FFT (fast Fourier transform) plays a very important role in many fields, such as digital signal processing, digital image processing and so on. However, in application, FFT becomes a factor of affecting the processing efficiency, especially in remote sensing, which large amounts of data need to be processed with FFT. So shortening the FFT computation time is particularly important. GPU (Graphic...

We present a gravitational hierarchical N-body code that is designed to run efficiently on Graphics Processing Units (GPUs). All parts of the algorithm are exectued on the GPU which eliminates the need for data transfer between the Central Processing Unit (CPU) and the GPU. Our tests indicate that the gravitational tree-code outperforms tuned CPU code for all parts of the algorithm and show an ...

Due to the rapid advance of general-purpose graphics processing unit (GPU), it is an active research topic to study performance improvement of non-linear optimization with parallel implementation on GPU, as attested by the much research on parallel implementation of relatively simple optimization methods, such as the conjugate gradient method. We study in this context the L-BFGS-B method, or th...

The Graphics Processing Unit (GPU) has extended its applications from its original graphic rendering to more general scientific computation. Through massive parallelization, state-ofthe-art GPUs can deliver 200 billion floating-point operations per second (0.2 TFLOPS) on a single consumer-priced graphics card. This paper describes our attempt in leveraging GPUs for efficient HMM model training....

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Most relatively modern desktop or even laptop computers contain a graphics card useful for more than showing colors on a screen. In this paper, we make a case for why you should learn enough about GPU (graphics processing unit) computing to use as an accelerator or even replacement to your CPU code. We include an example of our own as a case study to show what can be realistically expected.

Greedy Restrictive Boltzmann Machines yield an fairly low 0.72% error rate on the famous MNIST database of handwritten digits. All that was required to achieve this result was a high number of hidden layers consisting of many neurons, and a graphics card to greatly speed up the rate of learning. Keywords—ANN (Artificial Neural Networks), RBM (Restrictive Boltzmann Machine), MNIST handwritten da...

Recently developed architecture such as Compute Unified Device Architecture (CUDA) allows us to exploit the computational power of Graphics Processing Units (GPU). In this paper we propose an algorithm for implementation of Cover tree, accelerated on the graphics processing unit (GPU). The existing algorithm for Cover Tree implementation is for single core CPU and is not suitable for applicatio...

Sobel is one of the most popular edge detection operators used in image processing. To date, users utilize two-directional 3×3 operator as detectors because its low computational cost and reasonable performance. Simultaneously, many studies have been conducted on using large multi-directional to satisfy their needs considering high stability, but at an expense speed. This paper proposes a fast ...

We present a set of algorithms for simulating and visualizing real-time crowds in GPU (Graphics Processing Units) clusters. First we present crowd simulation and rendering techniques that take advantage of single GPU machines. Then, using as an example a wandering crowd behavior simulation algorithm, we explain how this kind of algorithms can be extended for their use in GPU cluster environment...