Cached two-level adaptive branch predictors with multiple stages

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2299, Issue , 2002, Pages 179-191

  Egan, Colin ^a   Steven, Gordon ^a   Vintan, Lucian ^b  

^a UNIVERSITY OF HERTFORDSHIRE   (United Kingdom)

^b University Lucian Braga of Sibiu   (Romania)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ARCHITECTURE; NETWORK ARCHITECTURE; UBIQUITOUS COMPUTING;

BRANCH PREDICTION; BRANCH PREDICTORS; CACHE MISS; HIGH-ACCURACY; MULTI STAGE; MULTIPLE STAGES; TWO-LEVEL PREDICTOR; TWO-STAGE PREDICTORS;

FORECASTING;

EID: 0345340029     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45997-9_14     Document Type: Conference Paper

References (16)

1. Yeh, T. and Patt, Y. N.: Two-Level Adaptive Training Branch Prediction, Micro-24, Albuquerque, New Mexico, (1991), 51-61.
2. Pan, S.; So, K. and Rahmeh, J. T.: Improving the Accuracy of Dynamic Branch Prediction Using Branch Correlation, ASPLOS-V, Boston, (1992), 76-84.
3. IA-64 Application Developer.s Guide, Intel, (2000).
4. Kessler, R. E.: The Alpha 21264 Microprocessor, IEEE Micro, (1999), 24-36.
5. Egan, C.: Dynamic Branch Prediction in High Performance Superscalar Processors, PhD thesis, University of Hertfordshire, (2000).
6. Steven, G. B.; Egan, C.; Quick, P. and Vintan, L.: A Cost Effective Cached Correlated Two-level Adaptive Branch Predictor, 18th IASTED International Conference on Applied Informatics (AI 2000), Innsbruck, (2000).
7. Yeh, T. and Patt, P.: Alternative Implementations of Two-Level Adaptive Branch Prediction, ISCA-19, Gold Coast, Australia, (1992), 124-134.
8. Yeh, T. and Patt, Y. N.: A Comparison of Dynamic Branch Predictors that use Two Levels of Branch History, ISCA - 20, (1993), 257-266.
9. McFarling, S.: Combining Branch Predictors, Western Research Laboratories Technical Report TN-36, (1993).
10. Chang, P., Hao, E., Yeh, T. and Patt, Y. N.: Branch Classification: A New Mechanism for Improving Branch Predictor Performance, Micro-27, San Jose, California, (1994), 22-31.
11. Lee, C. C., Chen, I. K. and Mudge, T. N.: The Bi-Mode Branch Predictor, Micro-30, Research Triangle Park, North Carolina, (1997), 4-13.
12. Sprangle, E., Chappell, R. S., Alsup, M. and Patt, Y. N.: The Agree Predictor: A Mechanism for Reducing Negative Branch History Interference, ISCA.24, Denver, Colorado, (1997), 284-291.
13. Chen, I. K., Coffey, J. T. and Mudge, T. N.: Analysis of Branch Prediction via Data Compression, ASPLOS VII, (1996), 128-137.
14. Steven, G., Anguera, R., Egan, C., Steven, F. and Vintan, L.: Dynamic Branch Prediction Using Neural Networks, DSD 2001, Poland, (2001), 178-185.
15. Chang, L, Hao E. and Patt, Y. N.: Alternative Implementations of Hybrid Branch Predictors, Micro-29, Ann Arbor, Michigan, (1995), 252-257.
16. Steven, G. B., Christianson, D. B., Collins, R., Potter, R. D. and Steven, F. L.: A Superscalar Architecture to Exploit Instruction Level Parallelism, Microprocessors and Microsystems, 20 (7), (1997), 391-400.