GPU/ML-Enhanced Large Scale Global Routing Contest
Rongjian Liang, Anthony Agnesina, Wen-Hao Liu, Haoxing Ren
Abstract
Modern VLSI design flows demand scalable global routing techniques applicable across diverse design stages. In response, the ISPD 2024 contest pioneers the first GPU/ML-enhanced global routing competition, selecting advancements in GPU-accelerated computing platforms and machine learning techniques to address scalability challenges. Large-scale benchmarks, containing up to 50 million cells, offer test cases to assess global routers' runtime and memory scalability. The contest provides simplified input/output formats and performance metrics, framing global routing challenges as mathematical optimization problems and encouraging diverse participation. Two sets of evaluation metrics are introduced: the primary one concentrates on global routing applications to guide post-placement optimization and detailed routing, focusing on congestion resolution and runtime scalability. Special honor is given based on the second set of metrics, placing additional emphasis on runtime efficiency and aiming at guiding early-stage planning.