Accurate and faster computation of the Fast Fourier Transform (FFT) using parallel computing is the result of a novel algorithm called FFTpc described in this paper. As opposed to the Cooley-Tukey FFT, the FFTpc uses ...
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ISBN:
(纸本)9798350332865
Accurate and faster computation of the Fast Fourier Transform (FFT) using parallel computing is the result of a novel algorithm called FFTpc described in this paper. As opposed to the Cooley-Tukey FFT, the FFTpc uses only real-valued operations until the very last step. Filtering in parallel in the frequency domain is done on data subsets that are processed simultaneously with no data interchange between processors through the main parts of the filtering process. In addition, if the user only requires the magnitude of the transform, the algorithm involves no complex-valued operations at all. Many other novel aspects of the FFTpc and both estimated and actual speedups are reported.
In the present paper, an efficient method for parallel solving the time-consuming multicriterial optimization problems, where the optimality criteria can be multiextremal, and the computation of the criteria values ca...
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ISBN:
(纸本)9783319629322;9783319629315
In the present paper, an efficient method for parallel solving the time-consuming multicriterial optimization problems, where the optimality criteria can be multiextremal, and the computation of the criteria values can require a large amount of computations, is proposed. The proposed scheme of parallel computations allows obtaining several efficient decisions of a multicriterial problem. During performing the computations, the maximum use of the search information is provided. The results of the numerical experiments have demonstrated such an approach to allow reducing the computational costs of solving the multicriterial optimization problems essentially - several tens and hundred times.
As parallelism on different levels becomes ubiquitous in todays computers, it seems worthwhile to provide a review of the wealth of every aspect of parallel computing that has evolved over the last decades. We refrain...
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ISBN:
(纸本)9781538655009
As parallelism on different levels becomes ubiquitous in todays computers, it seems worthwhile to provide a review of the wealth of every aspect of parallel computing that has evolved over the last decades. We refrain from a comprehensive survey and concentrate on parallel programming patterns, design for parallel program, parallel programming models, parallel programming languages, design of parallel algorithms, together with a perspective of parallel computing. Besides presenting the patterns, models, design frameworks, we also refer to languages, implementation, and tools.
In this paper, we address the problem of accelerating inversion algorithms for nonlinear acoustic tomographic imaging by parallel computing on graphics processing units (GPUs). Nonlinear inversion algorithms for tomog...
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ISBN:
(纸本)9781510601116
In this paper, we address the problem of accelerating inversion algorithms for nonlinear acoustic tomographic imaging by parallel computing on graphics processing units (GPUs). Nonlinear inversion algorithms for tomographic imaging often rely on iterative algorithms for solving an inverse problem, thus computationally intensive. We study the simultaneous iterative reconstruction technique (SIRT) for the multiple-input-multiple-output (MIMO) tomography algorithm which enables parallel computations of the grid points as well as the parallel execution of multiple source excitation. Using graphics processing units (GPUs) and the Compute Unified Device Architecture (CUDA) programming model an overall improvement of 26.33x was achieved when combining both approaches compared with sequential algorithms. Furthermore we propose an adaptive iterative relaxation factor and the use of non-uniform weights to improve the overall convergence of the algorithm. Using these techniques, fast computations can be performed in parallel without the loss of image quality during the reconstruction process.
Image inpainting refers to image restoration process that reconstruct damaged image to obtain it lost information based on existing information. PDE-based approach is commonly used for image interpolation especially i...
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ISBN:
(纸本)9781538647394
Image inpainting refers to image restoration process that reconstruct damaged image to obtain it lost information based on existing information. PDE-based approach is commonly used for image interpolation especially inpainting. Since PDE process express convolution and continuous change, the approach may take a lot of computational resources and will run slow on standard computer CPU. To overcome that, GPU parallel computing method for PDE-based image inpainting are proposed. These days, some handy platform or frameworks to utilize GPU are already exist like CUDA, Theano, and Tensorflow. CUDA is well-known as parallel computing platform and programming model to work with programming language such as C/C++. In other hand Theano and Tensorflow is a bit different thing, both of them is a machine learning framework based on Python that also able to utilize GPU. Although Theano and Tensorflow are specialized for machine learning and deep learning, the system is general enough to applied for computational process like image inpainting. The results of this work show benchmark performance of PDE image inpainting running on CPU using C++, Theano, and Tensorflow and on GPU with CUDA, Theano, and Tensorflow. The benchmark shows that parallel computing accelerated PDE image inpainting can run faster on GPU either with CUDA, Theano, or Tensorflow compared to PDE image inpainting running on CPU.
