Wrong-path speculative execution on an out-of-order processor core has no impact on an application's functionality and correctness, but it can impact performance by changing the state of caches and predictors. Not modeling wrong-path execution in performance simulation leads to performance projection errors up to 22% for our setup. However, wrong-path execution is challenging to model for common functional-first simulators, because the functional simulator is not aware of branch predictor misses and only provides correct-path instructions. We propose and evaluate multiple wrong-path modeling techniques for functional-first simulators, each with a different accuracy versus simulation speed balance. The novel instruction reconstruction with convergence exploitation technique proves to be the best balanced technique, with about 3x lower error than no wrong path modeling and about 2 to 3x faster simulation than full wrong path emulation.
