skip to main content
research-article

Implementing an affordable high-performance computing for teaching-oriented computer science curriculum

Published:07 February 2013Publication History
Skip Abstract Section

Abstract

With the advances in computing power, high-performance computing (HPC) platforms have had an impact on not only scientific research in advanced organizations but also computer science curriculum in the educational community. For example, multicore programming and parallel systems are highly desired courses in the computer science major. However, the high cost of HPC equipment and maintenance makes it hard to be adapted into a conventional computer science curriculum. Specifically, teaching-oriented institutions cannot afford an HPC system due to the high cost, lack of experience, and smaller research infrastructure. The main objective of this article is to present an affordable and easy-to-use high-performance cluster system for teaching-oriented computer science curriculums. In order to address this, we have designed and implemented an affordable high-performance cluster system based on the PlayStation 3 (PS3). For the performance evaluation of the PS3 cluster, we conducted a benchmarking test, that is, matrix multiplication, with different numbers of synergistic processing elements (SPEs) and nodes. As a result, it was concluded that the PS3Cluster provides enough computing power as an HPC for computer science courses, while the total cost is less than 10% of an existing cluster system on the market that has similar performance. In addition, the implemented PS3Cluster system has been used for computer science courses, such as Parallel and Distributed Databases and Parallel Programming.

