完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.author | Ho, Yu-Fan Jr | |
| dc.contributor.author | Chen, Sih-Wei Jr | |
| dc.contributor.author | Chen, Chang-Yi Jr | |
| dc.contributor.author | Hsu, Yung-Ching Jr | |
| dc.contributor.author | Liu, Pangfeng Jr | |
| dc.date.accessioned | 2011-02-18T03:26:13Z | |
| dc.date.accessioned | 2020-05-18T03:10:43Z | - |
| dc.date.available | 2011-02-18T03:26:13Z | |
| dc.date.available | 2020-05-18T03:10:43Z | - |
| dc.date.issued | 2011-02-18T03:26:13Z | |
| dc.date.submitted | 2010-12-18 | |
| dc.identifier.uri | http://dspace.lib.fcu.edu.tw/handle/2377/29997 | - |
| dc.description.abstract | MapReduce is a very popular parallel programming model for processing large data sets. This paper discusses strategies in implementing a MapReduce runtime system using Message Passing Interface (MPI) library. The implementation uses blocking communication function in MPI, e.g. MPI Send and MPI Recv, to transfer intermediate data, so as to make the communication between mappers and reducers in MapReduce model much more efficient. Experiment results indicate that our MPI implementation performs better than Hadoop when the data volume is below 60MB, and perform five times better then native Hadoop when the input size is below 5MB. | |
| dc.description.sponsorship | National Cheng Kung University,Tainan | |
| dc.format.extent | 6p. | |
| dc.relation.ispartofseries | 2010 ICS會議 | |
| dc.subject | MapReduce | |
| dc.subject | MPI | |
| dc.subject.other | Peer to Peer, Grid, and Cloud Computing | |
| dc.title | A Mapreduce Programming Framework Using Message Passing | |
| 分類: | 2010年 ICS 國際計算機會議(如需查看全文，請連結至IEEE Xplore網站) | |
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