Dynamic Prediction of Critical Path Instructions

Modern processors come close to executing as fast as true dependences allow. The particular dependences that constrain execution speed constitute the critical path of execution. To optimize the performance of the processor, we either have to reduce the critical path or execute it more efficiently. In both cases, it can be done more effectively if we know the actual instructions that constitute that path. This paper describes Critical Path Prediction for dynamically identifying instructions likely to be on the critical path, allowing various processor optimizations to take advantage of this information. We show several possible critical path prediction techniques, and apply critical path prediction to value prediction and clustered architecture scheduling. We show that critical path prediction has the potential to increase the effectiveness of these hardware optimizations by as much as 70%, without adding greatly to their cost.