Using PLAPACK : parallel linear algebra package
著者
書誌事項
Using PLAPACK : parallel linear algebra package
（Scientific and engineering computation）
MIT, c1997
- : pbk
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注記
Bibliography: p. [185]-186
Includes indexes
内容説明・目次
内容説明
This book is a comprehensive introduction to all the components of a high-performance parallel linear algebra library, as well as a guide to the PLAPACK infrastructure.
PLAPACK is a library infrastructure for the parallel implementation of linear algebra algorithms and applications on distributed memory supercomputers such as the Intel Paragon, IBM SP2, Cray T3D/T3E, SGI PowerChallenge, and Convex Exemplar. This infrastructure allows library developers, scientists, and engineers to exploit a natural approach to encoding so-called blocked algorithms, which achieve high performance by operating on submatrices and subvectors. This feature, as well as the use of an alternative, more application-centric approach to data distribution, sets PLAPACK apart from other parallel linear algebra libraries, allowing for strong performance and significanltly less programming by the user. This book is a comprehensive introduction to all the components of a high-performance parallel linear algebra library, as well as a guide to the PLAPACK infrastructure. Scientific and Engineering Computation series
目次
- 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.
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