We describe a parallel simulated annealing algorithm for FPGA placement. The algorithm proposes and evaluates multiple moves in parallel, and has been incorporated into Altera’s Quartus II CAD system. Across a set of 18 industrial benchmark circuits, we achieve geometric average speedups during the quench of 2.7x and 4.0x on four and eight processors, respectively, with individual circuits achieving speedups of up to 3.6x and 5.9x. Over the course of the entire anneal, we achieve speedups of up to 2.8x and 3.7x, with geometric average speedups of 2.1x and 2.4x. Our algorithm is the first parallel placer to optimize for criteria other than wirelength, such as critical path length, and is one of the few deterministic parallel placement algorithms. We discuss the challenges involved in combining these two features and the new techniques we used to overcome them. We also quantify the impact of maintaining determinism on eight cores, and find that while it reduces performance by approximately 15% relative to an ideal speedup of 8.0x, hardware limitations are a larger factor and reduce performance by 30--40%. We then suggest possible enhancements to allow our approach to scale to 16 cores and beyond.

In this paper, we describe the application of two parallelization strategies to the Quartus II FPGA placer. The first uses a pipelining approach and achieves speedups of 1.3x on two processing cores. The second uses a parallel moves approach and achieves speedups of 2.2x on four cores. Unlike all previous parallel moves algorithms, ours is deterministic and always gives the same answer as the serial version of the algorithm, without any significant reduction in performance.