Toward virtualizing branch direction prediction

This work introduces a new branch predictor design that increases the perceived predictor capacity without increasing its delay by using a large virtual second-level table allocated in the second-level caches. Virtualization is applied to a state-of-the-art multi-table branch predictor. We evaluate the design using instruction count as proxy for timing on a set of commercial workloads. For a predictor whose size is determined by access delay constraints, accuracy can be improved by 8.7%. Alternatively, the design can be used to achieve the same accuracy as a non-virtualized design while using 25% less dedicated storage.