Skip to main content

Static Techniques to Improve Power Efficiency of Branch Predictors

  • Conference paper
High Performance Computing - HiPC 2004 (HiPC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3296))

Included in the following conference series:

  • 655 Accesses

Abstract

In this paper, we illustrate the application of two static techniques to reduce the activities of the branch predictor in a processor leading to its significant power reduction. We introduce the use of a static branch target buffer (BTB) that achieves the similar performance to the traditional branch target buffer but which eliminates most of the state updates thus reducing the power consumption of the BTB significantly. We also introduce a correlation-based static prediction scheme into a dynamic branch predictor so that those branches that can be predicted statically or can be correlated to the previous ones will not go through normal prediction algorithm. This reduces the activities and conflicts in the branch history table (BHT). With these optimizations, the activities and conflicts of the BTB and BHT are reduced significantly and we are able to achieve a significant reduction (43.9% on average) in power consumption of the BPU without degradation in the performance.

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 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.

References

  1. Yeh, T.Y., Patt, Y.N.: Two Level Adaptive Branch prediction. In: 24th ACM/IEEE International Symposium on Microarchitecture (November 1991)

    Google Scholar 

  2. Yeh, T.Y., Patt, Y.N.: A Comparison of Dynamic Branch Predictors that Use Two levels of Branch History. In: 20th Annual International Symposium on Computer Architecture (May 1996)

    Google Scholar 

  3. Young, C., Gloy, N., Smith, M.D.: A Comparative Analysis of Schemes For Correlated Branch Prediction. In: ACM SIGARCH Computer Architecture News, Proceedings of the 22nd annual International Symposium on Computer Architecture, May 1995, vol. 23(2) (1995)

    Google Scholar 

  4. Sechrest, S., Lee, C.C., Mudge, T.: Correlation and Aliasing in Dynamic Branch Predictors. In: ACM SIGARCH Computer Architecture News, Proceedings of the 23rd annual international symposium on Computer architecture, May 1996, vol. 24(2) (1996)

    Google Scholar 

  5. Parikh, D., Skadron, K., Zhang, Y., Barcella, M., Stan, M.: Power Issues Related to Branch Prediction. In: Proc. of the 2002 International Symposium on High-Performance Computer Architecture, Cambridge, MA (February 2002)

    Google Scholar 

  6. Patil, H., Emer, J.: Combining static and dynamic branch prediction to reduce destructive aliasing. In: Proceedings of the 6th Intl. Conference on High Performance Computer Architecture, January 2000, pp. 251–262 (2000)

    Google Scholar 

  7. Young, C., Smith, M.D.: Improving the Accuracy of Static Branch Prediction Using Branch Correlation. In: ASPLOS 1994, pp. 232–241 (1994)

    Google Scholar 

  8. Young, C., Smith, M.D.: Static correlated branch prediction. TOPLAS 21(5), 1028–1075 (1999)

    Article  Google Scholar 

  9. McFarling, S.: Combining branch predictors. Tech. Note TN-36, DEC WRL (June 1993)

    Google Scholar 

  10. Pan, S.-T., So, K., Rahmeh, J.T.: Improving the Accuracy of Dynamic Branch Prediction Using Branch Correlation. In: ASPLOS 1992, pp. 76–84 (1992)

    Google Scholar 

  11. Haungs, M., Sallee, P., Farrens, M.K.: Branch Transition Rate: A New Metric for Improved Branch Classification Analysis. In: HPCA 2000, pp. 241–250 (2000)

    Google Scholar 

  12. Grunwald, D., Lindsay, D., Zorn, B.: Static methods in hybrid branch prediction. In: Proc. Of the International Conference on Parallel Architectures and Compilation Techniques (PACT), October 1998, pp. 222–229 (1998)

    Google Scholar 

  13. Dhodapkar, A.S., Smith, J.E.: Managing Multi-Configuration Hardware via Dynamic Working Set Analysis. In: Proc. of the 29 Intl. Sym. on Computer Architecture, May 2002, pp. 233–244 (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, T., Shi, W., Pande, S. (2004). Static Techniques to Improve Power Efficiency of Branch Predictors. In: Bougé, L., Prasanna, V.K. (eds) High Performance Computing - HiPC 2004. HiPC 2004. Lecture Notes in Computer Science, vol 3296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30474-6_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30474-6_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24129-4

  • Online ISBN: 978-3-540-30474-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics