InstantGR: Scalable GPU Parallelization for Global Routing

Global routing plays a crucial role in electronic design automation (EDA), serving not only as a means of optimizing routing but also as a tool for estimating routability in earlier stages such as logic synthesis and physical planning. However, these scenarios often require global routing on unpartitioned large designs, posing unique challenges in scalability, both in terms of runtime and design size. To tackle this issue, this paper introduces useful techniques for parallelizing large-scale global routing that can significantly increase parallelism and thus reduce runtime. Building upon these techniques, we have developed an open-source GPU-based global router that achieves the state-of-the-art results in the latest ISPD'24 Contest benchmarks, thereby showcasing the effectiveness of our methods. The source code of this work is available at https://github.com/cuhk-eda/InstantGR.