3 edition of **A parallel solution for the symmetric eigenproblem** found in the catalog.

A parallel solution for the symmetric eigenproblem

Gaylen A. Thurston

- 6 Want to read
- 8 Currently reading

Published
**1987**
by National Aeronautics and Space Administration, Langley Research Center, For sale by the National Technical Information Service in Hampton, Va, [Springfield, Va
.

Written in English

- Algorithms.,
- Eigenvalues.

**Edition Notes**

Statement | Gaylen A. Thurston. |

Series | NASA technical memorandum -- 89082. |

Contributions | Langley Research Center. |

The Physical Object | |
---|---|

Format | Microform |

Pagination | 1 v. |

ID Numbers | |

Open Library | OL15282527M |

Complex eigenproblem solution by a parallel norm-reducing Jacobi method. Megson, G.M. Complex eigenproblem solution by a parallel norm-reducing Jacobi method. Journal of Computer Systems Science and Engineering. 5 (3), pp. Author: G. M. Megson. Journal of Parallel and Distributed Computing, 14, pp. , Fast computation of eigenvalue decompositions on vector architectures, Advances in Optimization and Parallel Computing, pp. , North-Holland, (with A.A. Anda) A parallel algorithm for the unbalanced orthogonal Procrustes problem, Parallel Computing, 17, pp.

Parallel Techniques and Algorithms. Parallel Sorting Algorithms. Solution of a System of Linear Algebraic Equations. The Symmetric Eigenvalue Problem: Jacobi's Method. QR Factorization. Singular Value Decomposition and Related Problems. J. Ortega (). Introduction to Parallel and Vector Solution of Linear Systems, Plenum Press, New York. Vector and Parallel Processing - VECPAR'98 Third International Conference Porto, Portugal, June , Selected Papers and Invited Talks Multi-sweep Algorithms for the Symmetric Eigenproblem. Pages Vector and Parallel Processing - VECPAR'98 Book Subtitle Third International Conference Porto, Portugal, June ,

Lanczos versus subspace iteration for solution of eigenvalue problems. Bahram Nour‐Omid. University of California, Berkeley, California, U.S.A. Parallel Computing, 20, 8, (), , The Lanczos algorithm for the generalized symmetric eigenproblem on shared-memory architectures, Applied Numerical Mathematics, 12, 5. The most significant new routines and functions include: 1) a faster singular value decomposition computed by divide-and-conquer 2) faster routines for solving rank-deficient least squares problems: using QR with column pivoting using the SVD based on divide-and-conquer 3) new routines for the generalized symmetric eigenproblem: faster routines.

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@article{osti_, title = {Parallel solution of the symmetric tridiagonal eigenproblem}, author = {Jessup, E.R.}, abstractNote = {This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed memory MIMD multiprocessor.

Only those techniques having the potential for both. COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus.

@article{osti_, title = {Parallel solution of the symmetric tridiagonal eigenproblem. Research report}, author = {Jessup, E.R.}, abstractNote = {This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed-memory Multiple Instruction, Multiple Data multiprocessor.

In this paper we present a parallel algorithm for the symmetric algebraic eigenvalue problem. The algorithm is based upon a divide and conquer scheme suggested by Cuppen for computing the eigensystem of a symmetric tridiagonal matrix. We extend this idea to obtain a parallel algorithm that retains a number of active parallel processes that is greater than or equal to the initial number Cited by: 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. SIAM Journal on Matrix Analysis and ApplicationsAbstract | PDF ( KB) () A Stable and Efficient Algorithm for the Rank-One Modification of the Symmetric by: We present a new parallel solution for the dense symmetric eigenvalue/eigenvector problem that is based upon the tridiagonal eigensolver, Algorithm MR, recently developed by Dhillon & Parlett.

[8] C. HENDRICKSON, E. JESSUP, AND C. SMITH, A parallel eigensolver for dense sym- metric matrices. Submitted for publication. [9] E. JESSUP, Parallel Solution of the Symmetric Tridiagonal Eigenproblem, PhD thesis, Dept of Computer Science, Yale University, Author: E.R. Jessup.

