Abstract

Abstract Membrane computing is a theoretical model of computation that inspired from the structure and functioning of cells. Membrane computing models naturally have parallel structure. Most of the simulations of membrane computing have been done in a serial way on a machine with a central processing unit (CPU). This has neglected the advantage of parallelism in membrane computing. This paper uses Graphic Processing Unit (GPU) as a parallel tool to implement membrane computing. The method minimizes data transferring which is time consuming procedure between the device and the host by processing all computing on GPU and transfer only the final results to CPU. Simulations show that speed increases up to 15 times compared to sequential simulation and using of shared memory increases speed, up to 38 times.

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