A Fast Power Network Optimization Algorithm for Improving Dynamic IR-drop

As the power consumption of an electronic equipment varies more severely, the device voltages in a modern design may fluctuate violently as well. Consideration of dynamic IR-drop becomes indispensable to current power network design. Since solving voltage violations according to all power consumption files in all time slots is impractical in reality, this paper applies a clustering based approach to find representative power consumption files and shows that most IR-drop violations can be repaired if we repair the power network according to these files. In order to further reduce runtime, we also propose an efficient and effective power network optimization approach. Compared to the intuitive approach which repairs a power network file by file, our approach alternates between different power consumption files and always repairs the file which has the worst IR-drop violation region that involves more power consumption files in each iteration. Since many violations can be resolved at the same time, this method is much faster than the iterative approach. The experimental results show that the proposed algorithm can not only eliminate voltage violations efficiently but also construct a power network with less routing resource.