Jiří Barnat

Temporal Logic Control of Discrete-Time Piecewise Affine Systems

We present a computational framework for automatic synthesis of a feedback control strategy for a discrete-time piecewise affine (PWA) system from a specification given as a linear temporal logic (LTL) formula over an arbitrary set of linear predicates in the systems state variables. Our approach consists of two main steps. First, by defining appropriate partitions for its state and input spaces, we construct a finite abstraction of the PWA system in the form of a control transition system. Second, by leveraging ideas and techniques from LTL model checking and Rabin games, we develop an algorithm to generate a control strategy for the finite abstraction. While provably correct and robust to state measurements and small perturbations in the applied inputs, the overall procedure is conservative and expensive. The proposed algorithms have been implemented as a software package and made available for download. Illustrative examples are included.

DiVinE: a tool for distributed verification

We present a tool for cluster-based LTL model-checking and reachability analysis. The tool incorporates several novel distributed-memory 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.

Scalable multi-core LTL model-checking

Recent development in computer hardware has brought more wide-spread emergence of shared-memory, multi-core systems. These architectures offer opportunities to speed up various tasks - among others LTL model checking. In the paper we show a design for a parallel shared-memory LTL model checker, that is based on a distributed-memory algorithm. To achieve good scalability, we have devised and experimentally evaluated several implementation techniques, which we present in the paper.

DiVinE 3.0: an explicit-state model checker for multithreaded c & c++ programs

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.

Revisiting resistance speeds up I/O-efficient LTL model checking

Revisiting resistant graph algorithms are those, whose correctness is not vulnerable to repeated edge exploration. Revisiting resistant I/O efficient graph algorithms exhibit considerable speed-up in practice in comparison to nonrevisiting resistant algorithms. In the paper we present a new revisiting resistant I/O efficient LTL model checking algorithm. We analyze its theoretical I/O complexity and we experimentally compare its performance to already existing I/O efficient LTL model checking algorithms.

Designing fast LTL model checking algorithms for many-core GPUs

Recent technological developments made various many-core hardware platforms widely accessible. These massively parallel architectures have been used to significantly accelerate many computation demanding tasks. In this paper, we show how the algorithms for LTL model checking can be redesigned in order to accelerate LTL model checking on many-core GPU platforms. Our detailed experimental evaluation demonstrates that using the NVIDIA CUDA technology results in a significant speedup of the verification process. Together with state space generation based on shared hash-table and DFS exploration, our CUDA accelerated model checker is the fastest among state-of-the-art shared memory model checking tools. The effective utilization of the CUDA technology, however, is quite often reduced by the costly preparation of suitable data structures and limited to small or middle-sized instances due to space limitations, which is also the case of our CUDA-aware LTL model checking solutions. Hence, we further suggest how to overcome these limitations by multi-core construction of the compact data structures and by employing multiple CUDA devices for acceleration of fine-grained communication-intensive parallel algorithms for LTL model checking.

Distributed Algorithms for SCC Decomposition

We study existing parallel algorithms for the decomposition of a partitioned graph into its strongly connected components (SCCs). In particular, we identify several individual procedures that the algorithms are assembled from and show how to assemble a new and more efficient algorithm, called Recursive OBF (OBFR), to solve the decomposition problem. We also report on a thorough experimental study to evaluate the new algorithm. It shows that it is possible to perform SCC decomposition in parallel efficiently and that OBFR, if properly implemented, is the best choice in most cases.

A Time-Optimal On-the-Fly Parallel Algorithm for Model Checking of Weak LTL Properties

One of the most important open problems of parallel LTL model-checking is to design an on-the-fly scalable parallel algorithm with linear time complexity. Such an algorithm would give the optimality we have in sequential LTL model-checking. In this paper we give a partial solution to the problem. We propose an algorithm that has the required properties for a very rich subset of LTL properties, namely those expressible by weak Buchi automata.

High-performance analysis of biological systems dynamics with the DiVinE model checker

The current interest in systems biology is to gain a better understanding of how the complex dynamic behaviour of the cell emerges from mutual interactions of molecular species. When solving such a nontrivial goal, biological data have to be necessarily integrated with mathematical modelling and computer analysis. Since the key aspect of biological modelling is based on unifying several kinds of data captured in terms of large-scale biological networks, scalable and automatized methods are necessary to obtain novel predictions and understanding. In this review, we provide a brief description of the tool DiVinE adapted for automatized analysis of biological systems dynamics. The tool employs high-performance computing techniques to enable analysis of large models.

Cluster-Based LTL model checking of large systems

In recent years a bundle of parallel and distributed algorithms for verification of finite state systems has appeared. We survey distributed-memory enumerative LTL model checking algorithms designed for networks of workstations communicating via MPI. In the automata-based approach to LTL model checking the problem is reduced to the accepting cycle detection problem in a graph. Distributed algorithms, in opposite to sequential ones, cannot rely on depth-first search postorder which is essential for efficient detection of accepting cycles. Therefore, diverse conditions that characterise the existence of cycles in a graph have to be employed in order to come up with efficient and practical distributed algorithms. We compare these algorithms both theoretically and experimentally and determine cases where particular algorithms can be successful.