Summary of Fastswitch: Optimizing Context Switching Efficiency in Fairness-aware Large Language Model Serving, by Ao Shen et al.
FastSwitch: Optimizing Context Switching Efficiency in Fairness-aware Large Language Model Serving
by Ao Shen, Zhiyao Li, Mingyu Gao
First submitted to arxiv on: 27 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Distributed, Parallel, and Cluster Computing (cs.DC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the issue of fairness in Large Language Models (LLMs) serving systems, which are designed to handle multiple users and requests concurrently. The authors propose a novel approach called FastSwitch that mitigates the overhead caused by preemption-induced context switching while maintaining balance during runtime. This is achieved through dynamic adjustments of request priorities using a scheduling policy. The paper identifies three main challenges that result in this overhead: inadequate I/O utilization, GPU idleness, and unnecessary I/O transmission during multi-turn conversations. By introducing FastSwitch, the authors demonstrate speedups of 1.4-11.2x compared to state-of-the-art LLM serving systems like vLLM. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making sure that a computer system can handle many people asking for things at the same time. This is important because we want everyone to have a good experience, not just a few lucky ones. The problem is that some systems are too focused on getting lots of work done quickly and forget about the extra costs of doing so. To solve this, the authors created a new system called FastSwitch that can adjust how it handles requests in real-time to make sure everyone gets a fair share. They found three main problems that cause extra costs: not using computer resources efficiently, wasting time when computers are idle, and sending too many messages during conversations. By creating FastSwitch, they showed that it can handle tasks 1.4-11.2 times faster than other systems. |
