Cluster refinement for block placement

  • Authors:
  • Jin Xu;Pei-Ning Guo;Chung-Kuan Cheng

  • Affiliations:
  • Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA

  • Venue:
  • DAC '97 Proceedings of the 34th annual Design Automation Conference
  • Year:
  • 1997

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Abstract

We propose an iterative optimization approach for mixedmacro-cell and standard-cell placement, which minimizes the chipsize and interconnection wire length at the same time. We present abranch-and-bound algorithm which efficiently searches for the optimalsolution by evaluating all of the possible configurations on theselected cluster to minimize the gap distance between the ceilingand the floor. A virtual grid and permutation order are generateddynamically to eliminate redundant branches, which was the causeof much higher complexity in other approaches. Experimentalresults on the MCNC benchmark circuits show that the algorithmachieves very competitive results to manual design.