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Branch prediction for network processors

Bermingham, David and Liu, Zhen and Wang, Xiaojun and Liu, Bin (2008) Branch prediction for network processors. In: ICM 2008 - International Conference on Microelectronics, 14-17 December 2008, Sharjah, United Arab Emirates. ISBN 978-1-4244-2369-9

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Abstract

Meeting the future requirements of higher bandwidth while providing ever more complex functions, future network processors will require a number of methods of improving processing performance. One such method will involve deeper processor pipelines to obtain higher operating frequencies. Mitigation of the penalty costs associated with deeper pipelines have achieved by implementing prediction schemes, with previous execution history used to determine future decisions. In this paper we present an analysis of common branch prediction schemes when applied to network applications. Using widespread network applications, we find that unlike general purpose processing, hit rates in excess of 95% can be obtained in a network processor using a small 256-entry single level predictor. While our research demonstrates the low silicon cost of implementing a branch predictor, the long run times of network applications can leave the majority of the predictor logic idle, increasing static power and reducing device utilization.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computer architecture; multiprocessing systems; pipeline processing;
Subjects:Engineering > Telecommunication
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Published in:Proceedings of the 2008 International Conference on Microelectronics. . Institute of Electrical and Electronics Engineers. ISBN 978-1-4244-2369-9
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/ICM.2008.5393519
Copyright Information:©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Funders:Science Foundation Ireland
ID Code:15531
Deposited On:21 Jul 2010 09:49 by DORAS Administrator. Last Modified 21 Jul 2010 09:52

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