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Fast branch misprediction recovery in out-of-order superscalar processors
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Source International Conference on Supercomputing archive
Proceedings of the 19th annual international conference on Supercomputing table of contents
Cambridge, Massachusetts
SESSION: Session 2: value table of contents
Pages: 41 - 50  
Year of Publication: 2005
ISBN:1-59593-167-8
Authors
Peng Zhou  Michigan Technological University, Houghton, Michigan
Soner Önder  Michigan Technological University, Houghton, Michigan
Steve Carr  Michigan Technological University, Houghton, Michigan
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 57,   Citation Count: 5
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ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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REVIEW

"Ronaldo A. L. Goncalves : Reviewer"

This paper proposes a mechanism, eager misprediction recovery (EMR), for recovering the processor state after branch misprediction in modern out-of-order architectures. The idea of this mechanism is to restart the instruction fetching on the corre  more...

Collaborative Colleagues:
Peng Zhou: colleagues
Soner Önder: colleagues
Steve Carr: colleagues