Efficient Conflict-Based Learning in an RTL Circuit Constraint Solver

  • Authors:
  • M. K. Iyer;G. Parthasarathy;K.-T. Cheng

  • Affiliations:
  • University of California - Santa Barbara;University of California - Santa Barbara;University of California - Santa Barbara

  • Venue:
  • Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
  • Year:
  • 2005

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Abstract

We present new techniques for improving search in a hybrid Davis-Putnam-Logemann-Loveland based constraint solver for RTL circuits (HDPLL). In earlier work on HDPLL,the authors combined solvers for integer and Boolean domains using finite-domain constraint propagation with heuristic conflict-based learning. In this work, we describe a new algorithm that extends the conflict-based unique-implication point learning in Boolean SAT solvers to hybrid Boolean-Integer domains in HDPLL. We describe data-structures for efficient constraint propagation on the hybrid learned relations, similar to two-literal watching in Boolean SAT. We demonstrate that these new techniques provide considerable performance benefits when compared with other combinations of decision theories.