We present an algorithm for parallel solving of nonlinear systems in a real time environment. The current implementation uses Real Time Linux (RTLinux) and is independent on the numerical method used for solving the s...
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ISBN:
(纸本)1892512459
We present an algorithm for parallel solving of nonlinear systems in a real time environment. The current implementation uses Real Time Linux (RTLinux) and is independent on the numerical method used for solving the system. Experimental tests show that the algorithm is up to ten times faster than the same parallel algorithm run in a normal environment.
The processing of three-dimensional (3-D) objects from 3-D digital image data is an important task in the image processing and the computer vision fields. The distance transform (DT) is extensively applied in the imag...
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ISBN:
(纸本)0780378407
The processing of three-dimensional (3-D) objects from 3-D digital image data is an important task in the image processing and the computer vision fields. The distance transform (DT) is extensively applied in the image processing and computer vision areas as a key operation. In a two or three-dimensional image array, the computation of distance transform (DT) is an important task, With the increasing application of 3D voxel images, it is useful to consider the distance transform of a 3D digital image array. In order to provide the efficient transform computations, parallelism is employed. We develop parallel algorithms for the three-dimensional Euclidean distance transform (3D-EDT) on the SIMD hypercube computer. The time complexity of our parallel algorithm is O{log(2) N} for an N x N x N image array using N-3 processors. A generalized parallel algorithm for the 3D-EDT is also proposed and it runs O((N/p)(3) log(N) + (N/p)(2) log(2) p) time for an N x N x N binary image array on the SIMD hypercube computer using p(3) PE's, where 1 less than or equal to p less than or equal to N.
In discrete optimization, most exact solution approaches are based on branch and bound, which is conceptually easy to parallelize in its simplest forms. More sophisticated variants, such as the so-called branch, cut, ...
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In discrete optimization, most exact solution approaches are based on branch and bound, which is conceptually easy to parallelize in its simplest forms. More sophisticated variants, such as the so-called branch, cut, and price algorithms, are more difficult to parallelize because of the need to share large amounts of knowledge discovered during the search process. In the first part of the paper, we survey the issues involved in parallelizing such algorithms. We then review the implementation of SYMPHONY and COIN/BCP, two existing frameworks for implementing parallel branch, cut, and price. These frameworks have limited scalability, but are effective on small numbers of processors. Finally, we briefly describe our next-generation framework, which improves scalability and further abstracts many of the notions inherent in parallel BCP, making it possible to implement and parallelize more general classes of algorithms.
parallel merge sort is useful for sorting a large quantity of data progressively. The merge sort should be parallelized carefully since the conventional algorithm has poor performance due to the successive reduction o...
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parallel merge sort is useful for sorting a large quantity of data progressively. The merge sort should be parallelized carefully since the conventional algorithm has poor performance due to the successive reduction of the number of participating processors by half, and down to one in the last merging stage. The proposed load-balanced merge sort utilizes all processors throughout the computation. It evenly distributes data to all processors in each stage. Thus every processor is forced to work in all phases. Significant performance enhancement has been achieved up to a speedup of (P - 1)/log P where P is the number of processors. Experimental results demonstrate a speedup of 9.6 (upper bound of 10.7) on 32-processor Cray T3E when sorting 4M 32-bit integers, and a speed up of 2.3 (upper bound of 2.8) on an 8-node PC cluster.
Algebraic Reconstruction Technique (ART) is a method for reconstructing images from projections. It is widely used in applications such as Computed Tomography (CT). The algorithm requires fewer views, and hence less r...
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ISBN:
(纸本)1892512459
Algebraic Reconstruction Technique (ART) is a method for reconstructing images from projections. It is widely used in applications such as Computed Tomography (CT). The algorithm requires fewer views, and hence less radiation, to produce a satisfactory image. However,, the approach is not widely used due to the computational intensive nature of the problem. In this paper we design and develop a parallel ART (PART) algorithm and study its performance on a network of workstations using the Message Passing Interface(MPI).
A new mathematical morphology-based algorithm is proposed to achieve automatic center location of non-eye typhoon. The center of a non-eye typhoon is near the geometric center of the cloud system and has higher temper...
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ISBN:
(纸本)0780378407
A new mathematical morphology-based algorithm is proposed to achieve automatic center location of non-eye typhoon. The center of a non-eye typhoon is near the geometric center of the cloud system and has higher temperature. For each infrared satellite cloud image, the locating procedures are as follows: a) noises filtering, b) main cloud systems segmenting, c) center locating and d) multispectral image verification. The algorithms are based on operations of mathematical morphology, and designed in IBM SP2 massively parallel computer. The experiment results show that the algorithm locates the centers of most non-eye typhoons successfully and achieves faster, more precise and non-human interactive non-eye typhoon center positioning.
This article scrutinizes anomalies in accuracy studies by Brook et al. (Int J Quantum Chem 2001, 85, 263-271) for a moving free particle. These studies were carried out in the framework of the quantum trajectory metho...
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This article scrutinizes anomalies in accuracy studies by Brook et al. (Int J Quantum Chem 2001, 85, 263-271) for a moving free particle. These studies were carried out in the framework of the quantum trajectory method developed from Bohm's hydrodynamic formalism. These accuracy studies exhibited a strange behavior of the relative error in the probability density that apparently contradicts the quantum fluid dynamic formalism. It is found that improper initialization of the pseudoparticle velocities is responsible for the observed anomalies. This article presents a method for appropriate initialization of the pseudoparticle velocities. It also evaluates the accuracy of this method by reinvestigating accuracy studies by Brook et al. for a moving free particle. (C) 2003 Wiley Periodicals, Inc.
The main contributions of this paper are in designing fast and scalable parallel algorithms for selection and median filtering. Based on the radix-omega representation of data and the prune-and-search approach, we fir...
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The main contributions of this paper are in designing fast and scalable parallel algorithms for selection and median filtering. Based on the radix-omega representation of data and the prune-and-search approach, we first design a fast and scalable selection algorithm on the arrays with reconfigurable optical buses (AROB). To the authors' knowledge, this is the most time efficient algorithm yet published, especially compared to the algorithms proposed by Han et al. [8] and Pan [16]. Then, given an N x N image and a W x W window, based on the proposed selection algorithm, several scalable median filtering algorithms are developed on the AROB model with a various number of processors. In the sense of the product of time and the number of processors used, most of the proposed algorithms are time or cost optimal.
We discuss the nonstationary multisplittings and two-stage multisplittings to solve the linear systems of algebraic equations Ax = b when the coefficient matrix is a non-Hermitian positive definite matrix, and establi...
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We discuss the nonstationary multisplittings and two-stage multisplittings to solve the linear systems of algebraic equations Ax = b when the coefficient matrix is a non-Hermitian positive definite matrix, and establish the convergence theories with general weighting matrices. This not only eliminates the restrictive condition that it is usually assumed for scalar weighting matrices, but also generalizes it to a general positive definite matrix. (C) 2003 Elsevier Science Ltd. All rights reserved.
Particle filtering may cope with non-linear and/or non-Gaussian models. As a counterpart, this technique suffers from an heavy computation cost. and cannot always satisfy the real time constraints of applications. A d...
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Particle filtering may cope with non-linear and/or non-Gaussian models. As a counterpart, this technique suffers from an heavy computation cost. and cannot always satisfy the real time constraints of applications. A data parallel algorithm is proposed to achieve real-time particle filtering. Extensive results are presented in the passive SONAR tracking context for maneuvering targets. (C) 2003 Elsevier B.V. All rights reserved.
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