Cypress: VLSI-Inspired PCB Placement with GPU Acceleration

Le résumé fourni par la source

The scale of printed circuit board (PCB) designs has increased significantly, with modern commercial designs featuring more than 10,000 components. However, the placement process heavily relies on manual efforts that take weeks to complete, highlighting the need for automated PCB placement methods. The challenges of PCB placement arise from its flexible design space and limited routing resources. Existing automated PCB placement tools have achieved limited success in quality and scalability. In contrast, very large-scale integration (VLSI) placement methods have proven to be scalable for designs with millions of cells and delivering high-quality results. Therefore, we propose Cypress, a scalable, GPU-accelerated PCB placement method inspired by VLSI. It incorporates tailored cost functions, constraint handling, and optimized techniques adapted for PCB layouts. In addition, there is an increasing demand for realistic and open-source benchmarks to (1) enable meaningful comparisons between tools and (2) establish performance baselines to track progress in PCB placement technology. To address this gap, we present a PCB benchmark suite synthesized from real commercial designs. We evaluate our method against state-of-the-art commercial and academic PCB placement tools with the benchmark suite. Our approach demonstrates a 1-5.9X higher routability on the proposed benchmarks. For fully routed designs, Cypress achieves 1-19.7X shorter routed track lengths. With GPU acceleration, Cypress delivers up to 492.3X speedup in run time. Finally, we demonstrate scalability to real commercial designs, a capability unmatched by existing tools.

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