Mixed integer programming models for detailed placement

  • Authors:
  • Shuai Li;Cheng-Kok Koh

  • Affiliations:
  • Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA

  • Venue:
  • Proceedings of the 2012 ACM international symposium on International Symposium on Physical Design
  • Year:
  • 2012

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Abstract

Existing detailed placement optimization methods typically involve the use of enumeration to determine the optimal location of a small number of cells. We propose two Mixed Integer Programming (MIP) models that can optimize the detailed placement of more cells efficiently. Compared with existing models, the first proposed model has fewer integer variables. The second proposed model, derived based on Dantzig-Wolfe decomposition principle, is with tighter bounds during its solution. Experimental results show that both models are capable of optimizing in reasonable time the detailed placement of much larger problem instances than existing models. Experiments on large-scale real benchmark circuits also show that detailed placer based on advanced MIP models can effectively reduce half-perimeter wirelengh (HPWL), as well as routed wirelength and vertical vias, of the original placement results generated by enumeration approach.