Introduction to Parallel Computing

Name: Introduction to Parallel Computing | A practical guide with examples in C
Brand: Oxford University Press, UK
Price: 78.89 EUR
Availability: OnlineOnly

A practical guide with examples in C

Peter Arbenz Wesley Petersen(Autor*in)

Oxford University Press, UK

1. Auflage

Erschienen am 8. Januar 2004

278 Seiten

E-Book

PDF mit Adobe-DRM

Systemvoraussetzungen

978-0-19-151361-9 (ISBN)

78,89 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Adobe-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Weitere Ausgaben

Inhalt

Intro
Contents
List of Figures
List of Tables
1 BASIC ISSUES
1.1 Memory
1.2 Memory systems
1.2.1 Cache designs
1.2.2 Pipelines, instruction scheduling, and loop unrolling
1.3 Multiple processors and processes
1.4 Networks
2 APPLICATIONS
2.1 Linear algebra
2.2 LAPACK and the BLAS
2.2.1 Typical performance numbers for the BLAS
2.2.2 Solving systems of equations with LAPACK
2.3 Linear algebra: sparse matrices, iterative methods
2.3.1 Stationary iterations
2.3.2 Jacobi iteration
2.3.3 Gauss-Seidel (GS) iteration
2.3.4 Successive and symmetric successive overrelaxation
2.3.5 Krylov subspace methods
2.3.6 The generalized minimal residual method (GMRES)
2.3.7 The conjugate gradient (CG) method
2.3.8 Parallelization
2.3.9 The sparse matrix vector product
2.3.10 Preconditioning and parallel preconditioning
2.4 Fast Fourier Transform (FFT)
2.4.1 Symmetries
2.5 Monte Carlo (MC) methods
2.5.1 Random numbers and independent streams
2.5.2 Uniform distributions
2.5.3 Non-uniform distributions
3 SIMD, SINGLE INSTRUCTION MULTIPLE DATA
3.1 Introduction
3.2 Data dependencies and loop unrolling
3.2.1 Pipelining and segmentation
3.2.2 More about dependencies, scatter/gather operations
3.2.3 Cray SV-1 hardware
3.2.4 Long memory latencies and short vector lengths
3.2.5 Pentium 4 and Motorola G-4 architectures
3.2.6 Pentium 4 architecture
3.2.7 Motorola G-4 architecture
3.2.8 Branching and conditional execution
3.3 Reduction operations, searching
3.4 Some basic linear algebra examples
3.4.1 Matrix multiply
3.4.2 SGEFA: The Linpack benchmark
3.5 Recurrence formulae, polynomial evaluation
3.5.1 Polynomial evaluation
3.5.2 A single tridiagonal system
3.5.3 Solving tridiagonal systems by cyclic reduction
3.5.4 Another example of non-unit strides to achieve parallelism
3.5.5 Some examples from Intel SSE and Motorola Altivec
3.5.6 SDOT on G-4
3.5.7 ISAMAX on Intel using SSE
3.6 FFT on SSE and Altivec
4 SHARED MEMORY PARALLELISM
4.1 Introduction
4.2 HP9000 Superdome machine
4.3 Cray X1 machine
4.4 NEC SX-6 machine
4.5 OpenMP standard
4.6 Shared memory versions of the BLAS and LAPACK
4.7 Basic operations with vectors
4.7.1 Basic vector operations with OpenMP
4.8 OpenMP matrix vector multiplication
4.8.1 The matrix-vector multiplication with OpenMP
4.8.2 Shared memory version of SGEFA
4.8.3 Shared memory version of FFT
4.9 Overview of OpenMP commands
4.10 Using Libraries
5 MIMD, MULTIPLE INSTRUCTION, MULTIPLE DATA
5.1 MPI commands and examples
5.2 Matrix and vector operations with PBLAS and BLACS
5.3 Distribution of vectors
5.3.1 Cyclic vector distribution
5.3.2 Block distribution of vectors
5.3.3 Block-cyclic distribution of vectors
5.4 Distribution of matrices
5.4.1 Two-dimensional block-cyclic matrix distribution
5.5 Basic operations with vectors
5.6 Matrix-vector multiply revisited
5.6.1 Matrix-vector multiplication with MPI
5.6.2 Matrix-vector multiply with PBLAS
5.7 ScaLAPACK
5.8 MPI two-dimensional FFT example
5.9 MPI three-dimensional FFT example
5.10 MPI Monte Carlo (MC) integration example
5.11 PETSc
5.11.1 Matrices and vectors
5.11.2 Krylov subspace methods and preconditioners
5.12 Some numerical experiments with a PETSc code
APPENDIX A: SSE INTRINSICS FOR FLOATING POINT
A.1 Conventions and notation
A.2 Boolean and logical intrinsics
A.3 Load/store operation intrinsics
A.4 Vector comparisons
A.5 Low order scalar in vector comparisons
A.6 Integer valued low order scalar in vector comparisons
A.7 Integer/floating point vector conversions
A.8 Arithmetic function intrinsics
APPENDIX B: ALTIVEC INTRINSICS FOR FLOATING POINT
B.1 Mask generating vector comparisons
B.2 Conversion, utility, and approximation functions
B.3 Vector logical operations and permutations
B.4 Load and store operations
B.5 Full precision arithmetic functions on vector operands
B.6 Collective comparisons
APPENDIX C: OPENMP COMMANDS
APPENDIX D: SUMMARY OF MPI COMMANDS
D.1 Point to point commands
D.2 Collective communications
D.3 Timers, initialization, and miscellaneous
APPENDIX E: FORTRAN AND C COMMUNICATION
APPENDIX F: GLOSSARY OF TERMS
APPENDIX G: NOTATIONS AND SYMBOLS
References
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
R
S
T
V
W
X

Systemvoraussetzungen

Als PDF speichern Als Link merken