Analyzing Branch Prediction Contexts Influence

All present branch prediction techniques are limited in their accuracy. Our aim is to demonstrate that an important limitation cause is given by the used prediction contexts (global and local histories respectively path information). Using these dynamic contexts, some branches are unbiased and randomly shuffled, therefore unpredictable. The percentages of these branches represent a fundamental prediction limitation. For outperforming this limitation it is necessary additional more relevant context information, in order to further reduce the entropy of these branches