Novel probabilistic combinational equivalence checking

  • Authors:
  • Shih-Chieh Wu;Chun-Yao Wang;Yung-Chih Chen

  • Affiliations:
  • Department of Computer Science, National TsingHua University, HsinChu, Taiwan, R.O.C.;Department of Computer Science, National TsingHua University, HsinChu, Taiwan, R.O.C.;Department of Computer Science, National TsingHua University, HsinChu, Taiwan, R.O.C.

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Year:
  • 2008

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Abstract

Exact approaches to combinational equivalence checking, such as automatic test pattern generation-based, binary decision diagrams (BDD)-based, satisfiability-based, and hybrid approaches, have been proposed over the last two decades. Recently, we proposed another exact approach using signal probability. This probability-based approach assigns probability values to the primary inputs and compares the corresponding output probability of two networks via a probability calculation process to assert if they are equivalent. The shortcoming of all these exact approaches is that if two networks are too complex to be handled, their equivalence cannot be determined, even with tolerance. An approximate approach, named the probabilistic approach, is a suitable way to give such an answer for those large circuits. However, despite generally being more efficient than exact approaches, the probabilistic approach faces a major concern of a non zero aliasing rate, which is the possibility that two different networks have the same output probability/signatures. Thus, minimizing aliasing rate is substantial in this area. In this paper, we propose a novel probabilistic approach based on the exact probability-based approach. Our approach exploits proposed probabilistic equivalence checking architecture to efficiently calculate the signature of network with virtually zero aliasing rate. We conduct experiments on a set of benchmark circuits, including large and complex circuits, with our probabilistic approach. Experimental results show that the aliasing rate is virtually-zero, e.g., 10-6013. Also, to demonstrate the effectiveness of our approach on error detection, we randomly inject errors into networks for comparison. As a resuit, our approach more efficiently detects the error than a commercial tool, Cadence LEC, does. Although our approach is not exact, it is practically useful. Thus, it can effectively complement exact methods to improve the efficiency and effectiveness of combination equivalence checking algorithms.