GNeuron1.0 is a stream approach to neural networks. Neural network operations expose a high degree of parallelism.This parallelism is exposed throughly by GPU(Graphics Processing Units)
Backpropagation is a supervised learning technique used for training artificial neural networks. Supervised learning indicates that prior to using it, it has been trained throughly with a set of inputs and outputs.The characteristic of this algorithm is that there is no feedback between the layers.Hence the name
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GPU stands for Graphics Processing Unit.They are highly parallel units which are largely unused for general purposes.The reason is that mapping a general task to a more graphics task is difficult.This field has been referred to as GPGPU.And the results have been stunning. A low-end gpu can outclass a high-end CPU
More...This project utilizes the enormous computing power of GPU for parallelizing the Backpropagation operation.Accelerator from Microsoft Research is used as GPU library