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arXiv · 2506.05871

BestServe: Serving Strategies with Optimal Goodput in Collocation and Disaggregation Architectures

Xiannan Hu·Tianyou Zeng·Xiaoming Yuan·Liwei Song·Guangyuan Zhang·Bangzheng He
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Abstract

Serving large language models (LLMs) to millions of users requires efficient resource allocation and parallelism strategies. It is a labor intensive trial-and-error process to find such a strategy. We present BestServe, a novel framework for ranking serving strategies by estimating goodput under various operating scenarios. Supporting both collocated and disaggregated architectures, BestServe leverages an inference simulator built on an adapted roofline model and CPU-GPU dispatch dynamics. Our framework determines the optimal strategy in minutes on a single standard CPU, eliminating the need for costly benchmarking, while achieving predictions within a $20\%$ error margin. It appeals to be practical for rapid deployment planning because of its lightweight design and strong extensibility.

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Xiannan Hu, Tianyou Zeng, Xiaoming Yuan, Liwei Song, Guangyuan Zhang, Bangzheng He. 2025-06-06. BestServe: Serving Strategies with Optimal Goodput in Collocation and Disaggregation Architectures. https://arxiv.org/abs/2506.05871

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