Abstract. An efficient parallel algorithm, which we dubbed farm-zeroinNR, for the eigenvalue problem of a symmetric tridiagonal matrix has been implemented in a distributed memory multiprocessor with nodes [].The basis of our parallel implementation is an improved version of the zeroinNR method [].It is consistently faster than simple bisection and produces more accurate eigenvalues than Author: Maria Antónia Forjaz, Rui Ralha.

Stuart, E. J., and J. Weston, An Algorithm for the Parallel Computation of Subsets of Eigenvalues and Associated Eigenvectors of Large Symmetric Matrices using an Array Processor, in Proceedings Euromicro Workshop on Parallel and Distributed Processing, 27–29 January,Milligan, P., and A.

Nunez (Eds.), IEEE Computer Society Press Cited by: 3. 1) then v is an eigenvector of the linear transformation A and the scale factor λ is the eigenvalue corresponding to that eigenvector. Equation (1) is the eigenvalue equation for the matrix A. Equation (1) can be stated equivalently as (A − λ I) v = 0, {\displaystyle (A-\lambda I)v=0,} (2) where I is the n by n identity matrix and 0 is the zero vector.

Eigenvalues and the characteristic. A parallel solution for the symmetric eigenproblem [microform] / Gaylen A. Thurston Separation analysis, a tool for analyzing multigrid algorithms [microform] / Sorin Costiner, Shlomo Ta'asan A real norm reducing Jacobi type eigenvalue algorithm / R.

Sacks-Davis. A Coarse-Grain Parallel Implementation of the Block Tridiagonal Divide and Conquer Algorithm In the book Matrix Computations [6], Golub and Van Loan state that the symmetric eigen- Cuppen’s divide-and-conquer algorithm for the tridiagonal symmetric eigenproblem [3]. Gallopoulos E and Saad Y On the parallel solution of parabolic equations Proceedings of the 3rd international conference on Supercomputing, () Li T and Rhee N () Homotopy algorithm for symmetric eigenvalue problems, Numerische Mathematik.

On MR3-type Algorithms for the Tridiagonal Symmetric Eigenproblem and the Bidiagonal SVD as student attending a lab on parallel programming with Java he gave in the summer of During later collaboration in the form of student jobs, symmetric eigenproblem that will be referred to later.

The most significant new routines and functions include: 1. a faster singular value decomposition computed by divide-and-conquer 2. faster routines for solving rank-deficient least squares problems: Using QR with column pivoting using the SVD based on divide-and-conquer 3.

new routines for the generalized symmetric eigenproblem: faster routines. Vidal A, Garcia V, Alonso P and Bernabeu M () Parallel computation of the eigenvalues of symmetric Toeplitz matrices through iterative methods, Journal of Parallel and Distributed Computing,(), Online publication date: 1-Aug The development of efficient, general-purpose software for the iterative solution of sparse linear systems on parallel MIMD computers depends on recent results from a wide variety of research areas.

Parallel graph heuristics, convergence analysis, and basic linear algebra implementation issues must Cited by: seen a growing demand for the numerical solution of the eigenvalue problems.

Since the publication of Parlett’s exploratory review paper, ‘The software scene in the extraction of eigenvalues from sparse matrices’ [35], nearly a decade ago, many new numerical methods and analyses have been developed for the eigenproblem.

The PETSc Scientific Computing Libraries Numerical software libraries for the parallel solution of sparse linear systems, reduction of a symmetric-definite generalized eigenproblem to standard form, the symmetric, There is a collection of example programs from the book Using MPI.

Get this from a library! Vector and parallel processing--VECPAR ' Third International Conference, Porto, Portugal, Juneselected papers and invited talks. [José M L M Palma; J J Dongarra; Vicente Hernández;] -- This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Vector and Parallel Processing, VECPAR'98, held in.Gabriel Ok sa Convergence of the parallel Block-Jacobi EVD algo-rithm for Hermitian matrices 18 Michael Rippl E cient transformation of the general eigenproblem with symmetric banded matrices to a banded standard eigenproblem 19 Stefan Rosenberger OpenACC parallelization for the solution of the Bido-main equations Buy Applied Numerical Linear Algebra 97 edition () by NA for up to 90% off at Edition: