Modules to teach parallel and distributed computing using MPI for Python']Python and Disco

被引：2
|
作者：
Ortiz-Ubarri, Jose [1 ]
Arce-Nazario, Rafael [1 ]
Orozco, Edusmildo [1 ]
机构：
[1] Univ Puerto Rico, Dept Comp Sci, Rio Piedras, PR 00931 USA
来源：
2016 IEEE 30TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW) | 2016年
关键词：
parallel computing; mpi; mapreduce; master worker;
D O I：
10.1109/IPDPSW.2016.204
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The ability to design effective solutions using parallel processing should be a required competency for every computing student. However, teaching parallel concepts is sometimes challenging and costly, specially at early stages of a computer science degree. For such reasons we present a set of modules to teach parallel computing paradigms using as examples problems that are computationally intensive, but easy to understand and can be easily implemented using the Python parallelization libraries MPI for Python and Disco.
引用
收藏
页码：958 / 962
页数：5
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