AdaServe: SLO-Customized LLM Serving with Fine-Grained Speculative Decoding

• URL: http://arxiv.org/abs/2501.12162v1
• Date: Tue, 21 Jan 2025 14:15:01 GMT
• Title: AdaServe: SLO-Customized LLM Serving with Fine-Grained Speculative Decoding
• Authors: Zikun Li, Zhuofu Chen, Remi Delacourt, Gabriele Oliaro, Zeyu Wang, Qinghan Chen, Shuhuai Lin, April Yang, Zhihao Zhang, Zhuoming Chen, Sean Lai, Xupeng Miao, Zhihao Jia,
• Abstract summary: AdaServe is the first LLM serving system to support SLO customization through fine-grained speculative decoding.<n>AdaServe achieves up to 73% higher SLO attainment and 74% higher goodput compared to state-of-the-art systems.
• Score: 12.377283389338709
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces AdaServe, the first LLM serving system to support SLO customization through fine-grained speculative decoding. AdaServe leverages the logits of a draft model to predict the speculative accuracy of tokens and employs a theoretically optimal algorithm to construct token trees for verification. To accommodate diverse SLO requirements without compromising throughput, AdaServe employs a speculation-and-selection scheme that first constructs candidate token trees for each request and then dynamically selects tokens to meet individual SLO constraints while optimizing throughput. Comprehensive evaluations demonstrate that AdaServe achieves up to 73% higher SLO attainment and 74% higher goodput compared to state-of-the-art systems. These results underscore AdaServe's potential to enhance the efficiency and adaptability of LLM deployments across varied application scenarios.

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