Cirrus 超级计算机上的矩阵乘法算法性能分析

Temitayo Adefemi
{"title":"Cirrus 超级计算机上的矩阵乘法算法性能分析","authors":"Temitayo Adefemi","doi":"arxiv-2408.15384","DOIUrl":null,"url":null,"abstract":"Matrix multiplication is integral to various scientific and engineering\ndisciplines, including machine learning, image processing, and gaming. With the\nincreasing data volumes in areas like machine learning, the demand for\nefficient parallel processing of large matrices has grown significantly.This\nstudy explores the performance of both serial and parallel matrix\nmultiplication on the Cirrus supercomputer at the University of Edinburgh. The\nresults demonstrate the scalability and efficiency of these methods, providing\ninsights for optimizing matrixmultiplication in real-world applications.","PeriodicalId":501422,"journal":{"name":"arXiv - CS - Distributed, Parallel, and Cluster Computing","volume":"11 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of the Performance of the Matrix Multiplication Algorithm on the Cirrus Supercomputer\",\"authors\":\"Temitayo Adefemi\",\"doi\":\"arxiv-2408.15384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Matrix multiplication is integral to various scientific and engineering\\ndisciplines, including machine learning, image processing, and gaming. With the\\nincreasing data volumes in areas like machine learning, the demand for\\nefficient parallel processing of large matrices has grown significantly.This\\nstudy explores the performance of both serial and parallel matrix\\nmultiplication on the Cirrus supercomputer at the University of Edinburgh. The\\nresults demonstrate the scalability and efficiency of these methods, providing\\ninsights for optimizing matrixmultiplication in real-world applications.\",\"PeriodicalId\":501422,\"journal\":{\"name\":\"arXiv - CS - Distributed, Parallel, and Cluster Computing\",\"volume\":\"11 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Distributed, Parallel, and Cluster Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.15384\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Distributed, Parallel, and Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.15384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

矩阵乘法是机器学习、图像处理和游戏等各种科学和工程学科不可或缺的一部分。本研究探讨了爱丁堡大学 Cirrus 超级计算机上串行和并行矩阵乘法的性能。研究结果证明了这些方法的可扩展性和效率,为优化实际应用中的矩阵乘法提供了启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analysis of the Performance of the Matrix Multiplication Algorithm on the Cirrus Supercomputer
Matrix multiplication is integral to various scientific and engineering disciplines, including machine learning, image processing, and gaming. With the increasing data volumes in areas like machine learning, the demand for efficient parallel processing of large matrices has grown significantly.This study explores the performance of both serial and parallel matrix multiplication on the Cirrus supercomputer at the University of Edinburgh. The results demonstrate the scalability and efficiency of these methods, providing insights for optimizing matrixmultiplication in real-world applications.
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
期刊最新文献
Massively parallel CMA-ES with increasing population Communication Lower Bounds and Optimal Algorithms for Symmetric Matrix Computations Energy Efficiency Support for Software Defined Networks: a Serverless Computing Approach CountChain: A Decentralized Oracle Network for Counting Systems Delay Analysis of EIP-4844
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1