CAREER: Robust Behavioral Fault Simulation Algorithms for Multilevel Simulation

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This research focuses on improving simulation and test methodologies through the use of Concurrent Simulation (CS) and Multiple Domain Concurrent Simulation (MDCS) algorithms. This project develops an efficient behavioral fault simulation architecture that integrates well with structural and RTL models. The inherent ability of CS to represent and store only unique behaviors from the fault free experiment allows for excellent internal observation and comparative experimentation. Furthermore, the use of MDCS algorithms provides compression techniques for large simulations, overcoming memory bottlenecks while supporting the creation of multiple experiment scenarios. This allows a designer to vary parameters within any model and simulate it against other model configurations in a single simulation. Activities being explored under this grant include: (a) Developing algorithms for behavioral fault simulation, observability and signature traces using CS and MDCS; (b) Reduction of memory requirements through enhanced erratic experiment (infinite loop) detection, experiment compression using MDCS algorithms and fault dropping. (c) Evaluation of algorithms that allow the seamless integration of multilevel models.