PD Constraint-aware Physical/Logical Topology Co-Design for Network on Wafer
Qize Yang, Taiquan Wei, Sihan Guan, Chengran Li, Haoran Shang, Jinyi Deng, Huizheng Wang, Chao Li, Lei Wang, Yan Zhang, Shouyi Yin, Yang Hu
Abstract
As cluster scales for LLM training expand, waferscale chips, characterized by the high integration density and bandwidth, emerge as a promising approach to enhancing training performance.The role of Network on Wafer (NoW) is becoming increasingly significant, which puts an emphasis on two facts: physical and logical topology.However, existing networks fail to co-design both aspects.Additionally, physical topology typically focuses on optimizing communication or computation separately, neglecting opportunities to improve overall training performance.In this paper, we propose a physical design (PD) constraint-aware joint optimization strategy, developing mesh-switch physical topology and a dual-granularity logical topology.Mesh-switch leverages the high integration density of mesh and the efficient communication performance of fat tree, optimizing the allocation of on-chip
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