Implementation of Membrane Algorithms on GPU
Author(s) -
Xingyi Zhang,
Bangju Wang,
Zhuanlian Ding,
Jin Tang,
Juanjuan He
Publication year - 2014
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2014/307617
Subject(s) - computer science , membrane computing , graphics processing unit , central processing unit , parallel computing , set (abstract data type) , algorithm , general purpose computing on graphics processing units , parallelism (grammar) , class (philosophy) , graphics , matching (statistics) , artificial intelligence , computer hardware , mathematics , statistics , computer graphics (images) , programming language
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
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