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Budget Beowulfs: A Showcase of Inexpensive Clusters for Teaching PDC

Published:24 February 2015Publication History

ABSTRACT

In response to the shift to multicore processors, the ACM-IEEE CS2013 curriculum recommendations [1] include parallel and distributed computing (PDC) as a new core knowledge area. Some of the key concepts in PDC are the distinctions between shared-memory, distributed-memory, and heterogeneous system architectures.

Most CS educators would agree that providing students with hands-on experience improves their students' learning. Given the ubiquity of multicore processors, it is quite easy to give today's students hands-on experience developing software on shared-memory architectures. By contrast, providing students with hands-on experience developing software for distributed architectures has typically required access to a Beowulf cluster, the price of which was beyond the reach of many institutions. However, hardware manufacturers have recently begun producing a variety of inexpensive --system on a board multiprocessors. Creative CS educators are using these multiprocessors to design and build inexpensive Beowulf clusters, and using them to provide students with hands-on experience with shared-memory, distributed-memory, and heterogeneous computing paradigms.

In this special session, several PDC educators will bring, present, and demonstrate their innovative Beowulf clusters; each designed and built using a different inexpensive multiprocessor board.

References

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  1. Budget Beowulfs: A Showcase of Inexpensive Clusters for Teaching PDC

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      • Published in

        cover image ACM Conferences
        SIGCSE '15: Proceedings of the 46th ACM Technical Symposium on Computer Science Education
        February 2015
        766 pages
        ISBN:9781450329668
        DOI:10.1145/2676723

        Copyright © 2015 Owner/Author

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 February 2015

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        SIGCSE '15 Paper Acceptance Rate105of289submissions,36%Overall Acceptance Rate1,595of4,542submissions,35%

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