Parallelizing A Symbolic Compositional Model-Checking Algorithm

We describe a parallel, symbolic, model-checking algorithm, built around a compositional reasoning method. The method constructs a collection of per-process (i.e., local) invariants, which together imply a desired global safety property. The local invariant computation is a simultaneous fixpoint evaluation, which easily lends itself to parallelization. Moreover, locality of reasoning helps limit both the frequency and the amount of cross-thread synchronization, leading' to good parallel performance. Experimental results show that the parallelized computation can achieve substantial speed-up, with reasonably small memory overhead.