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In this paper we consider the search in large state spaces with high branching factors and an objective function to be maximized. Our method portfolio, which we refer to as heuristically guided swarm tree search, is randomized, as it consists of several Monte-Carlo runs, and guided, as it relies on fitness selection. We apply different search enhancement… (More)

- Stefan Edelkamp, Damian Sulewski, Cengizhan Yücel
- ICAPS
- 2010

This paper exploits parallel computing power of graphics cards to accelerate state space search. We illustrate that modern graphics processing units (GPUs) have the potential to speed up breadth-first search significantly. For a bitvector representation of the search frontier, GPU algorithms with one and two bits per state are presented. Efficient perfect… (More)

- Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski
- SPIN
- 2009

We present algorithms for parallel probabilistic model checking on general purpose graphic processing units (GPGPUs). For this purpose we exploit the fact that some of the basic algorithms for probabilistic model checking rely on matrix vector multiplication. Since this kind of linear algebraic operations are implemented very efficiently on GPGPUs, the new… (More)

- Stefan Edelkamp, Damian Sulewski
- SPIN
- 2010

We accelerate state space exploration for explicit-state model checking by executing complex operations on the graphics processing unit (GPU). In contrast to existing approaches enhancing model checking through performing parallel matrix operations on the GPU, we parallelize the breadth-first layered construction of the state space graph. For efficient… (More)

- Damian Sulewski, Stefan Edelkamp, Peter Kissmann
- ICAPS
- 2011

- Stefan Edelkamp, Damian Sulewski
- MoChArt
- 2010

- Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs
- International Journal on Software Tools for…
- 2010

We present algorithms for parallel probabilistic model checking on general purpose graphic processing units (GPGPUs). Our improvements target the numerical components of the traditional sequential algorithms. In particular, we capitalize on the fact that in most of them operations like matrix–vector multiplication and solving systems of linear equations are… (More)

This paper exploits parallel computing power of the graphics card for the enhanced enumeration of state spaces. We illustrate that modern graphics processing units (GPUs) have the potential to speed up state space search significantly. For an bitvector representation of the search frontier, GPU algorithms with one and two bits per state are presented. For… (More)

In this paper we improve large-scale disk-based model checking by shifting complex numerical operations to the graphic card, enjoying that during the last decade graphics processing units (GPUs) have become very powerful. For disk-based graph search, the delayed elimination of duplicates is the performance bottleneck as it amounts to sorting large state… (More)

- Stefan Edelkamp, Damian Sulewski
- 2008 Sixth IEEE International Conference on…
- 2008

Solid state disks based on flash memory are an apparent alternative to hard disks for external memory search. Random reads are much faster, while random writes are generally not. In this paper, we illustrate how this influences the time-space trade-offs for scaling semi-external LTL model checking algorithms that request a constant number of bits per state… (More)