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Teaching Distributed Computing with WorkQueue (Abstract Only)

Published: 08 March 2017 Publication History

Abstract

With the recent emphasis on Parallel and Distributed Computing topics in the Computer Science Curricula 2013, instructors are increasingly incorporating these topics into their undergraduate courses. Unfortunately, many universities lack the dedicated computing resources to provide hands-on experiences in this area. This workshop guides attendees through the open source WorkQueue software to teach parallel and distributed computing principles to undergraduate students. WorkQueue is a distributed master worker framework developed by the Cooperative Computing Lab at the University of Notre Dame. WorkQueue is well-suited for inclusion in undergraduate courses due to the ease of use and deployment on a wide range of computer systems, low administrative overhead, and scalability. WorkQueue can be deployed on any system, from a small Raspberry Pi cluster to a high-performance grid computing environment. This workshop walks attendees through the use of WorkQueue with three demonstrations: a "live demo" such as would be used to engage students in the classroom with a hands-on introduction to distributed computing principles, and a guided "tour" through two lab assignments. The first lab assignment will give attendees a hands-on example of a simple distributed computing problem from implementation to deployment. The second lab will demonstrate WorkQueue MapReduce, a simple framework that can be used to introduce the MapReduce programming model without the overhead of a Hadoop cluster or equivalent. A laptop is required to participate in the workshop; the presenters will provide a pre-configured Linux VirtualBox virtual machine to facilitate software setup, or attendees can use their own Linux installations.

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cover image ACM Conferences
SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
March 2017
838 pages
ISBN:9781450346986
DOI:10.1145/3017680
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 March 2017

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Author Tags

  1. MapReduce
  2. WorkQueue
  3. distributed computing
  4. parallel computing

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SIGCSE '17
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SIGCSE '17 Paper Acceptance Rate 105 of 348 submissions, 30%;
Overall Acceptance Rate 1,787 of 5,146 submissions, 35%

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