Abstract
This paper presents a scalable method for parallel symbolic on-the-fly model checking in a distributed memory environment. Our method combines a scheme for on-the-fly model checking for safety properties with a scheme for scalable reachability analysis. We suggest an efficient, BDD-based algorithm for a distributed construction of a counterexample. The extra memory requirement for counterexample generation is evenly distributed among the processes by a memory balancing procedure. At no point during computation does the memory of a single process contain all the data. This enhances scalability. Collaboration between the parallel processes during counterexample generation reduces memory utilization for the backward step. We implemented our method on a standard, loosely- connected environment of workstations, using a high-performance model checker. Our initial performance evaluation, carried out on several large circuits, shows that our method can check models that are too large to fit in the memory of a single node. Our on-the-fly approach may find counterexamples even when the model is too large to fit in the memory of the parallel system.
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Ben-David , S., Grumberg , O., Heyman , T. et al. Scalable distributed on-the-fly symbolic model checking. STTT 4, 496–504 (2003). https://doi.org/10.1007/s10009-002-0093-2
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DOI: https://doi.org/10.1007/s10009-002-0093-2