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WSC-LLM: Efficient LLM Service and Architecture Co-exploration for Wafer-scale Chips

Zheng Xu, Dehao Kong, Jiaxin Liu, Jinxi Li, Jingxiang Hou, Xu Dai, Chao Li, Shaojun Wei, Yang Hu, Shouyi Yin

2025Year
22Citations
4Top-tier citations

Abstract

The deployment of large language models (LLMs) imposes significant demands on computing, memory, and communication resources.Wafer-scale technology enables the high-density integration of multiple single-die chips with high-speed Die-to-Die (D2D) interconnections, presenting a promising solution to meet these demands arising from LLMs.However, given the limited wafer area, a trade-off needs to be made among computing, storage, and communication resources.Maximizing the benefits and minimizing the drawbacks of wafer-scale technology is crucial for enhancing the performance of LLM service systems, which poses challenges to both architecture and scheduling.Unfortunately, existing methods cannot effectively address these challenges.To bridge the gap, we propose WSC-LLM, an architecture and scheduling co-exploration framework.We first define a highly configurable general hardware template designed to explore optimal architectural parameters for wafer-scale chips.Based on it, we

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