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A Glance at High Performance Computing (HPC)

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Introduction to HPC with MPI for Data Science

Part of the book series: Undergraduate Topics in Computer Science ((UTICS))

Abstract

High Performance Computing, or HPC for short, is an area encompassing among others the various paradigms of parallel programming, their related programming languages and application programming interfaces (APIs), the dedicated software tools, the international specialized conferences (ACM/IEEE Super-Computing, or SC for short), etc. Loosely speaking, HPC is both the scientific and technical fields of study of “Super-Computers” (SCs).

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Notes

  1. 1.

    http://www.top500.org/.

  2. 2.

    http://www.green500.org/.

  3. 3.

    http://www.seti.org/.

  4. 4.

    http://hadoop.apache.org/.

  5. 5.

    http://fr.wikipedia.org/wiki/Streaming_SIMD_Extensions.

  6. 6.

    See the -O option argument of g++. Other options are listed using g++ –help.

  7. 7.

    http://openmp.org/.

  8. 8.

    For sake of simplicity, we assume that each process runs on a distinct processor that is a node of the distributed-memory parallel machine.

  9. 9.

    A free graphing utility that can be downloaded from http://www.gnuplot.info/.

  10. 10.

    Indeed, we are not interested in running a program on a data-set that may take 100 years to complete.

  11. 11.

    Available since MPI-2.

  12. 12.

    http://lustre.opensfs.org/.

  13. 13.

    http://www-03.ibm.com/systems/platformcomputing/products/gpfs/.

  14. 14.

    http://www.swift.com/about_swift/company_information/swift_history.

References

  1. Amdahl, G.M.: Validity of the single processor approach to achieving large scale computing capabilities. In: Proceedings of Spring Joint Computer Conference, AFIPS ’67 (Spring), pp. 483–485. ACM, New York (1967)

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  3. Hill, M.D., Marty, M.R.: Amdahl’s law in the multicore era. Computer 41(7), 33–38 (2008)

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  4. Woo, D.H., Lee, H.-H.S.: Extending Amdahl’s law for energy-efficient computing in the many-core era. Computer 41(12), 24–31 (2008)

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  5. Hwang, K.: Advanced Computer Architecture: Parallelism, Scalability, Programmability, 1st edn. McGraw-Hill Higher Education, New York (1992)

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  6. Rotem-Gal-Oz, A.: Fallacies of distributed computing explained (2006), (initially discussed by James Gosling and Peter L. Deutsch). See http://www.rgoarchitects.com/Files/fallacies.pdf

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Authors and Affiliations

  1. École Polytechnique, Palaiseau, France

    Frank Nielsen

  2. Sony Computer Science Laboratories, Inc., Tokyo, Japan

    Frank Nielsen

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  1. Frank Nielsen
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Correspondence to Frank Nielsen .

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© 2016 Springer International Publishing Switzerland

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Nielsen, F. (2016). A Glance at High Performance Computing (HPC). In: Introduction to HPC with MPI for Data Science. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-21903-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-21903-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21902-8

  • Online ISBN: 978-3-319-21903-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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