Parallel State Space Exploration Research Articles

Parallel reachability analysis of hybrid systems in XSpeed

Reachability analysis techniques are at the core of the current state-of-the-art technology for verifying safety properties of cyber-physical systems (CPS). The current limitation of such techniques is their inability to scale their analysis by exploiting the powerful parallel multi-core architectures now available in modern CPUs. Here, we address this limitation by presenting for the first time a suite of parallel state-space exploration algorithms that, leveraging multi-core CPUs, enable to scale the reachability analysis for linear continuous and hybrid automaton models of CPS. To demonstrate the achieved performance speedup on multi-core processors, we provide an empirical evaluation of the proposed parallel algorithms on several benchmarks comparing their key performance indicators. This enables also to identify which is the ideal algorithm and the parameters to choose that would maximize the performances for a given benchmark.

Measuring and Evaluating Parallel State-Space Exploration Algorithms

We argue in this paper that benchmarking should be complemented by direct measurement of parallelisation overheads when evaluating parallel state-space exploration algorithms. This poses several challenges that so far have not been addressed in the literature: what exactly are those overheads, how can and cannot they be measured, and how should system models be selected in order to expose the causes of parallelisation (in)efficiencies? We discuss and answer these questions based on our experience with parallelising Saturation – a symbolic algorithm for generating state-spaces of asynchronous system models – on a shared-memory architecture. Doing so will hopefully spare newcomers to the growing PDMC community from having to learn these lessons the hard way, as we did over a painful period of almost three years.