Robust mixed-size placement under tight white-space constraints

A novel and very simple correct-by-construction top-down methodology for high-utilization mixed-size placement is presented. The Polarbear algorithm combines recursive cut-size-driven partitioning with fast and scalable legalization of every placement subproblem generated by every partitioning. The feedback provided by the legalizer at all stages of partitioning improves final placement quality significantly on standard IBM benchmarks and dramatically on low-white-space adaptations of them. Compared to Feng Shui 5.1 and Capo 9.3, Polarbear is the only tool that can consistently find high-quality placements for benchmarks with less than 5% white space. With white space at 5%, Polarbear beats Capo 9.3 by 10% in average total wirelength while Feng Shui 5.1 frequently fails to find legal placements altogether. With 20% white space, POLARBEAR still beats Capo 9.3 by 1% and Feng Shui 5.1 by 1% in average total wirelength, in comparable run times.