Computing of Neural Network on Graphics Card
نویسنده
چکیده
This paper deals the potential of parallel computing on graphics cards. In many applications we encounter time-consuming mathematical or general computing operations, which handle large amounts of data. One of these applications is artificial neural network. One solution to speed up such calculations is to get them done on a graphics card. Graphics cards with CUDA (Compute Unified Device Architecture) interface allow programmers to use parallel performance of modern graphics cards. In computing of neural network were used libraries Jacked and GPUmat created for Matlab enable parallel computing on the graphics processing unit (GPU). Then we tested the acceleration of chosen mathematical operations on selected graphics cards. Computing of training algorithm for neural network contains mathematical matrix operations, which is possible very good parallel execute on GPU. As practical example we implemented hand written digit recognition using artificial neural networks.
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