Intel Itanium 2 4路多处理器系统并行内部点求解器的构建与性能表征

P. Koka, T. Suh, M. Smelyanskiy, R. Grzeszczuk, C. Dulong
{"title":"Intel Itanium 2 4路多处理器系统并行内部点求解器的构建与性能表征","authors":"P. Koka, T. Suh, M. Smelyanskiy, R. Grzeszczuk, C. Dulong","doi":"10.1109/WWC.2004.1437402","DOIUrl":null,"url":null,"abstract":"In recent years the interior point method (IPM) has became a dominant choice for solving large convex optimization problems for many scientific, engineering and commercial applications. Two reasons for the success of the IPM are its good scalability on existing multiprocessor systems with a small number of processors and its potential to deliver a scalable performance on systems with a large number of processors. The scalability of a parallel IPM is determined by several key issues such as exploiting parallelism due to sparsity of the problem, reducing communication overhead and proper load balancing. In this paper we present an implementation of a parallel linear programming IPM workload and characterize its scalability on a 4-way Itanium/spl reg/ 2 system. We show a speedup of up to 3-times for some of the datasets. We also present a detailed micro-architectural analysis of the workload using VTune/spl trade/ performance analyzer. Our results suggest that a good IPM implementation is latency-bound. Based on these findings, we make suggestions on how to improve the performance of the IPM workload in the future.","PeriodicalId":240633,"journal":{"name":"IEEE International Workshop on Workload Characterization, 2004. WWC-7. 2004","volume":"11 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Construction and performance characterization of parallel interior point solver on 4-way Intel Itanium 2 multiprocessor system\",\"authors\":\"P. Koka, T. Suh, M. Smelyanskiy, R. Grzeszczuk, C. Dulong\",\"doi\":\"10.1109/WWC.2004.1437402\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years the interior point method (IPM) has became a dominant choice for solving large convex optimization problems for many scientific, engineering and commercial applications. Two reasons for the success of the IPM are its good scalability on existing multiprocessor systems with a small number of processors and its potential to deliver a scalable performance on systems with a large number of processors. The scalability of a parallel IPM is determined by several key issues such as exploiting parallelism due to sparsity of the problem, reducing communication overhead and proper load balancing. In this paper we present an implementation of a parallel linear programming IPM workload and characterize its scalability on a 4-way Itanium/spl reg/ 2 system. We show a speedup of up to 3-times for some of the datasets. We also present a detailed micro-architectural analysis of the workload using VTune/spl trade/ performance analyzer. Our results suggest that a good IPM implementation is latency-bound. Based on these findings, we make suggestions on how to improve the performance of the IPM workload in the future.\",\"PeriodicalId\":240633,\"journal\":{\"name\":\"IEEE International Workshop on Workload Characterization, 2004. WWC-7. 2004\",\"volume\":\"11 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Workshop on Workload Characterization, 2004. WWC-7. 2004\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WWC.2004.1437402\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Workshop on Workload Characterization, 2004. WWC-7. 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WWC.2004.1437402","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

近年来,内点法(IPM)已成为许多科学、工程和商业应用中求解大型凸优化问题的主要选择。IPM成功的两个原因是,它在现有的具有少量处理器的多处理器系统上具有良好的可伸缩性,并且具有在具有大量处理器的系统上提供可伸缩性能的潜力。并行IPM的可伸缩性由几个关键问题决定,例如由于问题的稀疏性而利用并行性、减少通信开销和适当的负载平衡。本文提出了一种并行线性规划IPM工作负载的实现方法,并对其在4路Itanium/spl reg/ 2系统上的可扩展性进行了表征。对于某些数据集,我们显示了高达3倍的加速。我们还使用VTune/spl交易/性能分析器对工作负载进行了详细的微架构分析。我们的结果表明,一个好的IPM实现是受延迟限制的。基于这些发现,我们对未来如何提高IPM工作负载的性能提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction and performance characterization of parallel interior point solver on 4-way Intel Itanium 2 multiprocessor system
In recent years the interior point method (IPM) has became a dominant choice for solving large convex optimization problems for many scientific, engineering and commercial applications. Two reasons for the success of the IPM are its good scalability on existing multiprocessor systems with a small number of processors and its potential to deliver a scalable performance on systems with a large number of processors. The scalability of a parallel IPM is determined by several key issues such as exploiting parallelism due to sparsity of the problem, reducing communication overhead and proper load balancing. In this paper we present an implementation of a parallel linear programming IPM workload and characterize its scalability on a 4-way Itanium/spl reg/ 2 system. We show a speedup of up to 3-times for some of the datasets. We also present a detailed micro-architectural analysis of the workload using VTune/spl trade/ performance analyzer. Our results suggest that a good IPM implementation is latency-bound. Based on these findings, we make suggestions on how to improve the performance of the IPM workload in the future.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信