Using PLAPACK: Parallel Linear Algebra Package
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Using PLAPACK: Parallel Linear Algebra Package

Using PLAPACK: Parallel Linear Algebra Package


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About the Book

Table of Contents:
Part 1 Introduction: why a new infrastructure? natural description of linear algebra algorithms; physically based matrix distribution; redistributing and duplicating matrices and vectors; implementation of basic matrix-vector operations (preview); basic linear algebra subprograms; message-passing interface; parallel sparse linear algebra; FORTRAN interface; availability. Part 2 Templates and linear algebra objects: initializing PLAPACK; distribution templates; linear algebra objects; example; return values; more operations and information. Part 3 Advanced linear algebra object manipulation: creating views into objects;, splitting of linear algebra objects; shifting of linear algebra objects; determining where to split; creating objects 'conformal to' other objects; annotating object orientation; casting object types; more operations and information. Part 4 Application program interface: introduction; API-activation; opening and closing an object; accessing a vector; accessing a matrix; completion and synchronization; examples; more operations and information. Part 5 Data duplication and consolidation: copy; reduce; pipeline computation and communication; a building block approach to implementing copy and reduce; more operations and information. Part 6 Vector-vector operations: copy; swap; scaling a vector (object); scaled vector (object) addition; inner product of vectors; norms of vectors; maximum absolute value in vector; example - parallelizing inner product; example - parallelizing 'axpy' for vector objects; more operations and information. Part 7 Matrix-vector operations: general matrix-vector multiplication; symmetric matrix-vector multiplication; triangular matrix-vector multiplication; triangular solve; Rank-1 update; symmetric Rank-1 update; symmetric Rank-2 update; example - parallelizing matrix-vector multiplication; example parallelizing Rank-1 update; more operations and information. Part 8 Matrix-matrix operations: general matrix-matrix multiplication; symmetric matrix-matrix multiplication; symmetric Rank-k update; symmetric Rank-2k update; triangular matrix-matrix multiplication; triangular solve with multiple right-hand-sides; example - parallelizing matrix-matrix multiplication; queering algorithmic blocking size; more operations and information. Part 9 Application of the infrastructure: Cholesky factorization; right-looking variant; left-looking variant; more operations and information. Summaries: PLAPACK routines and their arguments; BLAS related routines.

About the Author :
Robert van de Geijn is a Professor in the Department in Computer Science and the Texas Institute for Computational Engineering and Sciences at the University of Texas at Austin.


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Product Details
  • ISBN-13: 9780262720267
  • Publisher: MIT Press Ltd
  • Publisher Imprint: MIT Press
  • Height: 229 mm
  • No of Pages: 214
  • Spine Width: 13 mm
  • Width: 203 mm
  • ISBN-10: 0262720264
  • Publisher Date: 03 Apr 1997
  • Binding: Paperback
  • Language: English
  • Series Title: Scientific and Engineering Computation
  • Weight: 386 gr


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