Analyzing Overheads and Scalability Characteristics of OpenMP Applications

  • Karl Fürlinger
  • Michael Gerndt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4395)


Analyzing the scalability behavior and the overheads of Open-MP applications is an important step in the development process of scientific software. Unfortunately, few tools are available that allow an exact quantification of Open-MP related overheads and scalability characteristics. We present a methodology in which we define four overhead categories that we can quantify exactly and describe a tool that implements this methodology. We evaluate our tool on the Open-MP version of the NAS parallel benchmarks.


Critical Section Cache Size Load Imbalance Parallel Region Synchronization Overhead 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bane, M.K., Riley, G.: Automatic overheads profiler for OpenMP codes. In: Proceedings of the Second Workshop on OpenMP (EWOMP 2000), Edinburgh (Sept. 2000)Google Scholar
  2. 2.
    Bane, M.K., Riley, G.: Extended overhead analysis for OpenMP (research note). In: Monien, B., Feldmann, R.L. (eds.) Euro-Par 2002. LNCS, vol. 2400, pp. 162–166. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Bull, J.M.: A hierarchical classification of overheads in parallel programs. In: Proceedings of the First IFIP TC10 International Workshop on Software Engineering for Parallel and Distributed Systems, pp. 208–219. Chapman and Hall, London (1996)Google Scholar
  4. 4.
    Bull, J.M., O’Neill, D.: A microbenchmark suite for OpenMP 2.0. In: Proceedings of the Third Workshop on OpenMP (EWOMP’01), Barcelona, Spain (Sept. 2001)Google Scholar
  5. 5.
    Fredrickson, N.R., Afsahi, A., Qian, Y.: Performance characteristics of OpenMP constructs, and application benchmarks on a large symmetric multiprocessor. In: Proceedings of the 17th ACM International Conference on Supercomputing (ICS 2003), San Francisco, CA, USA, pp. 140–149. ACM Press, New York (2003)CrossRefGoogle Scholar
  6. 6.
    Fürlinger, K., Gerndt, M.: ompP: A profiling tool for OpenMP. In: Proceedings of the First International Workshop on OpenMP (IWOMP 2005), Eugene, Oregon, USA. Accepted for publication (May 2005)Google Scholar
  7. 7.
  8. 8.
    Jin, H., Frumkin, M., Yan, J.: The OpenMP implementation of NAS parallel benchmarks and its performance. Technical Report NAS-99-011 (1999)Google Scholar
  9. 9.
    Mohr, B., et al.: A performance monitoring interface for OpenMP. In: Proceedings of the Fourth Workshop on OpenMP (EWOMP 2002), Rome, Italy (Sept. 2002)Google Scholar
  10. 10.
    Mohr, B., et al.: Towards a performance tool interface for OpenMP: An approach based on directive rewriting. In: Proceedings of the Third Workshop on OpenMP (EWOMP’01) (Sept. 2001)Google Scholar
  11. 11.
    Solihin, Y., Lam, V., Torrellas, J.: Scal-Tool: Pinpointing and quantifying scalability bottlenecks in DSM multiprocessors. In: Proceedings of the 1999 Conference on Supercomputing (SC 1999), Portland, Oregon, USA (Nov. 1999)Google Scholar
  12. 12.
  13. 13.
    Sutter, H.: The free lunch is over: A fundamental turn toward concurrency in software. Dr. Dobb’s Journal 30(3) (2005)Google Scholar
  14. 14.
    Truong, H.-L., Fahringer, T.: SCALEA: A performance analysis tool for parallel programs. Concurrency and Computation: Practice and Experience 15, 1001–1025 (2003)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Karl Fürlinger
    • 1
  • Michael Gerndt
    • 1
  1. 1.Technische Universität München, Institut für Informatik, Lehrstuhl für Rechnertechnik und Rechnerorganisation 

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