Performance Evaluation of Matrix Multiplication in Virtual Machine

被引:0
|
作者
Muhammad, Asif [1 ]
Islam, Muhammad Arshad [1 ]
机构
[1] Capital Univ Sci & Technol, Fac Comp, Islamabad, Pakistan
关键词
High Performance Computing; Cache; Memory; Matrix Multiplication;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we have examined various implementations of matrix-matrix multiplication using.NET platform. Matrix multiplication is considered one of the basic operation in the field of linear algebra that is used various computer science algorithms. We have used the all loop reordering of traditional n(3) sequential algorithm to analyze its behavior on the.NET common language run-time over more than 10 varying sizes of matrices. Moreover we have also analyzed the blocking version of the traditional multiplication algorithm to observe the cache behavior. We have used Intel CoreiS Arandale 2.53 GHz and Haswell 3.30 GHz processors with dual channel RAM for our experiments. Our experiments show that KIJ and IKJ reordering have performed better than the rest of the loop reordering. Furthermore, blocking implementation of matrix multiplication have not been able to gain significantly on.NET platform. In future, we will utilize task parallel library included in.NET 4.5 to gauge the performance efficiency of linear algebraic operations.
引用
收藏
页码:205 / 210
页数:6
相关论文
共 50 条
  • [31] Writing a performance-portable matrix multiplication
    Fabeiro, Jorge F.
    Andrade, Diego
    Fraguela, Basilio B.
    PARALLEL COMPUTING, 2016, 52 : 65 - 77
  • [32] Anatomy of high-performance matrix multiplication
    Goto, Kazushige
    Van De Geijn, Robert A.
    ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2008, 34 (03):
  • [33] High Performance Matrix Multiplication on Many Cores
    Yuan, Nan
    Zhou, Yongbin
    Tan, Guangming
    Zhang, Junchao
    Fan, Dongrui
    EURO-PAR 2009: PARALLEL PROCESSING, PROCEEDINGS, 2009, 5704 : 948 - 959
  • [34] Intel vs AMD: Matrix Multiplication Performance
    Anchev, Nenad
    Gusev, Marjan
    Ristov, Sasko
    Atanasovski, Blagoj
    2013 36TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2013, : 182 - 187
  • [35] GPU computing performance analysis on matrix multiplication
    Huang, Zhibin
    Ma, Ning
    Wang, Shaojun
    Peng, Yu
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (23): : 9043 - 9048
  • [36] The virtual coordinate measuring machine (VCMM) in the evaluation of the performance of the act of measuring
    Abackerli, Alvaro J.
    Orrego, Roxana M. Martinez
    Miguel, Paulo A. Cauchick
    Ciencia y Engenharia/ Science and Engineering Journal, 2002, 11 (02): : 1 - 8
  • [37] Simple and practical disk performance evaluation method in virtual machine environments
    Baba, Teruyuki
    Tanaka, Atsuhiro
    PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON PERFORMANCE EVALUATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS, 2008, : 338 - 345
  • [38] Performance evaluation of virtual machine-based Grid workflow system
    Wang, Lizhe
    Kunze, Marcel
    Tao, Jie
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2008, 20 (15): : 1759 - 1771
  • [39] FlexCloud: A Flexible and Extensible Simulator for Performance Evaluation of Virtual Machine Allocation
    Xu, Minxian
    Li, Guozhong
    Yang, Wutong
    Tian, Wenhong
    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY), 2015, : 649 - 655
  • [40] A Machine Learning Approach Towards Runtime Optimisation of Matrix Multiplication
    Xia, Yufan
    De La Pierre, Marco
    Barnard, Amanda S.
    Barca, Giuseppe Maria Junior
    2023 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM, IPDPS, 2023, : 524 - 534