{"title":"在多核上实现线性代数基本计算核","authors":"Panagiotis D. Michailidis, K. Margaritis","doi":"10.1109/PCi.2012.23","DOIUrl":null,"url":null,"abstract":"This paper implements basic computational kernels of the scientific computing such as matrix - vector product, matrix product and Gaussian elimination on multi-core platforms using several parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and Fast Flow. The aim of this paper is to present an unified quantitative and qualitative study of these tools for parallel computation of scientific computing kernels on multicore. Finally, based on this study we conclude that the Intel ArBB and SWARM parallel programming tools are the most appropriate because these give good performance and simplicity of programming.","PeriodicalId":131195,"journal":{"name":"2012 16th Panhellenic Conference on Informatics","volume":"258 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Implementing Basic Computational Kernels of Linear Algebra on Multicore\",\"authors\":\"Panagiotis D. Michailidis, K. Margaritis\",\"doi\":\"10.1109/PCi.2012.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper implements basic computational kernels of the scientific computing such as matrix - vector product, matrix product and Gaussian elimination on multi-core platforms using several parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and Fast Flow. The aim of this paper is to present an unified quantitative and qualitative study of these tools for parallel computation of scientific computing kernels on multicore. Finally, based on this study we conclude that the Intel ArBB and SWARM parallel programming tools are the most appropriate because these give good performance and simplicity of programming.\",\"PeriodicalId\":131195,\"journal\":{\"name\":\"2012 16th Panhellenic Conference on Informatics\",\"volume\":\"258 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 16th Panhellenic Conference on Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCi.2012.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 16th Panhellenic Conference on Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCi.2012.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementing Basic Computational Kernels of Linear Algebra on Multicore
This paper implements basic computational kernels of the scientific computing such as matrix - vector product, matrix product and Gaussian elimination on multi-core platforms using several parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and Fast Flow. The aim of this paper is to present an unified quantitative and qualitative study of these tools for parallel computation of scientific computing kernels on multicore. Finally, based on this study we conclude that the Intel ArBB and SWARM parallel programming tools are the most appropriate because these give good performance and simplicity of programming.
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