Parallel Matrix Multiplication for Business Applications

被引:0
|
作者
Qasem, Mais Haj [1 ]
Qatawneh, Mohammad [1 ]
机构
[1] Univ Jordan, Comp Sci Dept, Amman, Jordan
来源
APPLIED COMPUTATIONAL INTELLIGENCE AND MATHEMATICAL METHODS: COMPUTATIONAL METHODS IN SYSTEMS AND SOFTWARE 2017, VOL. 2 | 2018年 / 662卷
关键词
Business application; Hadoop; MPI; MapReduce; Matrix multiplication; MAPREDUCE;
D O I
10.1007/978-3-319-67621-0_3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Business applications, such as market shops, use matrix multiplication to calculate yearly, monthly, or even daily profits based on price and quantity matrices. Matrices comprise large data in computer applications and other fields, which make the efficiency of matrix multiplication a popular research topic. Although the task of computing matrix products is a central operation in many numerical algorithms, it is potentially time consuming, making it one of the most well-studied problems in this field. In this paper, Message Passing Interface (MPI), MapReduce, and Multithreaded methods have been implemented to demonstrate their effectiveness in expediting matrix multiplication in a multi-core system. Simulation results show that the efficiency rates of MPI and MapReduce are 90.11% and 47.94%, respectively, with a multi-core processor on the Market Shop application, indicating better performances compared with those of the multithreaded and sequential methods.
引用
收藏
页码:24 / 36
页数:13
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