Improving the accuracy of branch prediction n for superscalar processors by employing both the global and local branch history information

• Main Author: 周宇文
• Other Authors: 張孟洲
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/79019460335724389391

碩士 === 長庚大學 === 電機工程研究所 === 89 === As the pipeline depth and issue rate of high-performance superscalar processors increase, the importance of an excellent branch predictor becomes more crucial to delivering the potential performance of a wide-issue, deep pipelined processor. Conventional two-level branch predictors predict the outcome of a branch either based on the local branch history information, comprising the previous outcomes of a single branch, or based on the global branch history information, comprising the previous outcomes of all branches. In this paper we propose a new branch prediction scheme, called GLshare, which employs both the global and local branch history information simultaneously to improve the branch prediction accuracy for superscalar processors. We show that GLshare can achieve higher branch prediction accuracy than conventional two-level predictors such as gshare and modified PAs.