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Per-RMAP: Feasibility-Seeking and Superiorization Methods for Floorplanning with I/O Assignment.

Shan Yu1, Yair Censor2, Ming Jiang1

  • 1Department of Information and Computational Sciences, School of Mathematical Sciences, Peking University, Beijing, China.

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Summary
This summary is machine-generated.

This study introduces a novel resetting strategy for feasibility-seeking algorithms in floorplanning, enhancing convergence for complex constraints. The approach, including superiorization methodology, yields near-optimal wirelengths with efficient performance.

Keywords:
I/O assignmentfeasibility-seekingfloorplanningprojection algorithmssuperiorization method

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Operations Research

Background:

  • Floorplanning involves complex, heterogeneous constraints, challenging traditional algorithms.
  • Conventional projection-based methods struggle with non-convex constraint sets common in floorplanning.

Purpose of the Study:

  • To develop a robust feasibility-seeking algorithm for complex floorplanning constraints.
  • To improve convergence and solution quality in floorplanning using a novel resetting strategy and superiorization methodology.

Main Methods:

  • A resetting strategy is proposed to enhance the convergence of projection-based feasibility-seeking algorithms.
  • The superiorization methodology is applied to floorplanning for the first time, using perturbations to optimize wirelength.
  • The algorithmic flow is designed to be extendable to various constraints, including I/O assignment.

Main Results:

  • The proposed algorithm obtains legal floorplans with wirelength only 3% inferior to optimal results.
  • Performance is competitive, only two times slower than branch-and-bound in its current prototype.
  • Incorporating I/O assignment constraints resulted in an 8% wirelength improvement.

Conclusions:

  • The novel resetting strategy effectively addresses convergence issues in feasibility-seeking floorplanning.
  • Superiorization methodology offers a powerful approach for optimizing floorplanning solutions.
  • The proposed algorithmic flow demonstrates versatility and effectiveness for complex floorplanning problems.