Branch Prediction is a key task in the operation of a high performance processor. An inaccurate branch predictor results in increased program run-time and a rise in energy consumption. The drive towards processors with limited die-space and tighter energy requirements will continue to intensify over the coming years, as will the shift towards increasingly multicore processors. Both trends make ...

Perceptron based predictors are highly accurate. This high accuracy is the result of exploiting long history lengths [1] and is achieved at the expense of high complexity. The dot product of two vectors is used as prediction. The first vector is the branch outcome history where the second vector is composed of per branch weights, which represent the correlation between branch outcome and previo...

This paper investigates how dynamic branch prediction in a microprocessor affects the predictability of execution time for software running on that processor. By means of experiments on a number of real processors employing various forms of branch prediction, we evaluate the impact of branch predictors on execution time predictability. The results indicate that dynamic branch predictors give a ...

Caches are partitioned into subarrays for optimal timing In a set associative cache if the way holding the data is known before an access only subarrays for that way need to be accessed Reduction in cache switching activities results in energy savings In this paper we propose to extend the branch pre diction framework to enable way footprint prediction The next fetch address and its way footpri...

Deep pipelines and fast clock rates are necessitating the development of high accuracy branch predictors. From microarchitectural viewpoint, in the last decade the importance of indirect branch prediction increased even though, in the computing programs the indirect jumps remain less frequent than the more predictable conditional branches. One reason refers to predicative execution that implies...

This work investigates the potential of direction-correlations to improve branch prediction. There are two types of direction-correlation: affectors and affectees. This work considers for the first time their implications at a basic level. These correlations are determined based on dataflow graph information and are used to select the subset of global branch history bits used for prediction. If...

Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Abstract Today's deeply pipelined, superscalar processors rely on accura...

The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in prediction accuracy is proportional to th...

Indirect branch prediction is likely to become more critical to program performance because indirect branches occur more frequently in object-oriented programs. We study indirect branch behavior in both procedural and object-oriented programs in order to build more accurate predictor architectures. First we use a statically classifying hybrid predictor with a shared history table and separate h...