XJava: Exploiting Parallelism with Object-Oriented Stream Programming

  • Frank Otto
  • Victor Pankratius
  • Walter F. Tichy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5704)

Abstract

This paper presents the XJava compiler for parallel programs. It exploits parallelism based on an object-oriented stream programming paradigm. XJava extends Java with new parallel constructs that do not expose programmers to low-level details of parallel programming on shared memory machines. Tasks define composable parallel activities, and new operators allow an easier expression of parallel patterns, such as pipelines, divide and conquer, or master/worker. We also present an automatic run-time mechanism that extends our previous work to automatically map tasks and parallel statements to threads.

We conducted several case studies with an open source desktop search application and a suite of benchmark programs. The results show that XJava reduces the opportunities to introduce synchronization errors. Compared to threaded Java, the amount of code could be reduced by up to 39%. The run-time mechanism helped reduce effort for performance tuning and achieved speedups up to 31.5 on an eight core machine.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Boost C++ Libraries, http://www.boost.org/
  2. 2.
    Chamberlain, B.L., Callahan, D., Zima, H.P.: Parallel Programmability and the Chapel Language. Int. J. High Perform. Comput. Appl. 21(3) (August 2007)Google Scholar
  3. 3.
    Charles, P., et al.: X10: an object-oriented approach to non-uniform cluster computing. In: Proc. OOPSLA 2005. ACM Press, New York (2005)Google Scholar
  4. 4.
    Gordon, M.I., Thies, W., Amarasinghe, S.: Exploiting coarse-grained task, data, and pipeline parallelism in stream programs. In: Proc. ASPLOS-XII. ACM Press, New York (2006)Google Scholar
  5. 5.
  6. 6.
    Lea, D.: The java.util.concurrent synchronizer framework. Sci. Comput. Program. 58(3) (2005)Google Scholar
  7. 7.
    Mattson, T.G., Sanders, B.A., Massingill, B.L.: Patterns for parallel programming. Addison-Wesley, Boston (2005)MATHGoogle Scholar
  8. 8.
    Nystrom, N., Clarkson, M.R., Myers, A.C.: Polyglot: An extensible compiler framework for java. In: Hedin, G. (ed.) CC 2003. LNCS, vol. 2622, pp. 138–152. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  9. 9.
    Otto, F., Pankratius, V., Tichy, W.F.: High-level Multicore Programming with XJava. In: ICSE 2009, New Ideas And Emerging Results. ACM Press, New York (2009)Google Scholar
  10. 10.
    Pankratius, V., Jannesari, A., Tichy, W.F.: Parallelizing BZip2. A Case Study in Multicore Software Engineering. Accepted for IEEE Software (September 2008)Google Scholar
  11. 11.
    Pankratius, V., Schaefer, C., Jannesari, A., Tichy, W.F.: Software engineering for multicore systems: an experience report. In: Proc. IWMSE 2008. ACM Press, New York (2008)Google Scholar
  12. 12.
  13. 13.
    Reinders, J.: Intel Threading Building Blocks. O’Reilly Media, Inc., Sebastopol (2007)Google Scholar
  14. 14.
    Stephens, R.: A Survey of Stream Processing. Acta Informatica 34(7) (1997)Google Scholar
  15. 15.
    Thies, W., Karczmarek, M., Amarasinghe, S.: StreamIt: A language for streaming applications. In: Horspool, R.N. (ed.) CC 2002. LNCS, vol. 2304, p. 179. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Frank Otto
    • 1
  • Victor Pankratius
    • 1
  • Walter F. Tichy
    • 1
  1. 1.University of KarlsruheKarlsruheGermany

Personalised recommendations