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Yuan Zhao, Xinchang Zhang, Zhen Zhang, Lu Wang, Yueming Hu
Because Cellular Automata (CA) is a dynamic system with inherent parallelism, many studies are focused on mapping CA to the parallel system in order to obtain high performance computing capability, such as using clusters, supercomputers and networks of computers. But the application of these systems are too expensive and difficult to use on the occasions […]
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Xueqin Zhang, Yifeng Zhang, Chunhua Gu
The network anomaly detection technology based on support vector machine (SVM) can efficiently detect unknown attacks or variants of known attacks, however, it cannot be used for detection of large-scale intrusion scenarios due to the demand of computational time. The graphics processing unit (GPU) has the characteristics of multi-threads and powerful parallel processing capability. Based […]
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Jie Guo, Jingui Pan
Monte Carlo based photorealistic image synthesis has proven to be one of the most flexible and powerful rendering techniques, but is plagued with undesirable artifacts known as Monte Carlo noise. We present an adaptive filtering method designed for Monte Carlo rendering systems that counteracts noise while respecting sharp features. The filter operates as a post-process […]
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Lukasz Swierczewski
Modern computers have graphics cards with much higher theoretical efficiency than conventional CPU. The paper presents application possibilities GPU CUDA acceleration for encryption of data using the new architecture tailored to the 3DES algorithm, characterized by increased security compared to the normal DES. The algorithm used in ECB mode (Electronic Codebook), in which 64-bit data […]
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L.F.C.C. Mallens
In recent years, graphics processing units (GPUs) became more and more popular as high performance processing units. Due to the availability of hundreds of cores, code fragments speed up significantly when they are transformed from CPU functions to GPU kernels. The transformation process is non-trivial and therefore error prone. Developing correct and efficient GPU accelerated […]
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Sulan Zhang, Qingsheng Zhu, Ji Liu, Lingqiu Zeng
When L-systems are applied to large and detailed 3D objects, the inherent serial geometric interpretation limits the speed of image generation. To accelerate the interpreting procedure, a Graphic Processing Unit (GPU) based method utilizing Compute Unified Device Architecture (CUDA) is proposed in this paper. The focused approach involves two phases: first is a sequential scan […]
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Heru Suhartanto, Arry Yanuar, Ari Wibisono
One of application that needs high performance computing resources is molecular d ynamic. There is some software available that perform molecular dynamic, one of these is a well known GROMACS. Our previous experiment simulating molecular dynamics of Indonesian grown herbal compounds show sufficient speed up on 32 n odes Cluster computing environment. In order to […]
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F.Pardo, P.Lopez, D. Cabello
Infrared thermography is an attractive technique for non-destructive evaluation processes and particularly for detecting shallowly buried mines. Its use consists of subjecting the area under inspection to a source of natural or artificial heating/cooling process and studying the soil’s response by means of the analysis of its thermal evolution given by a temporal sequence of […]
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Marko J. Misic, Milo V. Tomasevic
Graphics processing units (GPUs) have been increasingly used for general-purpose computation in recent years. The GPU accelerated applications are found in both scientific and commercial domains. Sorting is considered as one of the very important operations in many applications, so its efficient implementation is essential for the overall application performance. This paper represents an effort […]
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Nenad Krpan, Domagoj Jakobovic
This paper describes the parallelization of neural network training algorithms on heterogeneous architectures with graphical processing units (GPU). The algorithms used for training are particle swarm optimization and backpropagation. Parallel versions of both methods are presented and speedup results are given as compared to the sequential version. The efficiency of parallel training is investigated in […]
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Petro Stakhiv, Iryna Strubytska, Yuriy Kozak
Construction of mathematical models for nonlinear dynamical systems using optimization requires significant computation efforts to solve the optimization task. The most CPU time is required by optimization procedure for goal function calculations, which is repeated many times for different model parameters. This allows to use processors with SIMD architecture of calculation parallelization. The effectiveness of […]
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Xiwu Gu, Ruixuan Li, Kunmei Wen, Bei Peng, Weijun Xiao
The task of Chinese word segmentation is to split sequence of Chinese characters into tokens so that the Chinese information can be more easily retrieved by web search engine. Due to the dramatic increase in the amount of Chinese literature in recent years, it becomes a big challenge for web search engines to analyze massive […]
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