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文件名称:GPU-CUDA001
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- 上传时间：2012-11-16
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文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上。
-An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. Neural Networks have been widely used in "analogous" signal classifications, including handwriting, voice and image recognitions. Neural network can also be used in computer games. It enables games with the ability to adaptively learn from player behaviors. This technique has been used in racing games, such that opponent cars controlled by computers can learn how to drive by human players.
Since a Neural Network requires a considerable number of vector and matrix operations to get results, it is very suitable to be implemented in a parallel programming model and run on Graphics Processing Units (GPUs). Our goal is to utilize and unleash the power of GPUs to boost the performance o
-An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. Neural Networks have been widely used in "analogous" signal classifications, including handwriting, voice and image recognitions. Neural network can also be used in computer games. It enables games with the ability to adaptively learn from player behaviors. This technique has been used in racing games, such that opponent cars controlled by computers can learn how to drive by human players.
Since a Neural Network requires a considerable number of vector and matrix operations to get results, it is very suitable to be implemented in a parallel programming model and run on Graphics Processing Units (GPUs). Our goal is to utilize and unleash the power of GPUs to boost the performance o
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GPUNN_demo.zip
GPUNN_GUI.zip
GPUNN_kernel.zip
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