Applied parallel computing / Yuefan Deng.

Format:

Book

Author/Creator:

Deng, Yuefan.

Language:

English

Subjects (All):

Parallel processing (Electronic computers).

High performance computing.

Physical Description:

1 online resource (218 p.)

Edition:

1st ed.

Place of Publication:

Singapore ; Hong Kong : World Scientific, 2013.

Language Note:

English

Summary:

The book provides a practical guide to computational scientists and engineers to help advance their research by exploiting the superpower of supercomputers with many processors and complex networks. This book focuses on the design and analysis of basic parallel algorithms, the key components for composing larger packages for a wide range of applications.

Contents:

CONTENTS; Preface; Chapter 1. Introduction; 1.1. Definition of Parallel Computing; 1.2. Evolution of Computers; 1.3. An Enabling Technology; 1.4. Cost Effectiveness; 1.4.1. Purchasing costs; 1.4.2. Operating costs; 1.4.3. Programming costs; Chapter 2. Performance Metrics and Models; 2.1. Parallel Activity Trace; 2.2. Speedup; 2.3. Parallel Efficiency; 2.4. Load Imbalance; 2.5. Granularity; 2.6. Overhead; 2.7. Scalability; 2.8. Amdahl's Law; Chapter 3. Hardware Systems; 3.1. Node Architectures; 3.2. Network Interconnections; 3.2.1. Topology; 3.2.2. Interconnect Technology

3.3. Instruction and Data Streams3.4. Processor-MemoryConnectivity; 3.5. IO Subsystems; 3.6. System Convergence; 3.7. Design Considerations; Chapter 4. Software Systems; 4.1. Node Software; 4.1.1. Operating systems; 4.1.2. Compilers and libraries; 4.1.3. Profilers; 4.2. Programming Models; 4.2.1. Message passing; 4.2.2. Shared-memory; 4.3. ParallelDebuggers; 4.4. Parallel Profilers; Chapter 5. Design of Algorithms; 5.1. Algorithm Models; 5.1.1. Master-slave; 5.1.2. Domain decomposition; 5.1.3. Control decomposition; 5.1.4. Virtual-shared-memory; 5.1.5. Comparison of programming models

5.1.6. Parallel algorithmic issues5.1.7. Levels of algorithmic complication; 5.2. Examples of Collective Operations; 5.2.1. Broadcast; 5.2.2. Gather and scatter; 5.2.3. Allgather; 5.3. Mapping Tasks to Processors; 5.3.1. Supply matrix; 5.3.2. Demand matrix; 5.3.3. Review of mapping models; 5.3.4. Mapping models and algorithms; Chapter 6. Linear Algebra; 6.1. Problem Decomposition; 6.2. Matrix Operations; 6.2.1. Matrix-vector multiplications; 6.2.2. Matrix-matrix multiplications; 6.3. Solution of Linear Systems; 6.3.1. Direct methods; 6.3.2. Iterative methods; 6.3.3. ADI

Chapter 7. Differential Equations7.1. Integration and Differentiation; 7.1.1. Riemann summation for integration; 7.1.2. Monte Carlo method for integration; 7.1.3. Simple parallelization; 7.2. Partial Differential Equations; 7.2.1. Hyperbolic equations; 7.2.2. 3D Heat equation; 7.2.3. 2D Poisson equation; 7.2.4. 3D Poisson equation; 7.2.5. 3D Helmholtz equation; 7.2.6. Molecular dynamics; Chapter 8. Fourier Transforms; 8.1. Fourier Transforms; 8.2. Discrete Fourier Transforms; 8.3. Fast Fourier Transforms; 8.4. Simple Parallelization; 8.5. The Transpose Method; 8.6. Complexity Analysis for FFT

Chapter 9. Optimization9.1. Monte CarloMethods; 9.1.1. Basics; 9.1.2. Metropolis-Hastings Algorithm; 9.1.3. Simulated annealing; 9.1.4. Genetic algorithm; 9.2. Parallelization; 9.2.1. Basics; 9.2.2. Chain mixing method; Chapter 10. Applications; 10.1. Newton's Equation and Molecular Dynamics; 10.1.1. Molecular dynamics; 10.1.2. Basics of classical MD; 10.2. Schrodinger's Equations and Quantum Mechanics; 10.3. Partition Function, DFT and Material Science; 10.3.1. Materials research; 10.4. Maxwell's Equations and Electrical Engineering; 10.4.1. Helmholtz equation; 10.4.2. Electrical engineering

10.5. Diffusion Equation and Mechanical Engineering

Notes:

Description based upon print version of record.

Includes bibliographical references (p. 203) and index.

ISBN:

1-299-28111-7

981-4307-61-0

OCLC:

830162419