We present a parallel algorithm to solve the Gaussian elimination with complete or partial pivoting problem, based on the corresponding sequential algorithm, on SIMD hypercube computers with distributed memory. This p...
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We present a parallel algorithm to solve the Gaussian elimination with complete or partial pivoting problem, based on the corresponding sequential algorithm, on SIMD hypercube computers with distributed memory. This parallel algorithm is general in the sense that it allows for arbitrary dimensions for the matrix and the hypercube. The flexibility of this algorithm is rooted in the partition of the dimensions of the hypercube into two subsets, each one associated with one dimension of the matrix. The data are distributed in the local memories with a cyclic storage scheme. The performance of a parallel algorithm based on Gaussian elimination is bounded by data dependences.
Most special architectures for image processing handle image-based (iconic) transformations efficiently but are relatively inefficient for transforming images into more symbolic representations such as lists of promin...
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Most special architectures for image processing handle image-based (iconic) transformations efficiently but are relatively inefficient for transforming images into more symbolic representations such as lists of prominent lines, contour-description strings, or graphs that express the major spatial relationships in the image. Consequently some new architectures have been proposed to improve such operations. Here a representative sample of such architectures is presented in order to elucidate the relevant design ❉s. algorithms for these architectures are described and compared. Some new algorithms for iconic-to-symbolic transformations on pipelined systems are presented.
Concurrent multiprocessing algorithms are presented for the calculation of orthonormal bases employed in the nullspace and range space methods for simulating the dynamics of multibody systems. It is shown that highly ...
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We present a parallel algorithm for performing multidimensional fast Hartley transforms (FHTs) on hypercube SIMD computers with unshared local memory. The flexibility of the algorithm derives from the partition of the...
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We present a parallel algorithm for performing multidimensional fast Hartley transforms (FHTs) on hypercube SIMD computers with unshared local memory. The flexibility of the algorithm derives from the partition of the dimensions of the hypercube in subsets associated with each of the dimensions of the transform, the pure binary processor indexing, and the consecutive distribution of data in the processors' local memory, which facilitates the parallel performance of unidimensional FHTs. The complexity of the algorithm and the associated data redundancy are analyzed.
This paper describes a parallel algorithm for the LU decomposition of band matrices using Gaussian elimination. The matrix dimension is n × n with 2r?1 diagonals. In the case when 1 ? r ? 2 p an optimal number of...
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This paper describes a parallel algorithm for the LU decomposition of band matrices using Gaussian elimination. The matrix dimension is n × n with 2r?1 diagonals. In the case when 1 ? r ? 2 p an optimal number of the processors, , is determined according to the equation . When 2 p ? r ? n a number of processors, p, statged by Veldhorst is adopted (see [7]). For band matrix with 2r-1 diagonals (1 ? r ? 2p) the task scheduling procedure with the aim to obtain maximal parallelism in system operation, i.e. good load balancing, is defined. The architecture of the system is of MIMD type. The connection between the processors is realised via a common bus. Communication and synchronization is performed by message passing technique.
In this paper the best heuristic methods known up to now are compared to solve the flow shop sequencing problem and we improve the complexity of the best one. Next, this problem is applied to taboo search, a new techn...
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In this paper the best heuristic methods known up to now are compared to solve the flow shop sequencing problem and we improve the complexity of the best one. Next, this problem is applied to taboo search, a new technique to solve combinatorial optimization problems, and computational experiments are reported. Finally a parallel taboo search algorithm is presented and experimental results show that this heuristic allows very good speed-up. [ABSTRACT FROM AUTHOR]
parallel iterative methods are studied, and the focus is on linear algebraic systems whose matrix is symmetric and positive definite. The set of unknowns may be viewed as a union of subsets of unknowns (possibly with ...
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parallel iterative methods are studied, and the focus is on linear algebraic systems whose matrix is symmetric and positive definite. The set of unknowns may be viewed as a union of subsets of unknowns (possibly with overlap). The parallel iteration matrix is then formed by a weighted sum of iteration matrices that are associated with splittings of the matrix corresponding to the blocks. When the blocks are from a matrix in dissection form, it can be shown under suitable conditions that the parallel algorithm is convergent. When the multisplitting version of successive over-relaxation (SOR) is used, the SOR parameter is required to be less than ω0
We describe a cost-optimal parallel algorithm for enumerating all partitions (equivalence relations) of the set {1, ...,n}, in lexicographic order. The algorithm is designed to be executed on a linear array of process...
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We describe a cost-optimal parallel algorithm for enumerating all partitions (equivalence relations) of the set {1, ...,n}, in lexicographic order. The algorithm is designed to be executed on a linear array of processors. It usesn processors, each having constant size memory and each being responsible for producing one element of a given set partition. Set partitions are generated with constant delay leading to anO(B n) time solution, whereB n is the total number of set partitions. The same method can be generalized to enumerate some other combinatorial objects such as variations. The algorithm can be made adaptive, i.e. to run on any prespecified number of processors. To illustrate the model of parallel computation, a simple case of enumerating subsets of the set {1, ...,n}, having at mostm (≤n) elements is also described.
algorithms based on a divide-and-conquer strategy are well qualified for being implemented in a multitasking environment. The idea of the divide-and-conquer paradigm is to fragment a problem into subproblems of the sa...
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Three parallel algorithms, based on existing sequential methods for vibration analysis, were developed and evaluated for the solution of three example problems on a parallel computer. The three methods–Lanczos, multi...
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