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The recent development in sensor technology shows the unprecedented growth of Remote Sensing (RS) data archives-Big Data. However, this growth in RS archives has resulted in many processing challenges. The three V's of big data- Volume, Velocity and Variety is highly relevant in situations such as flood, earthquake disaster, where real/near real time processing of data from different RS data sources...
In the current work the authors present several approaches to the high performance simulation of human diseases propagation using hybrid two-component imitational models. The models under study were created by coupling compartmental and discrete-event submodels. The former is responsible for the simulation of the demographic processes in a population while the latter deals with a disease progression...
It has become increasingly common to see that supercomputing applications harness the massive parallelism of graphics cards to speed up computations. In this study, an analysis concerning to the time necessity for four different implementations of parallel matrix multiplication is presented. The execution time of parallel matrix multiplications in Compute Unified Device Architecture (CUDA) can be...
Detailed mechanism of optical illusion caused by visual neurons in human brain has not been well understood, and its numerical simulation is helpful to analyze visual system of humans. This paper describes implementation techniques of parallel numerical simulation to help understanding optical illusion by using a GPU-accelerated PC cluster. Our parallel acceleration techniques include following three...
We present a software package that supports teaching different parallel programming models in a computational science and engineering context. It implements a Finite Volume solver for the shallow water equations, with application to tsunami simulation in mind. The numerical model is kept simple, using patches of Cartesian grids as computational domain, which can be connected via ghost layers. The...
Numerical simulation for visual processing of the human brain is one of time-consuming applications. This paper shows acceleration techniques for a simulation program of the visual processing. We parallelize convolution calculations, which are core operations, which the simulation program requests, on a GPU-accelerated PC cluster. Our implementation includes three improvement points. Firstly, we consider...
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