Add to ORKGAbstract. It seems obvious that the massively parallel computations inherent in artificial neural networks (ANNs) can only be realized by massively parallel hardware. However, the vast majority of the many ANN applications simulate their ANNs on sequential computers which, in turn, are not resource-efficient. The increasing availability of parallel standard hardware such as FPGAs, graphics processors, and multi-core processors offers new scopes and challenges in respect to resource-efficiency and real-time applications of ANNs. Within this paper we will discuss some key issues for parallel ANN implementation on these standard devices compared to special purpose ANN implementations
Neural networks are employed in a large variety of practical contexts. However, the majority of such...
Article dans revue scientifique avec comité de lecture.The distributed structure of artificial neura...
Abstract. The first successful FPGA implementation [1] of artificial neural networks (ANNs) was publ...
It seems to be an everlasting discussion. Spending a lot of additional time and extra money to imple...
As artificial neural networks (ANNs) gain popularity in a variety of application domains, it is crit...
Colloque avec actes et comité de lecture. internationale.International audienceNeural networks are c...
Abstra t. Neural networks are onsidered as naturally parallel omputing models. But the number of o...
Over the past decade a large variety of hardware has been designed to exploit the inherent paralleli...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
Algorithms, applications and hardware implementations of neural networks are not investigated in clo...
Artificial Neural Network (ANN) is very powerful to deal with signal processing, computer vision and...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
Artificial neural network (ANN) has been widely used in many applications and has been started to be...
Parallelism and distribution have been considered the key features of neural processing. The term pa...
Living creatures pose amazing ability to learn and adapt, therefore researchers are trying to apply ...
Neural networks are employed in a large variety of practical contexts. However, the majority of such...
Article dans revue scientifique avec comité de lecture.The distributed structure of artificial neura...
Abstract. The first successful FPGA implementation [1] of artificial neural networks (ANNs) was publ...
It seems to be an everlasting discussion. Spending a lot of additional time and extra money to imple...
As artificial neural networks (ANNs) gain popularity in a variety of application domains, it is crit...
Colloque avec actes et comité de lecture. internationale.International audienceNeural networks are c...
Abstra t. Neural networks are onsidered as naturally parallel omputing models. But the number of o...
Over the past decade a large variety of hardware has been designed to exploit the inherent paralleli...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
Algorithms, applications and hardware implementations of neural networks are not investigated in clo...
Artificial Neural Network (ANN) is very powerful to deal with signal processing, computer vision and...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
Artificial neural network (ANN) has been widely used in many applications and has been started to be...
Parallelism and distribution have been considered the key features of neural processing. The term pa...
Living creatures pose amazing ability to learn and adapt, therefore researchers are trying to apply ...
Neural networks are employed in a large variety of practical contexts. However, the majority of such...
Article dans revue scientifique avec comité de lecture.The distributed structure of artificial neura...
Abstract. The first successful FPGA implementation [1] of artificial neural networks (ANNs) was publ...