Parallel Neural Hardware: The Time is Right
Ulrich Rückert, Erzsébet Merényi · 2012
Abstract. 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.