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A comparative analysis of schemes for correlated branch prediction
1995
Proceedings of the 22nd annual international symposium on Computer architecture - ISCA '95
Modern high-performance architectures require extremely accurate branch prediction to overcome the performance limitations of conditional branches. We present a framework that categorizes branch prediction schemes by the way in which they partition dynamic branches and by the kind of predictor that they use. The framework allows us to compare and contrast branch prediction schemes, and to analyze why they work. We use the framework to show how a static correlated branch prediction scheme
doi:10.1145/223982.224438
dblp:conf/isca/YoungGS95
fatcat:h67lwy65pvfcrh4asmfbm3z2ru