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Simulating a Family of Tissue P Systems Solving SAT on the GPU

Miguel A. Martinez-del-Amor, Jesus Perez-Carrasco, Mario J. Perez-Jimenez
Research Group on Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Avda. Reina Mercedes s/n, 41012 Sevilla, Spain
Eleventh Brainstorming Week on Membrane Computing (11BWMC), 2013

@article{martinez2013simulating,

   title={Simulating a Family of Tissue P Systems Solving SAT on the GPU},

   journal={Eleventh Brainstorming Week on Membrane Computing (11BWMC)},

   year={2013},

   month={08/2013},

   pages={201-220},

   publisher={F{‘e}nix Editora},

   address={Sevilla, Espa{~n}a},

   keywords={GPU Computing 1 Introduction, Membrane computing, SAT, Tissue P Systems},

   isbn={978-84-940691-9-2},

   url={http://www.gcn.us.es/files/11bwmc/201_martinez_del_amor.pdf},

   author={Miguel A. Mart{‘i}nez-del-Amor and Jes{‘u}s P{‘e}rez-Carrasco and Mario J. P{‘e}rez-Jim{‘e}nez}

}

In order to provide efficient software tools to deal with large membrane systems, high-throughput simulators are required. Parallel computing platforms are good candidates, since they are capable of partially implementing the inherently parallel nature of the model. In this concern, today GPUs (Graphics Processing Unit) are considered as highly parallel processors, and they are being consolidated as accelerators for scientific applications. In fact, previous attempts to design P systems simulators on GPUs have shown that a parallel architecture is better suited in performance than traditional single CPUs. In 2010, a GPU-based simulator was introduced for a family of P systems with active membranes solving SAT in linear time. This is the starting point of this paper, which presents a new GPU simulator for another polynomial-time solution to SAT by means of tissue P systems with cell division, trading space for time. The aim of this simulator is to further study which ingredients of different P systems models are well suited to be managed by the GPU.
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