3 edition of Applications and accuracy of the parallel diagonal dominant algorithm found in the catalog.
Applications and accuracy of the parallel diagonal dominant algorithm
by National Aeronautics and Space Administration, Langley Research Center, National Technical Information Service, distributor in Hampton, Va, [Springfield, Va
Written in English
|Series||ICASE report -- no. 93-6., NASA contractor report -- 191431., NASA contractor report -- NASA CR-191431.|
|Contributions||Langley Research Center.|
|The Physical Object|
[Published as Parallel Computing 21 ()] Abstract. A new algorithm is presented, designed to solve tridiagonal matrix problems efficiently with parallel computers (multiple instruction stream, multiple data stream (MIMD) machines with distributed memory). The algorithm is designed to be extendable to higher order banded diagonal systems. Sorting Applications. Sorting algorithms and priority queues are widely used in a broad variety of applications. Our purpose in this section is to briefly survey some of these applications. Sorting various types of data. Our implementations sort arrays of Comparable objects.
Parallel Algorithms Guy E. Blelloch and Bruce M. Maggs School of Computer Science Carnegie Mellon University Forbes Avenue Pittsburgh, PA [email protected], [email protected] Introduction The subject of this chapter is the design and analysis of parallel algorithms. Most of today’sFile Size: KB. Diethelm () performed parallel computation on the second order Adams–Bashforth–Moulton method of fractional derivatives, and discussed the accuracy of the parallel algorithm. Wang et al. () [ 31 ] constructed an improved conjugate gradient squared (CGS) method by decomposing a two-dimensional spatial fractional difference matrix Author: Xiaozhong Yang, Xu Dang.
A drawback of classical ILU algorithms is the sequential nature, which prohibits good performance on massively parallel hardware such as GPUs. ViennaCL provides an implementation of the recently proposed parallel ILU factorization algorithm proposed by Chow and Patel. While the authors propose an asynchronous algorithm, we use a synchronous. tridiagonal eigenvalue problem. We present an implementation of the MRRR algorithm on a data-parallel coprocessor using the CUDA pro-gramming environment. We obtain up to fold speedups over LA-PACK’s MRRR implementation and demonstrate that the algorithm can be mapped efﬁciently onto a data-parallel architecture. The accuracy ofFile Size: KB.
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PARALLEL COMPUTING ELSEVIER Parallel Computing 21 () Application and accuracy of the parallel diagonal dominant algorithm * Xian-HeSun * Department of Computer Science, Louisiana State University, Baton Rouge, LAUSA Received 21 May ; revised 1 April27 January Abstract The Parallel Diagonal Dominant (PDD) algorithm is an Cited by: Applications and Accuracy of the Parallel Diagonal Dominant Algorithm * Xian-He Sun ICASE Mail Stop C NASA Langley Research Center Hampton, VA ()[email protected] ABSTRACT The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiago-hal Size: KB.
Get this from a library. Applications and accuracy of the parallel diagonal dominant algorithm. [Xian-He Sun; Langley Research Center.]. CiteSeerX — Application and Accuracy of the Parallel Diagonal Dominant Algorithm CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The Parallel Diagonal Dominant (PDD) algorithm is an efficient tridiagonal solver.
In this paper, a detailed study of the PDD algorithm. PDD: Parallel Diagonal Dominant Algorithm When A is diagonal dominant, the most interesting mathematical properties is that the off diagonal coefficients of the matrix 1A V ~ − have an exponentially decay to 0. Therefore, the coefficients of (), (0 1) 0 () −1 v w i p i i m can be dropped within machine accuracy when p.
PDD: Parallel Diagonal Dominant Algorithm When A is diagonal dominant, an interesting mathematical property is that the off diagonal coefficients of the matrix AeðiÞV decay to 0 exponentially with the order of the matrix.
Therefore, the coefficients can be dropped within machine accuracy when p. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): A new method, namely the Parallel Two-Level Hybrid (PTH) method, is developed to solve tridiagonal systems on parallel computers.
