Skip to main content

Collecting Performance Data with PAPI-C

  • Conference paper
  • First Online:
Tools for High Performance Computing 2009

Abstract

Modern high performance computer systems continue to increase in size and complexity. Tools to measure application performance in these increasingly complex environments must also increase the richness of their measurements to provide insights into the increasingly intricate ways in which software and hardware interact. PAPI (the Performance API) has provided consistent platform and operating system independent access to CPU hardware performance counters for nearly a decade. Recent trends toward massively parallel multi-core systems with often heterogeneous architectures present new challenges for the measurement of hardware performance information, which is now available not only on the CPU core itself, but scattered across the chip and system. We discuss the evolution of PAPI into Component PAPI, or PAPI-C, in which multiple sources of performance data can be measured simultaneously via a common software interface. Several examples of components and component data measurements are discussed. We explore the challenges to hardware performance measurement in existing multi-core architectures. We conclude with an exploration of future directions for the PAPI interface.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Browne, S., Dongarra, J., Garner, N., Ho, G., Mucci, P.: A portable programming interface for performance evaluation on modern processors. International Journal of High-Performance Computing Applications, Vol. 14, No. 3, pp. 189-204 (2000)

    Article  Google Scholar 

  2. Cameron, K.W., Ge, R., and Feng, X.: High-performance, power-aware distributed computing for scientific applications. Computer, 38(11):40–47 (2005)

    Article  Google Scholar 

  3. Feng, W.C.: The importance of being low power in high performance computing. CTWatch Quarterly, 1(3), August (2005)

    Google Scholar 

  4. Freeh, V.W., Lowenthal, D.K., Pan, F., Kappiah, N.: Using multiple energy gears in MPI programs on a power-scalable cluster. In Principles and Practices of Parallel Programming (PPOPP), June (2005)

    Google Scholar 

  5. Perfmon2 Sourceforge Project Page: http://perfmon2.sourceforge.net

  6. Molnar, I.: Performance Counters for Linux, v8. http://lwn.net/Articles/336542

  7. Moore, S.: A Comparison of Counting and Sampling Modes of Using Performance Monitoring Hardware. ICCS 2002, Amsterdam, April (2002)

    Google Scholar 

  8. Operating System share, November 1999: http://www.top500.org/charts/list/14/os

  9. Operating System share, November 2009: http://www.top500.org/charts/list/34/os

  10. Pettersson, M.: Linux x86 Performance-Monitoring Counters Driver. http://www.csd.uu.se/~mikpe/linux/perfctr

  11. Jarp, S., Jurga, R., Nowak, A.: Perfmon2: A leap forward in Performance Monitoring. Journal of Physics: Conference Series 119, 042017 (2008)

    Article  Google Scholar 

  12. Luszczek, P., Dongarra, J., Koester, D., Rabenseifner, R., Lucas, B., Kepner, J., McCalpin, J., Bailey, D., Takahashi, D.: Introduction to the hpc challenge benchmark suite. Technical report, March (2005)

    Google Scholar 

  13. Hardware Monitoring by lm_sensors: http://www.lm-sensors.org/

  14. Top500 list: http://www.top500.org

  15. NCCS.gov computing resources documentation: http://www.nccs.gov/computing-resources/jaguar

  16. Software Optimization Guide for AMD Family 10h Processors, Pub. no. 40546 (2008)

    Google Scholar 

  17. Chen, J. H., Hawkes, E. R., et al.: Direct numerical simulation of ignition front propagation in a constant volume with temperature inhomogeneities I. fundamental analysis and diagnostics. Combustion and flame, 145, pp. 128-144 (2006)

    Article  Google Scholar 

  18. Sankaran, R., Hawkes, E. R., et al.: Structure of a spatially developing turbulent lean methane-air Bunsen flame. Proceedings of the combustion institute 31, pp. 1291-1298 (2007)

    Google Scholar 

  19. Hawkes, E. R., Sankaran, R., et al.: Scalar mixing in direct numerical simulations of temporally evolving nonpremixed plane jet flames with skeletal CO-H2 kinetics. Proceedings of the combustion institute 31, pp. 1633-1640 (2007)

    Google Scholar 

  20. Cray XT Programming Environment User’s Guide (Version 2.2). S-2396-22, July (2009)

    Google Scholar 

  21. BIOS and Kernel Developer’s Guide (BKDG) for AMD Family 10h Processors (particularly Section 3.12.). Vol. 31116 Rev 3.34, September (2009)

    Google Scholar 

  22. Intel 64 and IA-32 Architectures Software Developer’s Manual Volume 3B: System Programming Guide (Particularly Chapter 19.17.2 Performance Monitoring Facility in the Uncore). Part 2 Order Number: 253669-031US, June (2009)

    Google Scholar 

  23. Walkup, B.: Blue Gene/P Universal Performance Counters. http://www.nccs.gov/wp-content/training/2008_bluegene/BobWalkup_BGP_UPC.pdf

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dan Terpstra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Terpstra, D., Jagode, H., You, H., Dongarra, J. (2010). Collecting Performance Data with PAPI-C. In: Müller, M., Resch, M., Schulz, A., Nagel, W. (eds) Tools for High Performance Computing 2009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11261-4_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-11261-4_11

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11260-7

  • Online ISBN: 978-3-642-11261-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics