Karel Slany
ABSTRACT
In this work a branch prediction system which utilizes evolutionary techniques is introduced. It allows the predictor to adapt to the executed code and thus to improve its performance on the fly. Experiments with the predictor system were performed and the results display how various parameters can impact its performance on various executed code. It is evident that a one-level predictor can be evolved whose performance is better than comparable predictors of the same class. The dynamic prediction system predicts with a relative high accuracy and outperforms any static predictor of the same class.
- E. Damiani, A. Tettamanzi, and V. Liberali. On-line evolution of fpga-based circuits: A case study on hash functions. The First NASA/DoD Workshop on Evolvable Hardware, 1999. Google Scholar
Digital Library
- C. Egan, G. Steven, P. Quick, R. Anguera, F. Steven, and L. Vintan. Two-level branch prediction using neural networks. Journal of Systems Architecture, 49(12):557--570, December 2003. Google ScholarDigital Library
- K. Glette, J. Torresen, and M. Yasunaga. An online ehw pattern recognition system applied to sonar spectrum classification.Google Scholar
- D. A. Jiménez and C. Lin. Neural methods for dynamic branch prediction. ACM Transactions on Computer Systems, 20:369--397, 2002. Google ScholarDigital Library
- A. A. Rustan. Using artificial neural networks to improve hardware branchpredictors. International Joint Conference on Neural Networks, 5:3419--3424, 1999.Google Scholar
- L. Sekanina. Evolvable Components: From Theory to Hardware. Springer-Verlag, Berlin Heidelberg, 2004. Google ScholarDigital Library
- K. Slaný and V. Dvorák. Evolutionary designed branch predictors. 13th International Conference on Soft Computing, pages 18--23, 2007.Google Scholar
- J. E. Smith. A study of branch prediction strategies. Proceedings of the 8th annual symposium on Computer Architecture, pages 135--148, 1981. Google ScholarDigital Library
- E. Sprangle and D. Carmean. Increasing processor performance by implementing deeper pipelines. Proceedings of the 29th annual international symposium on Computer architecture, pages 25--34, 2002. Google ScholarDigital Library
- T.-Y. Yeh and Y. N. Patt. Two-level adaptive training branch prediction. International Symposium on Microarchitecture, pages 51--61, 1991. Google ScholarDigital Library
Index Terms
- Branch predictor on-line evolutionary system
Recommendations
NTB branch predictor: dynamic branch predictor for high-performance embedded processors
Branch prediction accuracy becomes more crucial in high-performance embedded processors. The importance of branch prediction in embedded processors continues to grow in the future. Many branch predictors have been proposed to alleviate the performance ...
A novel meta predictor design for hybrid branch prediction
Recent systems have been paved the way for being high-performance due to the super-pipelining, dynamic scheduling and superscalar processor technologies. The performance of the system is greatly affected by the accuracy of the branch prediction because ...
Design tradeoffs for the Alpha EV8 conditional branch predictor
Special Issue: Proceedings of the 29th annual international symposium on Computer architecture (ISCA '02)This paper presents the Alpha EV8 conditional branch predictor The Alpha EV8 microprocessor project, canceled in June 2001 in a late phase of development, envisioned an aggressive 8-wide issue out-of-order superscalar microarchitecture featuring a very ...
Comments