Master–Worker Paradigm on the TILE64 Many-core Platform
博士 === 國立清華大學 === 資訊工程學系 === 101 === Advances at an unprecedented rate in computer hardware and networking technologies have made the many-core computing affordable and readily available in a matter of few years. Nonetheless, it incurs challenges to pro-grammers to build scalable and high performanc...
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ndltd-TW-101NTHU53920962015-10-13T22:29:58Z http://ndltd.ncl.edu.tw/handle/94728055798710355530 Master–Worker Paradigm on the TILE64 Many-core Platform TILE64多核平台上之主從式架構 Lin, Xuan-Yi 林軒毅 博士 國立清華大學 資訊工程學系 101 Advances at an unprecedented rate in computer hardware and networking technologies have made the many-core computing affordable and readily available in a matter of few years. Nonetheless, it incurs challenges to pro-grammers to build scalable and high performance parallel software. Optimi-zations of parallel programs for a many-core platform are viewed as a multi-faceted problem, where system and architectural factors should be taken into account. In this dissertation, we tackle this problem by modeling and evalu-ating parallel application behavior on the TILE64 many-core platform. We choose both stream processing application and MapReduce as target applica-tions and master–worker model as a parallelization paradigm. We model the parallel execution of master–worker applications on the TILE64 many-core platform. We model nine different communication schemes for a master–worker system. We also propose performance modeling for the nine commu-nication schemes. We run program implementations to compare and verify theoretical and experimental results. The results show that the proposed model is capable of guiding software developers in choosing proper imple-mentation methodology for master–worker processing on the TILE64 many-core platform. Chung, Yeh-Ching 鍾葉青 2013 學位論文 ; thesis 101 en_US |
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博士 === 國立清華大學 === 資訊工程學系 === 101 === Advances at an unprecedented rate in computer hardware and networking technologies have made the many-core computing affordable and readily available in a matter of few years. Nonetheless, it incurs challenges to pro-grammers to build scalable and high performance parallel software. Optimi-zations of parallel programs for a many-core platform are viewed as a multi-faceted problem, where system and architectural factors should be taken into account. In this dissertation, we tackle this problem by modeling and evalu-ating parallel application behavior on the TILE64 many-core platform. We choose both stream processing application and MapReduce as target applica-tions and master–worker model as a parallelization paradigm. We model the parallel execution of master–worker applications on the TILE64 many-core platform. We model nine different communication schemes for a master–worker system. We also propose performance modeling for the nine commu-nication schemes. We run program implementations to compare and verify theoretical and experimental results. The results show that the proposed model is capable of guiding software developers in choosing proper imple-mentation methodology for master–worker processing on the TILE64 many-core platform.
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author2 |
Chung, Yeh-Ching |
author_facet |
Chung, Yeh-Ching Lin, Xuan-Yi 林軒毅 |
author |
Lin, Xuan-Yi 林軒毅 |
spellingShingle |
Lin, Xuan-Yi 林軒毅 Master–Worker Paradigm on the TILE64 Many-core Platform |
author_sort |
Lin, Xuan-Yi |
title |
Master–Worker Paradigm on the TILE64 Many-core Platform |
title_short |
Master–Worker Paradigm on the TILE64 Many-core Platform |
title_full |
Master–Worker Paradigm on the TILE64 Many-core Platform |
title_fullStr |
Master–Worker Paradigm on the TILE64 Many-core Platform |
title_full_unstemmed |
Master–Worker Paradigm on the TILE64 Many-core Platform |
title_sort |
master–worker paradigm on the tile64 many-core platform |
publishDate |
2013 |
url |
http://ndltd.ncl.edu.tw/handle/94728055798710355530 |
work_keys_str_mv |
AT linxuanyi masterworkerparadigmonthetile64manycoreplatform AT línxuānyì masterworkerparadigmonthetile64manycoreplatform AT linxuanyi tile64duōhépíngtáishàngzhīzhǔcóngshìjiàgòu AT línxuānyì tile64duōhépíngtáishàngzhīzhǔcóngshìjiàgòu |
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1718077402154795008 |