Constraint-Based Random Stimuli Generation for Hardware Verification

Yehuda Naveh, Michal Rimon, Itai Jaeger, Yoav Katz, Michael Vinov, Eitan s Marcu, Gil Shurek

Abstract


We report on random stimuli generation for hardware verification at IBM as a major applica-tion of various artificial intelligence technologies, including knowledge representation, expert systems, and constraint satisfaction. For more than a decade we have developed several related tools, with huge payoffs. Research and development around this application are still thriving, as we continue to cope with the ever-increasing complexity of modern hardware systems and demanding business environments.

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