A comparison of dynamic branch predictors that use two levels of branch history
ISCA '93 Proceedings of the 20th annual international symposium on computer architecture
Skewed associativity enhances performance predictability
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
Target prediction for indirect jumps
Proceedings of the 24th annual international symposium on Computer architecture
The cascaded predictor: economical and adaptive branch target prediction
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Predicting indirect branches via data compression
MICRO 31 Proceedings of the 31st annual ACM/IEEE international symposium on Microarchitecture
Execution Characteristics of Object Oriented Programs on the UltraSPARC-II
HIPC '98 Proceedings of the Fifth International Conference on High Performance Computing
ICCD '00 Proceedings of the 2000 IEEE International Conference on Computer Design: VLSI in Computers & Processors
Do object-oriented languages need special hardware support?
Do object-oriented languages need special hardware support?
Shade: A Fast Instruction Set Simulator for Execution Profiling
Shade: A Fast Instruction Set Simulator for Execution Profiling
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In this paper, we present a new hybrid branch predictor called the GoStay2, which can effectively reduce indirect misprediction rates. The GoStay2 has two different mechanisms compared to other 2- stage hybrid predictors that use a Branch Target Buffer (BTB) as the first stage predictor: Firstly, to reduce conflict misses in the first stage, a new effective 2-way cache scheme is used instead of a 4-way setassociative. Secondly, to reduce mispredictions caused by an inefficient predict and update rule, a new selection mechanism and update rule are proposed. We have developed a simulation program by using Shade and Spixtools, provided by SUN Microsystems, on an Ultra SPARC/10 processor. Our results show that the GoStay2 improves indirect misprediction rates of a 64-entry to 4K-entry BTB (with a 512- or 1K- entry PHT) by 14.9% to 21.53% compared to the leaky filter.