K-nearest neighbor (KNN) query algorithm based on road network plays an important role in location based service, which had been widely used in intelligent transportation, roadside assistance and other fields. However...
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K-nearest neighbor (KNN) query algorithm based on road network plays an important role in location based service, which had been widely used in intelligent transportation, roadside assistance and other fields. However, as road network density increases and the number of points of interest increases, query efficiency decreases *** order to improve the query efficiency, we adopted the MapReduce parallel computing framework to complete the query of K neighbor moving objects by designing Map, Reduce, Combiner and other functions. Before the start of the query, the road network was divided into pieces, and each fragment was calculated. The fmal K-nearest neighbor moving objects were obtained by aggregating the calculated results of each slice to realize the parallel optimization of KNN algorithm based on road network. The experimental results showed that the performance of parallel KNN algorithm based on MapReduce was better than that of serial KNN query algorithm in large-scale road network environment and the larger K value of query request. (C) 2019 The Authors. Published by Elsevier B.V.
The potential of parallel processing architecture is evaluated for power oscillation monitoring. In the emerging smart grid architecture using Wide Area Monitoring System (WAMS), data collected from Phasor Measurement...
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ISBN:
(纸本)9781424468904
The potential of parallel processing architecture is evaluated for power oscillation monitoring. In the emerging smart grid architecture using Wide Area Monitoring System (WAMS), data collected from Phasor Measurement Units (PMU) in remote locations are transmitted in real-time to the control center. The power system network oscillatory dynamic behavior can then be extracted online using modern signal processing techniques. In this paper an Extended Complex Kalman Filter (ECKF) algorithm is adopted for tracking oscillations. A brief overview of this method along with background of WAMS is presented. Later, parallelism is achieved by decomposing ECKF method into a set of subroutines and distributing them across multiple CPU cores. Comparisons of this performance with a conventional sequential structure is conducted using synthetic signals in MATLAB and Visual C++. The simulation results show that parallel processing is able to reduce the computing time.
Complex emergency resource scheduling schemes are essential to improve the quality and efficiency of processes and software services. Despite the effort of many researchers in this direction, there are not yet mechani...
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ISBN:
(纸本)9781479920020
Complex emergency resource scheduling schemes are essential to improve the quality and efficiency of processes and software services. Despite the effort of many researchers in this direction, there are not yet mechanisms that facilitate collaborative development of resource scheduling decision-making in complex emergency systems. In order to treat these issues, analytic hierarchy process (AHP) is introduced to handle multi-objective decision-making in emergency systems. In the process of collaboration, partition algorithm (PA) is proposed to divide rescue points into different sets. Experimental results have shown the proposed parallel computing method has significantly improved the computational efficiency of emergency resource scheduling schemes.
The fast Fourier transform (FFT) is a speed-up technique for calculating the discrete Fourier transform (DFT), which in turn is a discrete version of the continuous Fourier transform. The Fast Fourier Transform is use...
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ISBN:
(纸本)9781479941698
The fast Fourier transform (FFT) is a speed-up technique for calculating the discrete Fourier transform (DFT), which in turn is a discrete version of the continuous Fourier transform. The Fast Fourier Transform is used in linear systems analysis, antenna studies, optics, random process modeling, probability theory, quantum physics, and boundary-value problems, and has been very successfully applied to restoration of astronomical data. This paper formulates the one dimensional and two dimensional continuous and discrete Fourier transform, especially the fast Fourier transform, considers their parallel algorithms and reports the speed up of parallel computing in both shared memory and distributed memory modes.
With the rise and extensive usage of Bitcoin, a peer-to-peer electronic cash system beginning at 2008, the number of transactions is growing. In order to analyze the activity in this currency system, we present a para...
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ISBN:
(纸本)9780769551258
With the rise and extensive usage of Bitcoin, a peer-to-peer electronic cash system beginning at 2008, the number of transactions is growing. In order to analyze the activity in this currency system, we present a parallel analysis approach for meeting the need of building the transaction graph of this financial system. In order to test the performance and the realistic possibility of our approach, we implemented our approach and conducted some comparing to test the performance of our system. Through the experiment, we confirmed that this method is highly efficient and reliable compared with the traditional method.
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