A vector-parallel FFT with a user-specifiable data distribution scheme
We propose a 1-dimensional FFT routine for distributed-memory vector-parallel machines which provides the user with both high performance and flexibility in data distribution. Our routine inputs/outputs data using block cyclic data distribution, and the block sizes for input and output can be specif...
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creator | Yamamoto, Yusaku Igai, Mitsuyoshi Naono, Ken |
description | We propose a 1-dimensional FFT routine for distributed-memory vector-parallel machines which provides the user with both high performance and flexibility in data distribution. Our routine inputs/outputs data using block cyclic data distribution, and the block sizes for input and output can be specified independently by the user. This flexibility is realized with the same amount of inter-processor communication as the widely used transpose algorithm and no additional overhead for data redistribution is necessary. We implemented our method on the Hitachi SR2201, a distributed-memory parallel machine with pseudovector processing nodes, and obtained 45% of the peak performance on 16 nodes when the problem size is N = 224. This performance was unchanged for a wide range of block sizes from 1 to 16. |
doi_str_mv | 10.5555/1761566.1761613 |
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Our routine inputs/outputs data using block cyclic data distribution, and the block sizes for input and output can be specified independently by the user. This flexibility is realized with the same amount of inter-processor communication as the widely used transpose algorithm and no additional overhead for data redistribution is necessary. We implemented our method on the Hitachi SR2201, a distributed-memory parallel machine with pseudovector processing nodes, and obtained 45% of the peak performance on 16 nodes when the problem size is N = 224. 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Our routine inputs/outputs data using block cyclic data distribution, and the block sizes for input and output can be specified independently by the user. This flexibility is realized with the same amount of inter-processor communication as the widely used transpose algorithm and no additional overhead for data redistribution is necessary. We implemented our method on the Hitachi SR2201, a distributed-memory parallel machine with pseudovector processing nodes, and obtained 45% of the peak performance on 16 nodes when the problem size is N = 224. This performance was unchanged for a wide range of block sizes from 1 to 16.</description><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. 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User interface</topic><topic>Exact sciences and technology</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yamamoto, Yusaku</creatorcontrib><creatorcontrib>Igai, Mitsuyoshi</creatorcontrib><creatorcontrib>Naono, Ken</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yamamoto, Yusaku</au><au>Igai, Mitsuyoshi</au><au>Naono, Ken</au><au>Yang, Laurence Tianruo</au><au>Guo, Minyi</au><au>Guo, Minyi</au><au>Yang, Laurence Tianruo</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A vector-parallel FFT with a user-specifiable data distribution scheme</atitle><btitle>Lecture notes in computer science</btitle><date>2003-01-01</date><risdate>2003</risdate><volume>2745</volume><spage>362</spage><epage>374</epage><pages>362-374</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540405232</isbn><isbn>9783540405238</isbn><eisbn>3540376194</eisbn><eisbn>9783540376194</eisbn><abstract>We propose a 1-dimensional FFT routine for distributed-memory vector-parallel machines which provides the user with both high performance and flexibility in data distribution. Our routine inputs/outputs data using block cyclic data distribution, and the block sizes for input and output can be specified independently by the user. This flexibility is realized with the same amount of inter-processor communication as the widely used transpose algorithm and no additional overhead for data redistribution is necessary. We implemented our method on the Hitachi SR2201, a distributed-memory parallel machine with pseudovector processing nodes, and obtained 45% of the peak performance on 16 nodes when the problem size is N = 224. This performance was unchanged for a wide range of block sizes from 1 to 16.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.5555/1761566.1761613</doi><oclcid>935290877</oclcid><tpages>13</tpages></addata></record> |
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subjects | Applied sciences Computer science control theory systems Computer systems and distributed systems. User interface Exact sciences and technology Software |
title | A vector-parallel FFT with a user-specifiable data distribution scheme |
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