Fast branch misprediction recovery in out-of-order superscalar processors
Department of Computer Science
Current trends in modern out-of-order processors involve implementing deeper pipelines and a large instruction window to achieve high performance. However, as pipeline depth increases, the branch misprediction penalty becomes a critical factor in overall processor performance. Current approaches to handling branch mispredictions either incrementally roll back to in-order state by waiting until the mispredicted branch reaches the head of the reorder buffer, or utilize checkpointing at branches for faster recovery. Rolling back to in-order state stalls the pipeline for a significant number of cycles and checkpointing is costly.This paper proposes a fast recovery mechanism, called Eager Misprediction Recovery (EMR), to reduce the branch misprediction penalty. Upon a misprediction, the processor immediately starts fetching and renaming instructions from the correct path without restoring the map table. Those instructions that access incorrect speculative values wait until the correct data are restored; however, instructions that access correct values continue executing while recovery occurs. Thus, the recovery mechanism hides the latency of long branch recovery with useful instructions.EMR achieves a mean performance improvement very close to a recovery mechanism that supports checkpointing at each branch. In addition, EMR provides an average of 9.0% and up to 19.9% better performance than traditional sequential misprediction recovery on the SPEC2000 benchmark suite.
ICS '05 Proceedings of the 19th annual international conference on Supercomputing
Fast branch misprediction recovery in out-of-order superscalar processors.
ICS '05 Proceedings of the 19th annual international conference on Supercomputing, 41-50.
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