Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip
Compared to 2D NoC, 3D NoC has better integrated density and system performance, which was a reliable method to solve the problem about low-power mapping. On the basis of the traditional particle swarm optimization algo-rithm (PSOA), a dynamic adaptive discrete particle swarm optimization algorithm...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2016-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016215/ |
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| _version_ | 1841539592810921984 |
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| author | Qin-rang LIU Qi-hua DAI Jian-liang SHEN Bo ZHAO |
| author_facet | Qin-rang LIU Qi-hua DAI Jian-liang SHEN Bo ZHAO |
| author_sort | Qin-rang LIU |
| collection | DOAJ |
| description | Compared to 2D NoC, 3D NoC has better integrated density and system performance, which was a reliable method to solve the problem about low-power mapping. On the basis of the traditional particle swarm optimization algo-rithm (PSOA), a dynamic adaptive discrete particle swarm optimization algorithm (DADPSOA) was proposed . Parame-ter in this algorithm was adjusted dynamically based on the degree of early convergence and the charge of individual adap-tive value to approach the optimal solution. At the same time, the reasonable structure of the particles was made aiming at reducing the time complexity of this algorithm. Experimental results show that comparing with the random mapping, genetic algorithm (GA), PSOA and dynamic ant colony algorithm (DACA), DADPSOA can save the execution time, reduce the communication power consumption of mapping results. The power consumption of the task graph is reduced. |
| format | Article |
| id | doaj-art-8b2c848d726c4f05bc0796c1bea4d9ab |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2016-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-8b2c848d726c4f05bc0796c1bea4d9ab2025-01-14T06:56:16ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-11-0137233059704398Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chipQin-rang LIUQi-hua DAIJian-liang SHENBo ZHAOCompared to 2D NoC, 3D NoC has better integrated density and system performance, which was a reliable method to solve the problem about low-power mapping. On the basis of the traditional particle swarm optimization algo-rithm (PSOA), a dynamic adaptive discrete particle swarm optimization algorithm (DADPSOA) was proposed . Parame-ter in this algorithm was adjusted dynamically based on the degree of early convergence and the charge of individual adap-tive value to approach the optimal solution. At the same time, the reasonable structure of the particles was made aiming at reducing the time complexity of this algorithm. Experimental results show that comparing with the random mapping, genetic algorithm (GA), PSOA and dynamic ant colony algorithm (DACA), DADPSOA can save the execution time, reduce the communication power consumption of mapping results. The power consumption of the task graph is reduced.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016215/3D NoClow-power mappingdeconstructionadaptive discrete particle swarm optimization algorithm |
| spellingShingle | Qin-rang LIU Qi-hua DAI Jian-liang SHEN Bo ZHAO Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip Tongxin xuebao 3D NoC low-power mapping deconstruction adaptive discrete particle swarm optimization algorithm |
| title | Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip |
| title_full | Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip |
| title_fullStr | Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip |
| title_full_unstemmed | Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip |
| title_short | Dynamic adaptive discrete particle swarm optimization algorithm based method on low-power mapping in network-on-chip |
| title_sort | dynamic adaptive discrete particle swarm optimization algorithm based method on low power mapping in network on chip |
| topic | 3D NoC low-power mapping deconstruction adaptive discrete particle swarm optimization algorithm |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016215/ |
| work_keys_str_mv | AT qinrangliu dynamicadaptivediscreteparticleswarmoptimizationalgorithmbasedmethodonlowpowermappinginnetworkonchip AT qihuadai dynamicadaptivediscreteparticleswarmoptimizationalgorithmbasedmethodonlowpowermappinginnetworkonchip AT jianliangshen dynamicadaptivediscreteparticleswarmoptimizationalgorithmbasedmethodonlowpowermappinginnetworkonchip AT bozhao dynamicadaptivediscreteparticleswarmoptimizationalgorithmbasedmethodonlowpowermappinginnetworkonchip |