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Applied Parallel Computing.
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 com...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore :
World Scientific Publishing Company,
2012.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Preface; CONTENTS; 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.