Techniques for CAD Tool Parameter Auto-tuning in Physical Synthesis: A Survey (Invited Paper)

As the technology node of integrated circuits rapidly goes beyond 5nm, synthesis-centric modern very large-scale integration (VLSI) design flow is facing ever-increasing design complexity and suffering the pressure of time-to-market. During the past decades, synthesis tools have become progressively sophisticated and offer countless tunable parameters that can significantly influence design quality. Nevertheless, owing to the time-consuming tool evaluation plus a limitation to one possible parameter combination per synthesis run, manually searching for optimal configurations of numerous parameters proves to be elusive. What's worse, tiny perturbations to these parameters can result in very large variations in the Quality-of-Results (QoR). Therefore, automatic tool parameter tuning to reduce human cost and tool evaluation cost is in demand. Machine-learning techniques provide chances to enable the auto-tuning process of tool parameters. In this paper, we will survey the recent pace of progress on advanced parameter auto-tuning flows of physical synthesis tools. We sincerely expect this survey can enlighten the future development of parameter auto-tuning methodologies.