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Unifying computing resources and access interface to support parallel and distributed computing education
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DOI：10.1016/j.jpdc.2018.02.020.png)
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Abstract
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This article presents how various on-site and remote computing resources are combined into a framework to support teaching parallel and distributed computing (PDC) at the undergraduate level. The combination of these resources enables the delivery of PDC programming, system, and architectural concepts via a browser-based common interface (JupyterHub) and a single programming environment (Python and its supported libraries). This also allows lecturers and students to focus more on the principles of PDC and less on the technicalities of native languages for different platforms. We describe how this framework can support a comprehensive set of PDC course modules, including lectures, assignments, and projects, for a full semester junior-level class. Adoption of this framework in various teaching environments at Clemson University has received positive feedback from both instructors and participants. Published by Elsevier Inc.
Keywords:
Computing resources
MPI
MapReduce
Spark
Python
Distributed systems
Parallel computing education
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