An adaptive parallel flow for power distribution network simulation using discrete Fourier transform

  • Authors:
  • Xiang Hu;Wenbo Zhao;Peng Du;Amirali Shayan;Chung-Kuan Cheng

  • Affiliations:
  • University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA;University of California, San Diego, La Jolla, CA

  • Venue:
  • Proceedings of the 2010 Asia and South Pacific Design Automation Conference
  • Year:
  • 2010

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Abstract

A frequency-time-domain co-simulation flow using discrete Fourier transform (DFT) is introduced in this paper to analyze large power distribution networks (PDN's). The flow not only allows designers to gain an insight to the frequency-domain characteristics of the PDN but also to obtain accurate time-domain voltage responses according to different load current profiles. An adaptive method achieves accurate results within even shorter time compared to the basic DFT flow. In addition, parallel processing is incorporated which leads to a significant reduction in simulation time. Error bounds of the DFT flow are derived to assure the accuracy of simulation results. Experimental results show that the proposed flow has a relative error of 0.093% and a speedup of 10x compared to SPICE transient simulation with a single processor.