用GAN优化布线批次，提速40%且质量几乎不变
GANGR: GAN-Assisted Scalable and Efficient Global Routing Parallelization
- 用WGAN生成高质量布线批次，减少冲突
- 在ISPD'24基准上实现40%运行时间降低
- 适合追求高效并行化的大规模芯片设计
全局布线是电子设计自动化中关键环节，用于早期评估现代集成电路的可布线性，涉及拥塞、功耗和设计复杂度。批处理是高性能全局布线器的核心，将网表分组以支持并行处理和资源高效利用，从而改善内存使用、硬件可扩展性及拥塞控制。然而，传统批处理方法依赖计算昂贵的启发式策略，常导致次优结果：批次过大引发网表冲突、批次过多降低并行效率、生成时间过长，最终限制可扩展性和效率。本文提出一种基于Wasserstein生成对抗网络（WGAN）的新型批处理算法，通过生成更少、质量更高的批次，在更短时间内实现更有效的并行化。该算法在最新的ISPD'24竞赛基准上测试，相较当前最优路由器，运行时间最多降低40%，路由质量仅下降0.002%。
原文摘要 · Abstract (English)
Global routing is a critical stage in electronic design automation (EDA) that enables early estimation and optimization of the routability of modern integrated circuits with respect to congestion, power dissipation, and design complexity. Batching is a primary concern in top-performing global routers, grouping nets into manageable sets to enable parallel processing and efficient resource usage. This process improves memory usage, scalable parallelization on modern hardware, and routing congestion by controlling net interactions within each batch. However, conventional batching methods typically depend on heuristics that are computationally expensive and can lead to suboptimal results (oversized batches with conflicting nets, excessive batch counts degrading parallelization, and longer batch generation times), ultimately limiting scalability and efficiency. To address these limitations, a novel batching algorithm enhanced with Wasserstein generative adversarial networks (WGANs) is introduced in this paper, enabling more effective parallelization by generating fewer higher-quality batches in less time. The proposed algorithm is tested on the latest ISPD'24 contest benchmarks, demonstrating up to 40% runtime reduction with only 0.002% degradation in routing quality as compared to state-of-the-art router.
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