We present a tool for cluster-based LTL model-checking and reachability analysis. The tool incorporates several novel distributedmemory algorithms and provides a unique interface to use them. We describe the basic structure of the tool, discuss the main architecture decisions made, and briefly explain how the tool can be used.
The problem of decomposition of a directed graph into its strongly connected components is a fundamental graph problem inherently present in many scientific and commercial applications. In this paper we show how existing parallel algorithms can be reformulated in order to be accelerated by NVIDIA CUDA technology. In particular, we design a new CUDA-aware procedure for pivot selection and we redesign the parallel algorithms in order to allow for CUDA accelerated computation. We also experimentally demonstrate that with a single GTX 280 GPU card we can easily outperform optimal serial CPU implementation, which is particularly interesting result as unlike the serial CPU case, the asymptotic complexity of the parallel algorithms is not optimal.
Abstract. In this paper we propose a distributed algorithm for modelchecking LTL. In particular, we explore the possibility of performing nested depth-first search algorithm in distributed SPIN. A distributed version of the algorithm is presented, and its complexity is discussed.
We present a new release of the parallel and distributed LTL model checker DiVinE. The major improvement in this new release is an extension of the class of systems that may be verified with the model checker, while preserving the unique DiVinE feature, namely parallel and distributed-memory processing. Version 3.0 comes with support for direct model checking of (closed) multithreaded C/C++ programs, full untimed-LTL model checking of timed automata, and a general-purpose framework for interfacing with arbitrary system modelling tools.
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