Motivation Cellular Automata are used in Natural Science as well as in Social Sciences to simulate various processes. Since simulation of cellular automata is a calculation-intensive task, parallelization is desired and promises to be highly scalable this way due to the high locality of CAs. By comparing the performance of various kinds of cellular automata, some of them more of theoretical, so...

a r t i c l e i n f o a b s t r a c t The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) – a parallel computing architecture – has been developed by NVIDIA to utilize this performance in general purpose computations. Here we show for the first ...

Modern graphics cards for computers, and especially their graphics processing units (gpus), are designed for fast rendering of graphics. In order to achieve this gpus have a parallel architecture which can be exploited for general-purpose computing on graphics processing units (gpgpu) as a complement to the central processing unit (cpu). In this paper gpgpu techniques are used to implement stat...

An approximation for fast digital hologram generation is implemented on a central processing unit (CPU), a graphics processing unit (GPU), and a multi-GPU computational platform. The computational performance of the method on each platform is measured and compared. The computational speed on the GPU platform is much faster than on a CPU, and the algorithm could be further accelerated on a multi...

In many medical imaging modalities, the Fast Fourier Transform (FFT) is being used for the reconstruction of images from acquired raw data. The objective of the paper is to develop FFT and Inverse FT algorithms to run under GPU for performing in much faster way. The GPU based FFT implementation provides much faster reconstruction of Medical images than CPU based implementation. The GPU based al...

Coalition Structure Generation—the problem of finding the optimal division of agents into coalitions—has received considerable attention in recent AI literature. The fastest exact algorithm to solve this problem is IDP-IP [17], which is a hybrid of two previous algorithms, namely IDP and IP. Given this, it is desirable to speed up IDP as this will, in turn, improve upon the state-of-the-art. In...

Band selection is a common technique to reduce the dimensionality of hyperspectral imagery. When the desired object information is known, the reduction process can be achieved by selecting the bands that contain the most object information. It is expected that these selected bands can offer an overall satisfactory detection and classification performance. In this paper, we propose a new particl...

Laser speckle imaging (LSI) is a technique in which coherent light incident on a surface produces a reflected speckle pattern that is related to the underlying movement of optical scatterers, such as red blood cells, indicating blood flow. Image-processing algorithms can be applied to produce speckle flow index (SFI) maps of relative blood flow. We present a novel algorithm that employs the NVI...

Latent Semantic Indexing (LSA) aims to reduce the dimensions of large Term-Document datasets using Singular Value Decomposition. However, with the ever expanding size of data sets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. The Graphics Processing Unit (GPU) can solve some highly parallel problems much faster than the traditional sequ...

Graphics Processing Units (GPUs) are more and more used for general purpose calculations. In the area of modeling and simulation, GPU’s calculations are typically associated with executing specific simulation models. Besides this application, we propose the use of GPUs not only in the context of model execution but also to analyze simulation results, e.g., to compute the similarity of simulatio...