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E-raamat: Parallel Scientific Computation: A Structured Approach using BSP and MPI

(, Associate Professor, Mathematics Department, Utrecht University)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 04-Mar-2004
  • Kirjastus: Oxford University Press
  • Keel: eng
  • ISBN-13: 9780191523847
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 04-Mar-2004
  • Kirjastus: Oxford University Press
  • Keel: eng
  • ISBN-13: 9780191523847

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Bisseling (mathematics, Utrecht University) introduces a simple target architecture for designing parallel algorithms, known as the bulk synchronous parallel model, and presents sample algorithms for carrying out matrix computations, the fast Fourier transform, and the multiplication of a sparse matrix and a dense vector. Using primitive functions from the BSPlib library, the examples list the complete program text and provide illustrative results of each representation on a different parallel computer. The text is intended for graduate students and scientists. Annotation ©2004 Book News, Inc., Portland, OR (booknews.com)

Based on the author's extensive development, this is the first text explaining how to use BSPlib, the bulk synchronous parallel library, which is freely available for use in parallel programming. Aimed at graduate students and researchers in mathematics, physics and computer science, the main topics treated in the book are core in the area of scientific computation and many additional topics are treated in numerous exercises. An appendix on the message-passing interface (MPI) discusses how to program using the MPI communication library. MPI equivalents of all the programs are also presented. The main topics treated in the book are core in the area of scientific computation: solving dense linear systems by Gaussian elimination, computing fast Fourier transforms, and solving sparse linear systems, by iterative methods. Each topic is treated in depth, starting from the problem formulation and a sequential algorithm, through a parallel algorithm and its analysis to a complete parallel program written in C and BSPlib, and experimental results obtained using this program on a parallel computer. Additional topics treated in the exercises include: data compression, random number generation, cryptography, eigensystem solving, 3D and Strassen Matrix multiplication, wavelets and image compression, fast cosine transform, decimals of pi, simulated annealing and molecular dynamics. This book contains five small but complete example programs written in BSPlib which illustrates the methods taught. The appendix on MPI discusses how to program in a structured, bulk synchronous parallel style using the MPI communication library. It presents MPI equivalents of all the programs in the book. The complete programs of the book and their driver programs are freely available online in packages called BSPedupack and MPIedupack.

Arvustused

The book is contemporary, well presented, and balanced between concepts and the technical depth required for developing parallel algorithms. * Scalable Computing: Practice and Experience, Volume 7, No. 2, June 2006 * The book is carefully written and edited. It is an excellent starting point for learning how to write well-structured, parallel scientific programs. * Diego R. Llanos, ACM * A good lecture to learn the basic lessons of parallel programming * European Mathematical Society *

1 Introduction 1(49)
1.1 Wanted: a gentle parallel programming model
1(2)
1.2 The BSP model
3(6)
1.3 BSP algorithm for inner product computation
9(4)
1.4 Starting with BSPlib: example program bspinprod
13(11)
1.5 BSP benchmarking
24(3)
1.6 Example program bspbench
27(4)
1.7 Benchmark results
31(7)
1.8 Bibliographic notes
38(6)
1.8.1 BSP-related models of parallel computation
38(2)
1.8.2 BSP libraries
40(2)
1.8.3 The non-BSP world: message passing
42(1)
1.8.4 Benchmarking
43(1)
1.9 Exercises
44(6)
2 LU decomposition 50(50)
2.1 The problem
50(1)
2.2 Sequential LU decomposition
51(6)
2.3 Basic parallel algorithm
57(7)
2.4 Two-phase broadcasting and other improvements
64(8)
2.5 Example function bsplu
72(7)
2.6 Experimental results on a Cray T3E
79(6)
2.7 Bibliographic notes
85(3)
2.7.1 Matrix distributions
85(2)
2.7.2 Collective communication
87(1)
2.7.3 Parallel matrix computations
87(1)
2.8 Exercises
88(12)
3 The fast Fourier transform 100(63)
3.1 The problem
100(3)
3.2 Sequential recursive fast Fourier transform
103(2)
3.3 Sequential nonrecursive algorithm
105(8)
3.4 Parallel algorithm
113(7)
3.5 Weight reduction
120(7)
3.6 Example function bspfft
127(9)
3.7 Experimental results on an SGI Origin 3800
136(9)
3.8 Bibliographic notes
145(7)
3.8.1 Sequential FFT algorithms
145(2)
3.8.2 Parallel FFT algorithms with log2p or more supersteps
147(1)
3.8.3 Parallel FFT algorithms with 0(1) supersteps
148(3)
3.8.4 Applications
151(1)
3.9 Exercises
152(11)
4 Sparse matrix-vector multiplication 163(88)
4.1 The problem
163(4)
4.2 Sparse matrices and their data structures
167(6)
4.3 Parallel algorithm
173(6)
4.4 Cartesian distribution
179(7)
4.5 Mondriaan distribution for general sparse matrices
186(11)
4.6 Vector distribution
197(6)
4.7 Random sparse matrices
203(7)
4.8 Laplacian matrices
210(12)
4.9 Remainder of BSPlib: example function bspmv
222(9)
4.10 Experimental results on a Beowulf cluster
231(4)
4.11 Bibliographic notes
235(8)
4.11.1 Sparse matrix computations
235(2)
4.11.2 Parallel sparse matrix-vector multiplication algorithms
237(2)
4.11.3 Parallel iterative solvers for linear systems
239(1)
4.11.4 Partitioning methods
240(3)
4.12 Exercises
243(8)
A Auxiliary BSPedupack functions 251(3)
A.1 Header file bspedupack.h
251(1)
A.2 Utility file bspedupack.c
251(3)
B A quick reference guide to BSPlib 254(2)
C Programming in BSP style using MPI 256(27)
C.1 The message-passing interface
256(2)
C.2 Converting BSPedupack to MPledupack
258(20)
C.2.1 Program mpiinprod
258(3)
C.2.2 Program mpibench
261(4)
C.2.3 Function mpilu
265(5)
C.2.4 Function mpifft
270(3)
C.2.5 Function mpimv
273(5)
C.3 Performance comparison on an SGI Origin 3800
278(2)
C.4 Where BSP meets MPI
280(3)
References 283(16)
Index 299