A Work-Efficient Distributed Algorithm for Reachability Analysis

Grumberg, Orna; Heyman, Tamir; Schuster, Assaf

doi:10.1007/978-3-540-45069-6_5

Cited by 21 publications

(17 citation statements)

References 18 publications

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“…To achieve scalability, researchers have recently focused on memory load distribution. [20] has suggested to employ a host processor to manage the job queue for load-balance purposes and to minimize the overlap of image computation by slicing boolean functions with optimal choices of variables. However, no speedup is achieved.…”

Section: Resultsmentioning

confidence: 99%

Saturation NOW

Chung¹,

Ciardo²

2004

First International Conference on the Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings.

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We present a distributed version of the saturation algorithm for symbolic state-space generation of discrete-state models. The execution is strictly sequential but utilizes the overall available memory. Thanks to a level-based allocation of the decision diagram nodes onto the workstations, no additional node or work is created. A dynamic memory load balancing heuristic helps coping with the uneven growth of the decision diagram levels allocated to each workstation. Experiments on a conventional network of workstations show that the runtime of our distributed implementation is close to the sequential one even when balancing is triggered, while it is of course much better when the sequential implementation is forced to rely on virtual memory.

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Section: Resultsmentioning

confidence: 99%

Saturation NOW

Chung¹,

Ciardo²

2004

First International Conference on the Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings.

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“…However, how the timings were measured and whether they were instrumented in the code, or obtained using a profiling tool, is not described in the paper. Grumberg et al successfully parallelised a symbolic state-space exploration algorithm on a NOW using dynamic load balancing [15], based on the workstealing techniques in [16]. Their evaluation of the algorithm includes an estimate of how the load is balanced according to the dynamic partitioning method used.…”

Section: Related Workmentioning

confidence: 98%

Measuring and Evaluating Parallel State-Space Exploration Algorithms

Ezekiel

Lüttgen

2008

Electronic Notes in Theoretical Computer Science

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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.

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“…Distributing the computational work may increase synchronization cost significantly because of the complex data structures. However, in [12] authors presented a novel distributed, symbolic algorithm for reachability analysis that can effectively exploit a large number of machines working in parallel. The novelty of the algorithm is its dynamic allocation and reallocation of processes to tasks and its mechanism for recovery, from local state explosion.…”

Section: Related Workmentioning

confidence: 99%

Parallel Saturation Based Model Checking

Voros

Szabo

́mbor

et al. 2011

2011 10th International Symposium on Parallel and Distributed Computing

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Formal verification is becoming a fundamental step of safety-critical and model-based software development. As part of the verification process, model checking is one of the current advanced techniques to analyze the behavior of a system. In this paper, we examine an existing parallel model checking algorithm and we propose improvements to eliminate some computational bottlenecks. Our measurements show that the resulting new algorithm has better scalability and performance than both the former parallel approach and the sequential algorithm.

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A Work-Efficient Distributed Algorithm for Reachability Analysis

Cited by 21 publications

References 18 publications

Saturation NOW

Saturation NOW

Measuring and Evaluating Parallel State-Space Exploration Algorithms

Parallel Saturation Based Model Checking

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