Constrained Stimulus Generation with Self-Adjusting Using Tabu Search with Memory

Yanni ZHAO  Jinian BIAN  Shujun DENG  Zhiqiu KONG  Kang ZHAO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A   No.12   pp.3086-3093
Publication Date: 2009/12/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E92.A.3086
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
Category: Logic Synthesis, Test and Verfication
Keyword: 
constrained random simulation,  stimulus generation,  SAT,  piecewise-uniform,  tabu search with memory,  

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Summary: 
Despite the growing research effort in formal verification, industrial verification often relies on the constrained random simulation methodology, which is supported by constraint solvers as the stimulus generator integrated within simulator, especially for the large design with complex constraints nowadays. These stimulus generators need to be fast and well-distributed to maintain simulation performance. In this paper, we propose a dynamic method to guide stimulus generation by SAT solvers. An adjusting strategy named Tabu Search with Memory (TSwM) is integrated in the stimulus generator for the search and prune processes along with the constraint solver. Experimental results show that the method proposed in this paper could generate well-distributed stimuli with good performance.