Sub-quadratic objectives in quadratic placement

  • Authors:
  • Markus Struzyna

  • Affiliations:
  • University of Bonn, Bonn, Germany

  • Venue:
  • Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2013

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Abstract

This paper presents a new flexible quadratic and partitioning-based global placement approach which is able to optimize a wide class of objective functions, including linear, sub-quadratic, and quadratic net lengths as well as positive linear combinations of them. Based on iteratively re-weighted quadratic optimization, our algorithm extends the previous linearization techniques. If l is the length of some connection, most placement algorithms try to optimize l1 or l2. We show that optimizing lp with 1 p