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Parallelism in Matrix Computations

The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems, linear least squares, the symmetric algebraic eigenvalue problem, and the singular-value decomposition. It also deals with the development of parallel algorithms for special linear systems such as banded ,Vandermonde ,Toeplitz ,and block Toeplitz systems. Part III addresses sparse matrix computations: (a) the development of parallel iterative linear system solvers with emphasis on scalable preconditioners, (b) parallel schemes for obtaining a few of the extreme eigenpairs or those contained in a given interval in the spectrum of a standard or generalized symmetric eigenvalue problem, and (c) parallel methods for computing a few of the extreme singular triplets. Part IV focuses on the development of parallel algorithms for matrix functions and special characteristics such as the matrix pseudospectrum and the determinant. The book also reviews the theoretical and practical background necessary when designing these algorithms and includes an extensive bibliography that will be useful to researchers and students alike.

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Detail Information
Series Title
Scientific Computation
Call Number
512.943 4 GAL p
Publisher
: Springer.,
Collation
XXX, 473 halaman
Language
English
ISBN/ISSN
978-94-017-7188-7
Classification
512.943 4
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
-
Subject(s)
Matrices
Specific Detail Info
-
Statement of Responsibility
Other Information
Cataloger
maya
Source
-
Validator
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