摘要
In this paper, we study the interconnect buffer and wiresizing optimization problem under a distributed RLC model to optimize not just area and delay, but also crosstalk for RLC circuit with non-monotone signal response. We present a new multiobjective genetic algorithm（MOGA） which uses a single objective sorting（SOS） method for constructing the non-dominated set to solve this multi-objective interconnect optimization problem. The MOGA/SOS optimal algorithm provides a smooth trade-off among signal delay, wave form, and routing area. Furthermore, we use a new method to calculate the lower bound of crosstalk. Extensive experimental results show that our algorithm is scalable with problem size. Furthermore, compared to the solution based on an Elmore delay model, our solution reduces the total routing area by up to 30%, the delay to the critical sinks by up to 25%, while further improving crosstalk up to 25.73% on average.
In this paper, we study the interconnect buffer and wiresizing optimization problem under a distributed RLC model to optimize not just area and delay, but also crosstalk for RLC circuit with non-monotone signal response. We present a new multiobjective genetic algorithm（MOGA） which uses a single objective sorting（SOS） method for constructing the non-dominated set to solve this multi-objective interconnect optimization problem. The MOGA/SOS optimal algorithm provides a smooth trade-off among signal delay, wave form, and routing area. Furthermore, we use a new method to calculate the lower bound of crosstalk. Extensive experimental results show that our algorithm is scalable with problem size. Furthermore, compared to the solution based on an Elmore delay model, our solution reduces the total routing area by up to 30%, the delay to the critical sinks by up to 25%, while further improving crosstalk up to 25.73% on average.
基金
Supported by the National Natural Science Foundation of China (90307017)
