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dc.contributor.authorKuo, Yu-Lun
dc.contributor.authorYang, Chao-Tung
dc.date.accessioned2009-06-02T08:41:20Z
dc.date.accessioned2020-07-05T06:31:58Z-
dc.date.available2009-06-02T08:41:20Z
dc.date.available2020-07-05T06:31:58Z-
dc.date.issued2006-06-08T06:22:00Z
dc.date.submitted2003-12-18
dc.identifier.urihttp://dspace.fcu.edu.tw/handle/2376/1770-
dc.description.abstractIn addition to the traditional massively parallel computers, distributed workstation clusters now play an important role in scientific computing perhaps due to the advent of commodity high performance processors, low-latency/high-band width networks and powerful development tools. As we know, bioinformatics tools can speed up the analysis of large-scale sequence data, especially about sequence alignment. To fully utilize the relatively inexpensive CPU cycles available to today’s scientists, a PC cluster consists of one master node and seven slave nodes (16 processors totally), is proposed and built for bioinformatics applications. In this paper, we also experiment on Sun Fire 6800 Server and Grid System and compare with the bioinformatics tools performance. We use the mpiBLAST, FASTA and HMMer on parallel computer and Grid System to speed up the process for sequence alignment. The mpiBLAST and FASTA software use a messagepassing library called MPI (Message Passing Interface) and the HMMer software uses a software package called PVM (Parallel Virtual Machine), respectively. The system architecture and performances of these three platforms are also presented in this paper.
dc.description.sponsorship逢甲大學,台中市
dc.format.extent7P.
dc.format.extent317362 bytes
dc.format.mimetypeapplication/pdf
dc.language.isozh_TW
dc.relation.ispartofseries中華民國92年全國計算機會議
dc.subjectParallel computing
dc.subjectSun Fire 6800 SMP
dc.subjectGrid Computing
dc.subjectSpeedup
dc.subjectBioinformatics
dc.subject.other生物資訊
dc.titleApply Bioinformatics Applications on Parallel and Grid Computing Environment
dc.title.alternative應用生物資訊軟體於平行及網格計算環境
分類:2003年 NCS 全國計算機會議

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