Advertisement

An Introduction to Performance Debugging for Parallel Computers

Chapter
  • 575 Downloads
Part of the ICASE/LaRC Interdisciplinary Series in Science and Engineering book series (ICAS, volume 4)

Abstract

Programming parallel computers for performance is a difficult task that requires careful attention to both single-node performance and data exchange between processors. This chapter discusses some of the sources of poor performance, ways to identify them in an application, and a few ways to address these issues.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Message Passing Interface Forum, 1994. “MPI: A message-passing interface standard,”, Int. J. Supercomput. Applics. 8, pp. 159–416. http://www.mcs.anl.gov/mpi/mpi-report/mpi-report.htmlGoogle Scholar
  2. Foster, I., Gropp, W., and Stevens, R., 1992. “The parallel scalability of the spectral transform method,” Monthly Weather Review 120, pp. 835–850.CrossRefGoogle Scholar
  3. Gropp, W. and Smith, E., 1990. “Computational fluid dynamics on parallel processors,” Computers and Fluids 18, pp. 289–304.zbMATHCrossRefGoogle Scholar
  4. Gropp, W., Lusk, E., and Skjellum, A., 1994. Using MPI, MIT Press.Google Scholar
  5. Gropp, W. D. and Keyes, D. E., 1988. “Complexity of parallel implementation of domain decomposition techniques for elliptic partial differential equations,” SIAM J. Stat. Sci. Comp. 9, pp. 312–326.MathSciNetzbMATHCrossRefGoogle Scholar
  6. Heath, M. T. and Finger, J. E., September 1991. “Visualizing performance of parallel programs,” IEEE Software 8, pp. 29–39.CrossRefGoogle Scholar
  7. Herrarte, V. and Lusk, E., 1991. “Studying parallel program behavior with Upshot,” Technical Report ANL-91/15, Argonne National Laboratory, Mathematics and Computer Science Division.Google Scholar
  8. Nicol, D. M., 1990. “Inflated speedups in parallel simulations via malloc,” ICASE Technical Report 90-63.Google Scholar
  9. Reed, D. A., Aydt, R. A., Noe, R. J., Roth, P. C., Shields, K. A., Schwartz, B., and Tavera, L. F., 1993. “Scalable performance analysis: The Pablo performance analysis environment,” in Proc. Scalable Parallel Libraries Conference, Anthony Skjel-lum, ed., IEEE Computer Society, Los Alamitos.Google Scholar
  10. Yan, J., Hontalas, P., and Listgarten, S., 1993. The Automated Instrumentation and Monitoring System (AIMS) Reference Manual NASA TM-108795.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  1. 1.Mathematics and Computer Science DivisionArgonne National LaboratoryArgonneUSA

Personalised recommendations