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Volumn 19, Issue 1, 1997, Pages 188-222

Evidence-Based Static Branch Prediction Using Machine Learning

Author keywords

C.4 Computer Systems Organization : Performance of Systems measurement techniques; D.3.4 Programming Languages : Processors compilers; optimization; I.2.6 Artificial Intelligence : Learning connectionism and neural nets; parameter learning

Indexed keywords

COMPUTER ARCHITECTURE; COMPUTER PROGRAMMING LANGUAGES; DECISION TABLES; NEURAL NETWORKS; OPTIMIZATION; PROGRAM COMPILERS; SUBROUTINES;

EID: 0030784721     PISSN: 01640925     EISSN: None     Source Type: Journal    
DOI: 10.1145/239912.239923     Document Type: Article
Times cited : (77)

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    • CALDER, B., GRUNWALD, D., AND ZORN, B. 1994. Quantifying behavioral differences between C and C++ programs. J. Program. Lang. 2, 4. Also available as Tech. Rep. CU-CS-698-94, Univ. of Colorado, Boulder, Colo.
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  • 10
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    • Chang, P.P.1    Hwu, W.W.2
  • 11
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    • CHANG, P. P., MAHLKE, A. S., AND HWU, W. W. 1991. Using profile information to assist classic compiler code optimizations. Softw. Pract. Exper. 21, 12, 1301-1321.
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    • Fisher, J.A.1
  • 28
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    • A comparison of dynamic branch predictors that use two levels of branch history
    • ACM, New York
    • YEH, T.-Y. AND PATT, Y. N. 1993. A comparison of dynamic branch predictors that use two levels of branch history. In the 20th Annual International Symposium on Computer Architecture. ACM, New York, 257-266.
    • (1993) 20th Annual International Symposium on Computer Architecture , pp. 257-266
    • Yeh, T.-Y.1    Patt, Y.N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.