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Nowadays, artificial neural network models have been largely simulated on conventional computers, proving their ability to solve a large range of complicated problems. The real potential of these neural models will only be available with the development of highly parallel architectures that are designed to optimize the intensive computational requirements of these neural models. However, there exists...
The SpiNNaker project aims to develop parallel computer systems with more than a million embedded processors. The goal of the project is to support large-scale simulations of systems of spiking neurons in biological real time, an application that is highly parallel but also places very high loads on the communication infrastructure due to the very high connectivity of biological neurons. The scale...
Our work describes the simulation of a planar network of spiking I/F neurons on graphics processing hardware. The described approach adds to the fast-growing field of general-purpose computation on GPUs (GPGPU). We provide an in-depth explanation of the steps involved in implementing the network using programmable shading hardware. We replicated simulation results by Hopfield et al. and Maida et al...
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