[go: up one dir, main page]

Skip to main content

PerPI: A Tool to Measure Instruction Level Parallelism

  • Conference paper
Applied Parallel and Scientific Computing (PARA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7133))

Included in the following conference series:

Abstract

We introduce and describe PerPI, a software tool analyzing the instruction level parallelism (ILP) of a program. ILP measures the best potential of a program to run in parallel on an ideal machine – a machine with infinite resources. PerPI is a programmer-oriented tool the function of which is to improve the understanding of how the algorithm and the (micro-) architecture will interact. PerPI fills the gap between the manual analysis of an abstract algorithm and implementation-dependent profiling tools. The current version provides reproducible measures of the average number of instructions per cycle executed on an ideal machine, histograms of these instructions and associated data-flow graphs for any x86 binary file. We illustrate how these measures explain the actual performance of core numerical subroutines when measured run times cannot be correlated with the classical flop count analysis.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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.

Similar content being viewed by others

References

  1. Hennessy, J.L., Patterson, D.A.: Computer Architecture – A Quantitative Approach, 4th edn. Morgan Kaufmann (2007)

    Google Scholar 

  2. Higham, N.J.: Accuracy and Stability of Numerical Algorithms. SIAM (2002)

    Google Scholar 

  3. Langlois, P., Louvet, N.: More Instruction Level Parallelism Explains the Actual Efficiency of Compensated Algorithms. Technical Report, DALI Research Team (2007), http://hal.archives-ouvertes.fr/hal-00165020

  4. Luk, C., Cohn, R., Muth, R., Patil, H., Klauser, A., Lowney, G., Wallace, S., Reddi, V., Hazelwood, K.: Pin: Building Customized Program Analysis Tools with Dynamic Instrumentation. In: PLDI 2005: Proceedings of the 2005 ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 190–200 (2005)

    Google Scholar 

  5. Ogita, T., Rump, S.M., Oishi, S.: Accurate Sum and Dot Product. SIAM J. Sci. Comput. 26(6), 1955–1988 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  6. PAPI, http://icl.cs.utk.edu/papi

  7. Pin, http://www.pintool.org

  8. Rump, S.M.: Ultimately fast accurate summation. SIAM J. Sci. Comput. 31(5), 3466–3502 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  9. Rump, S.M., Ogita, T., Oishi, S.: Accurate floating-point summation – part I: Faithful rounding. SIAM J. Sci. Comput. 31(1), 189–224 (2008)

    Article  MATH  Google Scholar 

  10. Touati, S.: Towards a Statistical Methodology to Evaluate Program Speedups and their Optimisation Techniques. Technical Report, PRISM, UVSQ (2009), http://hal.archives-ouvertes.fr/hal-00356529/en/

  11. Weaver, V., Dongarra, J.: Can Hardware Performance Counters Produce Expected, Deterministic Results? In: 3rd Workshop on Functionality of Hardware Performance Monitoring, Atlanta, GA (December 4, 2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Kristján Jónasson

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Goossens, B., Langlois, P., Parello, D., Petit, E. (2012). PerPI: A Tool to Measure Instruction Level Parallelism. In: Jónasson, K. (eds) Applied Parallel and Scientific Computing. PARA 2010. Lecture Notes in Computer Science, vol 7133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28151-8_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28151-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28150-1

  • Online ISBN: 978-3-642-28151-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics