  This paper is concerned with developing a software tool, called IMPaCT, for
the parallelized verification and controller synthesis of large-scale
stochastic systems using interval Markov chains (IMCs) and interval Markov
decision processes (IMDPs), respectively. The tool serves to (i) construct
IMCs/IMDPs as finite abstractions of underlying original systems, and (ii)
leverage interval iteration algorithms for formal verification and controller
synthesis over infinite-horizon properties, including safety, reachability, and
reach-avoid, while offering convergence guarantees. IMPaCT is developed in C++
and designed using AdaptiveCpp, an independent open-source implementation of
SYCL, for adaptive parallelism over CPUs and GPUs of all hardware vendors,
including Intel and NVIDIA. IMPaCT stands as the first software tool for the
parallel construction of IMCs/IMDPs, empowered with the capability to leverage
high-performance computing platforms and cloud computing services.
Specifically, parallelism offered by IMPaCT effectively addresses the
challenges arising from the state-explosion problem inherent in
discretization-based techniques applied to large-scale stochastic systems. We
benchmark IMPaCT on several physical case studies, adopted from the ARCH tool
competition for stochastic models, including a 2-dimensional robot, a
3-dimensional autonomous vehicle, a 5-dimensional room temperature system, and
a 7-dimensional building automation system. To show the scalability of our
tool, we also employ IMPaCT for the formal analysis of a 14-dimensional case
study.
