Hazrina Yusof Hamdani, N. Rashid, M. F. Wajidi, A. Abdulrazzaq, Rana M. Ghadban
{"title":"基于OpenMP的快速PhyloCon算法","authors":"Hazrina Yusof Hamdani, N. Rashid, M. F. Wajidi, A. Abdulrazzaq, Rana M. Ghadban","doi":"10.1109/ICCTD.2009.198","DOIUrl":null,"url":null,"abstract":"This paper is to study and identify suitable algorithm that use in searching regulatory element where PhyloCon algorithm is one of the algorithms. Since PhyloCon has complexity limitation, the time performance is reduced. Therefore, a parallel technique is identified to improve performance of PhyloCon algorithm. The identified parallel technique is implemented on multicore architecture using OpenMP. This technique use multilevel parallelism which consists of outer parallelism and inner parallelism implemented in Phylocon algorithm. In each level, the data decomposition technique is applied to achieve computational load balancing. The implementation result produced maximum speed up until 2.62 on four processors compared to the sequential PhyloCon results.","PeriodicalId":269403,"journal":{"name":"2009 International Conference on Computer Technology and Development","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fast PhyloCon Algorithm Using OpenMP\",\"authors\":\"Hazrina Yusof Hamdani, N. Rashid, M. F. Wajidi, A. Abdulrazzaq, Rana M. Ghadban\",\"doi\":\"10.1109/ICCTD.2009.198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is to study and identify suitable algorithm that use in searching regulatory element where PhyloCon algorithm is one of the algorithms. Since PhyloCon has complexity limitation, the time performance is reduced. Therefore, a parallel technique is identified to improve performance of PhyloCon algorithm. The identified parallel technique is implemented on multicore architecture using OpenMP. This technique use multilevel parallelism which consists of outer parallelism and inner parallelism implemented in Phylocon algorithm. In each level, the data decomposition technique is applied to achieve computational load balancing. The implementation result produced maximum speed up until 2.62 on four processors compared to the sequential PhyloCon results.\",\"PeriodicalId\":269403,\"journal\":{\"name\":\"2009 International Conference on Computer Technology and Development\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Computer Technology and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCTD.2009.198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Computer Technology and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCTD.2009.198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper is to study and identify suitable algorithm that use in searching regulatory element where PhyloCon algorithm is one of the algorithms. Since PhyloCon has complexity limitation, the time performance is reduced. Therefore, a parallel technique is identified to improve performance of PhyloCon algorithm. The identified parallel technique is implemented on multicore architecture using OpenMP. This technique use multilevel parallelism which consists of outer parallelism and inner parallelism implemented in Phylocon algorithm. In each level, the data decomposition technique is applied to achieve computational load balancing. The implementation result produced maximum speed up until 2.62 on four processors compared to the sequential PhyloCon results.