Title
Clustered indexing for branch predictors
Abstract
As a result of resource limitations, state in branch predictors is frequently shared between uncorrelated branches. This interference can significantly limit prediction accuracy. In current predictor designs, the branches sharing prediction information are determined by their branch addresses and thus branch groups are arbitrarily chosen during compilation. This feasibility study explores a more analytic and systematic approach to classify branches into clusters with similar behavioral characteristics. We present several ways to incorporate this cluster information as an additional information source in branch predictors. Our profile-based results demonstrate that cluster information is useful in various branch prediction schemes. When clustered indexing is applied, the same performance can be obtained with 2-8 times less hardware budget. For small predictor budgets, clustered indexing is very cost-effective, e.g., the misprediction rate in an 8 Kib gshare is reduced 12.3% on average for SPEC CPU2000 INT. For large budgets up to 4 Mib, clustered indexing reduces the number of mispredictions by 3-5%, or stated otherwise only half the hardware budget is required to obtain the same performance as the original gshare scheme.
Year
DOI
Venue
2007
10.1016/j.micpro.2006.08.003
Microprocessors and Microsystems
Keywords
Field
DocType
prediction accuracy,clustered indexing,uncorrelated branch,prediction information,branch address,additional information source,cluster information,hardware budget,branch prediction,various branch prediction scheme,branch predictor,clustering,kib gshare,aliasing,cost effectiveness,indexation,feasibility study
Data mining,Cluster (physics),Computer science,Parallel computing,Uncorrelated,Search engine indexing,Real-time computing,Aliasing,Interference (wave propagation),Spec#,Cluster analysis,Branch predictor
Journal
Volume
Issue
ISSN
31
3
Microprocessors and Microsystems
Citations 
PageRank 
References 
1
0.36
11
Authors
3
Name
Order
Citations
PageRank
Veerle Desmet1363.09
Hans Vandierendonck262954.43
Koen De Bosschere31659117.74