References

  1. Afsaneh Minaie, R. S.-M. 2009. Incorporating parallel computing in the undergraduate computer science curriculum. In Proceedings of the National ASEE Conference.Google ScholarGoogle Scholar
  2. Agarwal, S., Lim, J., Zelnik-Manor, L., Perona, P., Kriegman, D., and Belongie, S. 2005. Beyond pairwise clustering. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, (CVPR '05). IEEE, Los Alamitos, CA, 838--845. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Arpaci-Dusseau, A. C., Arpaci-Dusseau, R. H., Culler, D. E., Hellerstein, J. M., and Patterson, D. A. 1998. Searching for the sorting record: Experiences in tuning now-sort. In Proceedings of the SIGMETRICS Symposium on Parallel and Distributed Tools (SPDT '98). ACM, New York, 124--133. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Bader, D. A. 2004. Computational biology and high-performance computing. Commun. ACM 47, 11, 34--41. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Baru, C. and Fecteau, G. 1995. An overview of db2 parallel edition. SIGMOD Rec. 24, 2, 460--462. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bjornson, R. D., Sherman, A. H., Weston, S. B., Willard, N., and Wing, J. 2002. Turboblast(r): A parallel implementation of blast built on the turbohub. In Proceedings of the 16th International Parallel and Distributed Processing Symposium (IPDPS '02). IEEE, Los Alamitos, CA, 325. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Blagojevic, F., Curtis-Maury, M., Yeom, J.-S., Schneider, S., and Nikolopoulos, D. 2008a. Scheduling asymmetric parallelism on a PlayStation3 cluster. In Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (CCGRID '08). IEEE, Los Alamitos, CA, 146--153. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Blagojevic, F., Curtis-Maury, M., Yeom, J.-S., Schneider, S., and Nikolopoulos, D. S. 2008b. Scheduling asymmetric parallelism on a playstation3 cluster. In Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid. IEEE, Los Alamitos, CA, 146--153. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. CHPC. 2012. Center for high performance computing at the University of Utah. http://www.chpc.utah.edu/.Google ScholarGoogle Scholar
  10. Cluster, S. P. 2011. Sony PS3 cluster (IBM Cell Be). http://moss.csc.ncsu.edu/mueller/cluster/ps3/.Google ScholarGoogle Scholar
  11. Culler, D. E. 1997. Parallel computing on the Berkeley now. In Proceedings of the 9th Joint Symposium on Parallel Processing (JSPP '97).Google ScholarGoogle Scholar
  12. Diesburg, S., Gray, P., and Joiner, D. 2005. High performance computing environments without the fuss: the Bootable Cluster CD. In Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, 2005. IEEE, Los Alamitos, CA, 8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Fedora. 2011. Eclipse. http://fedoraproject.org/wiki/eclipse.Google ScholarGoogle Scholar
  14. Hacker, T. 2010. Hands-on high performance computing developing a cluster computing course for real world supercomputing. In Proceedings of the National ASEE Conference. 3.Google ScholarGoogle Scholar
  15. Joiner, D. A., Gray, P., Murphy, T., and Peck, C. 2006. Teaching parallel computing to science faculty: Best practices and common pitfalls. In Proceedings of the 11th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP '06). ACM, New York, 239--246. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Kahle, J. A., Day, M. N., Hofstee, H. P., Johns, C. R., Maeurer, T. R., and Shippy, D. 2005. Introduction to the cell multiprocessor. IBM J. Res. Dev. 49, 4/5, 589--604. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Lee, J. and Abuzaghleh, O. 2011. Implementing an affordable high performance computing platform for teaching-oriented computer science curriculum. In Proceedings of the National ASEE Conference.Google ScholarGoogle Scholar
  18. Lillywhite, K., Lee, D.-J., Antani, S., Zhang, D., and Long, R. 2009. Lessons learned in developing a low-cost high performance medical imaging cluster. In Proceedings of the 22nd IEEE International Symposium on Computer-Based Medical Systems, (CBMS '09). IEEE, Los Alamitos, CA, 1--6.Google ScholarGoogle Scholar
  19. Lu, F., Song, J., Cao, X., and Zhu, X. 2012. CPU/GPU computing for long-wave radiation physics on large GPU clusters. Comput. Geosci. 41, 47--55. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. MPI. 2011. Open MPI. http://www.open-mpi.org/.Google ScholarGoogle Scholar
  21. Neill, R., Shabarshin, A., and Carloni, L. P. 2010. A heterogeneous parallel system running open MPI on a broadband network of embedded set-top devices. In Proceedings of the 7th ACM International Conference on Computing Frontiers (CF '10). ACM, New York, 187--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Ngamsuriyaroj, S. and Pornpattana, R. 2010. Performance evaluation of TPC-H queries on mysql cluster. In Proceedings of the 24th IEEE International Conference on Advanced Information Networking and Applications Workshops (WAINA '10). IEEE, Los Alamitos, CA, 1035--1040. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Peck, C. 2010. LittleFe: Parallel and distributed computing education on the move. J. Comput. Sci. Coll. 26, 1, 16--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Perlman, E., Burns, R., Li, Y., and Meneveau, C. 2007. Data exploration of turbulence simulations using a database cluster. In Proceedings of the ACM/IEEE Conference on Supercomputing (SC '07). ACM, New York, 23:1--23:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sites. 2011. Top 500 supercomputer sites. http://www.top500.org/.Google ScholarGoogle Scholar
  26. Sony Computer Entertainment, Inc. 2001. Sony business development. http://www.scei.co.jp/corporate/data/bizdatajpne.html.Google ScholarGoogle Scholar
  27. Sun, N., Kahaner, D., and Chen, D. 2010. High-performance computing in china: Research and applications. Int. J. High Perform. Comput. Appl. 24, 4, 363--409. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Tiwari, A., Chen, C., Chame, J., Hall, M., and Hollingsworth, J. K. 2009. A scalable auto-tuning framework for compiler optimization. In Proceedings of the IEEE International Symposium on Parallel and Distributed Processing (IPDPS '09). IEEE, Los Alamitos, CA, 1--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Weininger, A. 2000. Handling very large databases with informix extended parallel server. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD '00). ACM, New York, 548--549. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Zhang, X., Ding, Y., Huang, Y., and Dong, X. 2010. Design and implementation of a heterogeneous high-performance computing framework using dynamic and partial reconfigurable FPGAs. In Proceedings of the 10th IEEE International Conference on Computer and Information Technology (CIT '10). IEEE, Los Alamitos, CA, 2329--2334. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Implementing an affordable high-performance computing for teaching-oriented computer science curriculum

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    • Published in

      cover image ACM Transactions on Computing Education
      ACM Transactions on Computing Education  Volume 13, Issue 1
      January 2013
      66 pages
      EISSN:1946-6226
      DOI:10.1145/2414446
      Issue’s Table of Contents

      Copyright © 2013 ACM

      Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 February 2013
      • Accepted: 1 October 2012
      • Revised: 1 September 2012
      • Received: 1 December 2011
      Published in toce Volume 13, Issue 1

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader