Using Phoenix++ MapReduce to introduce undergraduate students to parallel computing
Using Phoenix++ MapReduce to introduce undergraduate students to parallel computing
复制标题
使用 Phoenix MapReduce 向本科生介绍并行计算
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Suzanne J. Matthews
中科院分区：
文献类型：
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作者：
Suzanne J. Matthews
随着CS2013的发布，全国各地的院系都在为核心计算机科学课程注入更多的并行性。MapReduce是向本科生介绍并行性的一个有吸引力的选择。然而，大多数教授MapReduce的方法都要求学生访问Hadoop集群。在许多机构中，这通常是一个可行的选择，特别是如果MapReduce在课程中代表一个次要主题。在本文中，我们将讨论如何使用Phoenix++ MapReduce向本科生介绍并行计算和MapReduce范式。我们在Phoenix++上发布了一个开源模块，使其他机构的教师能够快速采用Phoenix++ MapReduce用于他们自己的课程。
With the release of CS2013, departments around the country are injecting more parallelism into their core computer science courses. MapReduce is an attractive option for introducing undergraduate students to parallelism. However, most approaches to teaching MapReduce require students to access a Hadoop cluster. This is often too costly to be a viable option at many institutions, especially if MapReduce represents a minor topic in a course. In this paper, we discuss the use of Phoenix++ MapReduce for introducing undergraduate students to parallel computing and the MapReduce paradigm. We publish an open-source module on Phoenix++, enabling instructors at other institutions to rapidly adopt Phoenix++ MapReduce for use in their own curricula.