Recently, the discovery of memristor brought the promise of high density, low energy, and combined memory/arithmetic capability into computing. This paper demonstrates a practical neural branch predictor based on memristor. By using analog computation techniques, as well as exploiting the accuracy tolerance of branch prediction, our design is able to efficiently realize a neural prediction algorithm. Compared to the digital counterpart, our method achieves significant energy reduction while maintaining a better prediction accuracy and a higher IPC. Our approach also reduces the resource and energy required by an alternative design
Data-intensive computing operations, such as training neural networks, are essential but energy-inte...
This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of...
Abstract: The main aim of this short paper is to propose a new branch prediction approach called by ...
10.1109/ISLPED.2013.6629290Proceedings of the International Symposium on Low Power Electronics and D...
Accurate branch prediction is essential for modern microprocessors in order to maintain high in-stru...
This paper contributes to a dynamic branch predictor algorithm based on a perceptron in two directio...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
Microarchitectural prediction based on neural learning has received increasing attention in recent y...
In this paper, we propose a Bayesian branch-prediction circuit, consisting of an instruction-feature...
This research shows that using an Artificial Neural Network as the hardware branch predictor of a su...
Analog switching memristive devices can be used as part of the acceleration block of Neural Network...
Abstract—The cessation of Moore’s Law has limited further improvements in power efficiency. In recen...
The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution...
Artificial neural networks are successfully used for classification, prediction, estimation, modelin...
Analogue in-memory computing and brain-inspired computing based on the emerging memory technology ...
Data-intensive computing operations, such as training neural networks, are essential but energy-inte...
This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of...
Abstract: The main aim of this short paper is to propose a new branch prediction approach called by ...
10.1109/ISLPED.2013.6629290Proceedings of the International Symposium on Low Power Electronics and D...
Accurate branch prediction is essential for modern microprocessors in order to maintain high in-stru...
This paper contributes to a dynamic branch predictor algorithm based on a perceptron in two directio...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
Microarchitectural prediction based on neural learning has received increasing attention in recent y...
In this paper, we propose a Bayesian branch-prediction circuit, consisting of an instruction-feature...
This research shows that using an Artificial Neural Network as the hardware branch predictor of a su...
Analog switching memristive devices can be used as part of the acceleration block of Neural Network...
Abstract—The cessation of Moore’s Law has limited further improvements in power efficiency. In recen...
The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution...
Artificial neural networks are successfully used for classification, prediction, estimation, modelin...
Analogue in-memory computing and brain-inspired computing based on the emerging memory technology ...
Data-intensive computing operations, such as training neural networks, are essential but energy-inte...
This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of...
Abstract: The main aim of this short paper is to propose a new branch prediction approach called by ...