In this paper, we examine the application of simple neural processing elements to the problem of dynamic branch prediction in high-performance processors. A single neural network model is considered: the Perceptron. We demonstrate that a predictor based on the Perceptron can achieve a prediction accuracy in excess of that given by conventional Two-level Adaptive Predictors and suggest that neural predictors merit further investigation
In this paper, we propose a Bayesian branch-prediction circuit, consisting of an instruction-feature...
The state-of-the-art branch predictor, TAGE, remains inefficient at identifying correlated branches ...
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughp...
Dynamic branch prediction in high-performance processors is a specific instance of a general time se...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
Original article can be found at: http://www.sciencedirect.com/science/journal/13837621 Copyright El...
Exploiting the huge computing power of modern microprocessors requires fast, accurate branch predict...
Abstract: The main aim of this short paper is to propose a new branch prediction approach called by ...
Previous works have shown that neural branch prediction techniques achieve far lower misprediction r...
Abstract. Previous works have shown that neural branch prediction techniques achieve far lower mispr...
Abstract. Previous works have shown that neural branch prediction techniques achieve far lower mispr...
This research shows that using an Artificial Neural Network as the hardware branch predictor of a su...
Branch predictors are very critical in modern superscalar processors and are responsible for achievi...
This paper contributes to a dynamic branch predictor algorithm based on a perceptron in two directio...
Artificial neural networks (ANNs) have become a popular means of solving complex problems in predict...
In this paper, we propose a Bayesian branch-prediction circuit, consisting of an instruction-feature...
The state-of-the-art branch predictor, TAGE, remains inefficient at identifying correlated branches ...
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughp...
Dynamic branch prediction in high-performance processors is a specific instance of a general time se...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
Original article can be found at: http://www.sciencedirect.com/science/journal/13837621 Copyright El...
Exploiting the huge computing power of modern microprocessors requires fast, accurate branch predict...
Abstract: The main aim of this short paper is to propose a new branch prediction approach called by ...
Previous works have shown that neural branch prediction techniques achieve far lower misprediction r...
Abstract. Previous works have shown that neural branch prediction techniques achieve far lower mispr...
Abstract. Previous works have shown that neural branch prediction techniques achieve far lower mispr...
This research shows that using an Artificial Neural Network as the hardware branch predictor of a su...
Branch predictors are very critical in modern superscalar processors and are responsible for achievi...
This paper contributes to a dynamic branch predictor algorithm based on a perceptron in two directio...
Artificial neural networks (ANNs) have become a popular means of solving complex problems in predict...
In this paper, we propose a Bayesian branch-prediction circuit, consisting of an instruction-feature...
The state-of-the-art branch predictor, TAGE, remains inefficient at identifying correlated branches ...
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughp...