Enhancing the Accuracy of O-GEHL Branch Predictor: Analysis and Approach
نویسندگان
چکیده
In the first international branch prediction competition, the O-GEHL branch predictor has shown to yield the highest prediction accuracy under an official limited storage budget of 64Kbits. In this paper, we propose and evaluate two alternative designs of the predictor to further improve its efficiency. The first proposed method dynamically adjusts the lengths of branch history used in its indexing function with regard to the type of a benchmark currently in execution. The aim is to increase space utilization of the first predictor table. The second one proposes to add an extra table into the predictor using the space saved from the sharing of hysteresis bits. Experimental results show that each scheme increases the accuracy of two different predictor configurations, creating two attractive research paths for future explorations.
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