A Hierarchical Approach for Incremental Floorplan Based on Genetic Algorithms

Yongpan Liu, Huazhong Yang, Rong Luo, Hui Wang

Abstract: With more and more interactions between high-level and physical-level design, incremental floorplan is becoming a must to deal with such complexity. In this paper, we propose a hierarchical approach for incremental floorplan based on genetic algorithms. It combines the power of genetic optimization and partition algorithms to provide smooth controllable quality/runtime tradeoffs. Experiments show that our hierarchy approach can provide magnitudes of speedup compared to traditional flatten floorplan using genetic algorithms without much area overhead. Furthermore, incremental change is also supported in such a hierarchical floorplanner, which makes it very promising to be used in the high-level analysis and synthesis environment.