Title page for ETD etd-01282005-102938

Type of Document Dissertation
Author Zhang, Liang
Author's Email Address liang@vt.edu
URN etd-01282005-102938
Title Design Verification for Sequential Systems at Various Abstraction Levels
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Hsiao, Michael S. Committee Chair
Lu, Guo-Quan Committee Member
Martin, Thomas L. Committee Member
Shimozono, Mark M. Committee Member
Tront, Joseph G. Committee Member
  • Bounded Model Checking
  • Formal Verification
  • SAT
  • Simulation
  • ATPG
Date of Defense 2005-01-27
Availability unrestricted
With the ever increasing complexity of digital systems, functional verification has become a daunting task to circuit designers. Functional verification alone often surpasses 70% of the total development cost and the situation has been projected to continue to worsen. The most critical limitations of existing techniques are the capacity issue and the run-time issue. This dissertation addresses the functional verification problem using a unified approach, which utilizes different core algorithms at various abstraction levels. At the logic level, we focus on incorporating a set of novel ideas to existing formal verification approaches. First, we present a number of powerful optimizations to improve the performance and capacity of a typical SAT-based bounded model checking framework. Secondly, we present a novel method for performing dynamic abstraction within a framework for abstraction-refinement based model checking. Experiments on a wide range of industrial designs have shown that the proposed optimizations consistently provide between 1-2 orders of magnitude speedup and can be extremely useful in enhancing the efficacy of existing formal verification algorithms. At the register transfer level, where the formal verification is less likely to succeed, we developed an efficient ATPG-based validation framework, which leverages the high-level circuit information and an improved observability-enhanced coverage to generate high quality validation sequences. Experiments show that our approach is able to generate high quality validation vectors, which achieve both high tag coverage and high bug coverage with extremely low computational cost.
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