Abstract Many applications of FPGAs, especially logic emulation and custom computing, require the quick placement and routing of circuit designs. In these applications, the advantages FPGA-based systems have over software simulation are diminished by the long run-times of current CAD software used to map the circuit onto FPGAs. To improve the run-time advantage of FPGA systems, users may be willing to trade some mapping quality for a reduction in CAD tool runtimes. In this paper, we seek to establish how much quality degradation is necessary to achieve a given runtime improvement. For this purpose, we implemented and investigated numerous placement and routing algorithms for FPGAs. We also developed new tradeoff-oriented algorithms, where a tuning parameter can be used to control this quality vs. runtime tradeoff. We show how different algorithms can achieve different points within this tradeoff spectrum, as well as how a single algorithm can be tuned to form a curve in the spectrum. We demonstrate that the algorithms vary widely in their tradeoffs, with the fastest algorithm being 8x faster than the slowest, and the highest quality algorithm being 5x better than the least quality algorithm. Compared to the commercial Xilinx CAD tools, we can achieve a 3x speed-up by allowing 1.27x degradation in quality, and a factor of 1.6x quality improvement with 2x slowdown
