SWIP Prediction: Complexity-Effective Indirect-Branch Prediction Using Pointers

Predicting indirect-branch targets has become a performance bottleneck for many applications. Previous highperformance indirect-branch predictors usually require significant hardware storage or additional compiler support, which increases the complexity of the processor front-end or the compilers. This paper proposes a complexity-effective indirectbranch prediction mechanism, called the Set-Way Index Pointing (SWIP) prediction. It stores multiple indirect-branch targets in different branch target buffer (BTB) entries, whose set indices and way locations are treated as set-way index pointers. These pointers are stored in the existing branch-direction predictor. SWIP prediction reuses the branch direction predictor to provide such pointers, and then accesses the pointed BTB entries for the predicted indirect-branch target. Our evaluation shows that SWIP prediction could achieve attractive performance improvement without requiring large dedicated storage or additional compiler support. It improves the indirect-branch prediction accuracy by 36.5% compared to that of a commonly-used BTB, resulting in average performance improvement of 18.56%. Its energy consumption is also reduced by 14.34% over that of the baseline.