enhance the efficiency of Large Language Model (LLM) and Vision Language Model (VLM) serving. It achieves this through a co-design of a flexible frontend language and a fast backend runtime. The frontend simplifies programming with primitives for generation and parallelism, while the backend utilizes novel optimizations like RadixAttention for KV cache reuse and compressed finite state machines for faster structured output decoding. These innovations allow SGLang to significantly improve throughput and reduce latency compared to existing systems across various LLM applications and hardware platforms. The framework is open-source, boasts extensive model support, and has seen wide industry adoption due to its performance benefits in complex LM programs.Sources:https://arxiv.org/pdf/2312.07104https://docs.sglang.ai/https://github.com/sgl-project/sglang

There are no comments yet.

Please log in to write the first comment.