Implementation of Membrane Algorithms on GPU
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 parall...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/307617 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832550319640281088 |
|---|---|
| author | Xingyi Zhang Bangju Wang Zhuanlian Ding Jin Tang Juanjuan He |
| author_facet | Xingyi Zhang Bangju Wang Zhuanlian Ding Jin Tang Juanjuan He |
| author_sort | Xingyi Zhang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-fb5973685b5f449cb2af9be92f89876e |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-fb5973685b5f449cb2af9be92f89876e2025-02-03T06:07:07ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/307617307617Implementation of Membrane Algorithms on GPUXingyi Zhang0Bangju Wang1Zhuanlian Ding2Jin Tang3Juanjuan He4Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, ChinaKey Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, ChinaKey Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, ChinaKey Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, ChinaKey Laboratory of Image Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, ChinaMembrane 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.http://dx.doi.org/10.1155/2014/307617 |
| spellingShingle | Xingyi Zhang Bangju Wang Zhuanlian Ding Jin Tang Juanjuan He Implementation of Membrane Algorithms on GPU Journal of Applied Mathematics |
| title | Implementation of Membrane Algorithms on GPU |
| title_full | Implementation of Membrane Algorithms on GPU |
| title_fullStr | Implementation of Membrane Algorithms on GPU |
| title_full_unstemmed | Implementation of Membrane Algorithms on GPU |
| title_short | Implementation of Membrane Algorithms on GPU |
| title_sort | implementation of membrane algorithms on gpu |
| url | http://dx.doi.org/10.1155/2014/307617 |
| work_keys_str_mv | AT xingyizhang implementationofmembranealgorithmsongpu AT bangjuwang implementationofmembranealgorithmsongpu AT zhuanlianding implementationofmembranealgorithmsongpu AT jintang implementationofmembranealgorithmsongpu AT juanjuanhe implementationofmembranealgorithmsongpu |