PTH is designed based on Parallel Diagonal Dominant (PDD) algorithm. Like PDD, PTH is highly scalable. It provides accurate solutions when PDD may not be applicable and maintains a near. In this paper we will derive a new algorithm for solving symmetric pentadiagonal Toeplitz systems of linear equations based upon a technique used in [J.M.
McNally, L.E. Garey, R.E. Shaw, A split-correct parallel algorithm for solving tri-diagonal symmetric Toeplitz systems, Int.
Comput. Math. 75 () –] for tridiagonal Toeplitz Cited by: Parallel Programming and Parallel Algorithms INTRODUCTION Algorithms in which operations must be executed step by step are called serial or sequential algorithms.
Algorithms in which several operations may be executed simultaneously are referred to as parallel Size: KB. A Probing Method for Computing the Diagonal of the Matrix Inverse s with the rise of parallel processing, see, e.g., .
In the general case, it is known to converge when A high accuracy of the solution can only be obtained if a suﬃciently large number of vectors is taken, so the method can be expensive for the situation when a.
Parallel Algorithms and Parallel Architectures 13 Relating Parallel Algorithm and Parallel Architecture 14 Implementation of Algorithms: A Two-Sided Problem 14 Measuring Beneﬁ ts of Parallel Computing 15 Amdahl’s Law for Multiprocessor Systems 19 Gustafson–Barsis’s Law 21 Applications of Parallel Computing 22File Size: 8MB.
() Application and accuracy of the parallel diagonal dominant algorithm. Parallel Computing() A scalable eigenvalue solver for symmetric tridiagonal by: •band matrix, if a ij =0foronlyi − m l ≤ j ≤ i + m k,wherem l and m k are two natural numbers; the numberm l +m k +1 is called bandwidth of the matrix A • upper Hessenberg matrix, if a ij =0fori, j such that i>j+1; accordingly we deﬁne lower Hessenberg matrix • permutation matrix, if the columns of a matrix A are permutations of the columns of the identity matrix E (every row File Size: KB.
In this paper, we present a demonstrably fast, parallel, exact algorithm for the maximum clique problem. The presentation includes the design, implementation, analysis, and performance evaluation of the algorithm.
Further, enabled by its eﬃ-ciency, we use the clique ﬁnder to achieve three goals: (i) study maximum cliques. Parallel Algorithms and Applications Volume 6, NumberFrancisco Almeida and Felix García and Daniel Gonzalez and Casiano Rodríguez A Parallel Algorithm for the Integer Knapsack Problem for Pipeline Networks Reid Baldwin and Moon Jung Chung and Yunmo Chung Overlapping Window Algorithm for Computing GVT in Time Warp.
The parallel homotopy algorithm for finding few or all eigenvalues of a symmetric tridiagonal matrix is presented. The computations were executed on an NCUBE, a distributed memory multiprocessor.
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implementation and performance of the time integration of a 3d numerical transport model int j numer meth fl (4) aug 30 Approximate Incomplete Cyclic Reduction for Systems Which Are Tridiagonal and Strictly Diagonally Dominant by Rows. Authors; Sun, X.H.: Application and accuracy of the parallel diagonal dominant algorithm.
Parallel Comput – () Cited by: 1. An efficient parallel algorithm with application to computational fluid dynamics Article in Computers & Mathematics with Applications 45(1) January with 9 Reads How we measure 'reads'. In McNally [Fast parallel algorithms for tri-diagonal symmetric Toeplitz systems, MCS Thesis, University of New Brunswick, Saint John, ], an m processor Split & Correct algorithm.
Where are the parallel algorithms? by ROBERT G. VOIGT Institute for Computer Applications in Science and Engineering Hampton, Virginia ABSTRACT Four paradigms that can be useful in developing parallel algorithms are computa tional complexity analysis, changing the order of computation, asynchronous computation, and divide and conquer.The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiagonal solver.
Applications and Accuracy of the Parallel Diagonal Dominant Algorithm [Xian-He Sun] on *FREE* shipping on qualifying offers. Parallel Thomas Algorithm, High-order Formulas, Compact Schemes.Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest.
This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject s: 1.