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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 307617, 7 pages
Research Article

Implementation of Membrane Algorithms on GPU

1Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, China
2Key Laboratory of Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Received 7 May 2014; Accepted 25 June 2014; Published 10 July 2014

Academic Editor: Quanke Pan

Copyright © 2014 Xingyi Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Membrane algorithms are a new class of parallel algorithms, which attempt to incorporate some components of membrane computing models for designing efficient optimization algorithms, such as the structure of the models and the way of communication between cells. Although the importance of the parallelism of such algorithms has been well recognized, membrane algorithms were usually implemented on the serial computing device central processing unit (CPU), which makes the algorithms unable to work in an efficient way. In this work, we consider the implementation of membrane algorithms on the parallel computing device graphics processing unit (GPU). In such implementation, all cells of membrane algorithms can work simultaneously. Experimental results on two classical intractable problems, the point set matching problem and TSP, show that the GPU implementation of membrane algorithms is much more efficient than CPU implementation in terms of runtime, especially for solving problems with a high complexity.