This paper presents the GPU mapping of the recognition algo-rithm of a Convolution Neural Network (CNN). This work is based on a C-implementation of the application. The mapping to GPU was performed through different approaches which are explained in detail. The improvements achieved by each ap-proach are presented as well as the overall speed up of the appli-cation. The GPU implementation demonstrates the feasibility to integrate the algorithm in a real-time system as the frame rate accomplished is 30fps. In order to examine the scalability of the application, the use of multiples GPUs was explored. The CPU implementation is executed on a 800MHz AMD Phenom. The GPU platform used for the experiment is an Nvidia GeForce GTX570. 1
Automatic classification becomes more and more in- teresting as the amount of available data keeps g...
Real-time simulations of biological neural networks (BNNs) provide a natural platform for applicatio...
The human brain is an incredible system which can process, store, and transfer information with high...
Open-source deep learning tools has been distributed numerously and has gain popularity in the past ...
A graphical environment for CNN algorithm development is presented. The new generation of graphical ...
When asked to implement a neural network application, the decision concerning what hardware platform...
Convolutional deep neural networks (CNNs) has been shown to perform well in difficult learning tasks...
There is currently a strong push in the research community to develop biological scale implementatio...
This article introduces a parallel neural network approach implemented over Graphic Processing Units...
This paper proposes an algorithmic optimization for the feature extractors of biologically inspired ...
Simulating biological neural networks is an important task for computational neuroscientists attempt...
This paper presents a hardware accelerated model of a spiking neural network implemented in CUDA C. ...
This thesis deals with the implementation of an application for artificial neural networks simulatio...
AbstractThe pattern recognition (PR) process uses a large number of labelled patterns and compute in...
The Graphics Processing Unit (GPU) parallel architecture is now being used not just for graphics but...
Automatic classification becomes more and more in- teresting as the amount of available data keeps g...
Real-time simulations of biological neural networks (BNNs) provide a natural platform for applicatio...
The human brain is an incredible system which can process, store, and transfer information with high...
Open-source deep learning tools has been distributed numerously and has gain popularity in the past ...
A graphical environment for CNN algorithm development is presented. The new generation of graphical ...
When asked to implement a neural network application, the decision concerning what hardware platform...
Convolutional deep neural networks (CNNs) has been shown to perform well in difficult learning tasks...
There is currently a strong push in the research community to develop biological scale implementatio...
This article introduces a parallel neural network approach implemented over Graphic Processing Units...
This paper proposes an algorithmic optimization for the feature extractors of biologically inspired ...
Simulating biological neural networks is an important task for computational neuroscientists attempt...
This paper presents a hardware accelerated model of a spiking neural network implemented in CUDA C. ...
This thesis deals with the implementation of an application for artificial neural networks simulatio...
AbstractThe pattern recognition (PR) process uses a large number of labelled patterns and compute in...
The Graphics Processing Unit (GPU) parallel architecture is now being used not just for graphics but...
Automatic classification becomes more and more in- teresting as the amount of available data keeps g...
Real-time simulations of biological neural networks (BNNs) provide a natural platform for applicatio...
The human brain is an incredible system which can process, store, and transfer information with high...