Simulating Wrong-Path Instructions in Decoupled Functional-First Simulation

Wrong-path speculative execution on an out-oforder 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 $3 \times$ lower error than no wrong path modeling and about 2 to $3 \times$ faster simulation than full wrong path emulation.