Industrial Strength Parallel Computing
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Table of contents
- Cover
- Copyright Pageiv
- Contentsvii
- Prefacexix
- Color PlatesPlate1
- Part I : The Parallel Computing Environment1
- Chapter 1. Parallel Computing Architectures3
- 1.1 Historical Parallel Computing Architectures3
- 1.2 Contemporary Parallel Computing Architectures6
- References18
- Chapter 2. Parallel Application Performance21
- 2.1 Defining Performance21
- 2.2 Measuring Performance23
- References26
- Chapter 3. Programming Models and Methods27
- 3.1 Message Passing Models29
- 3.2 Data Parallel Models42
- 3.3 Parallel Programming Methods45
- References53
- Chapter 4. Parallel Programming Tools55
- 4.1 The Apprentice Performance Analysis Tool55
- 4.2 Debuggers60
- Chapter 5. Optimizing for Singlec-Processor Performance67
- 5.1 Using the Functional Units Effectively68
- 5.2 Hiding Latency with the Cache70
- 5.3 Stream Buffer Optimizations74
- 5.4 E-Register Operations76
- 5.5 How Much Performance Can Be Obtained on a Single Processor?77
- References79
- Chapter 6. Scheduling Issues81
- 6.1 Gang Scheduler Implementation82
- 6.2 Gang Scheduler Performance86
- References90
- Part II: The Applications91
- Chapter 7. Ocean Modeling and Visualization95
- 7.1 Introduction95
- 7.2 Model Description97
- 7.3 Computational Considerations97
- 7.4 Visualization on MPP Machines103
- 7.5 Scientific Results106
- 7.6 Summary and Future Challenges108
- Acknowledgments111
- References112
- Chapter 8. Impact of Aircraft on Global Atmospheric Chemistry115
- 8.1 Introduction115
- 8.2 Industrial Considerations116
- 8.3 Project Objectives and Application Code117
- 8.4 Computational Considerations119
- 8.5 Computational Results123
- 8.6 Industrial Results125
- 8.7 Summary126
- References127
- Chapter 9. Petroleum Reservoir Management129
- 9.1 Introduction129
- 9.2 The Need for Parallel Simulations130
- 9.3 Basic Features of the Falcon Simulator131
- 9.4 Parallel Programming Model and Implementation132
- 9.5 IMPES Linear Solver134
- 9.6 Fully Implicit Linear Solver136
- 9.7 Falcon Performance Results140
- 9.8 Amoco Field Study142
- 9.9 Summary143
- Acknowledgments144
- References145
- Chapter 10. An Architecture-Independent Navier-Stokes Code147
- 10.1 Introduction147
- 10.2 Basic Equations148
- 10.3 A Navier Stokes Solver151
- 10.4 Parallelization of a Navier-Stokes Solver155
- 10.5 Computational Results159
- 10.6 Summary163
- Acknowledgments164
- References166
- Chapter 11. Gaining Insights into the Flow In a Static Mixer169
- 11.1 Introduction169
- 11.2 Computational Aspects172
- 11.3 Performance Results178
- 11.4 Industrial Results180
- 11.5 Summary186
- Acknowledgments186
- References187
- Chapter 12. Modeling Groundwater Flow and Contaminant Transport189
- 12.1 Introduction189
- 12.2 Numerical Simulation of Groundwater Flow191
- 12.3 Parallel Implementation194
- 12.4 The MGCG Algorithm202
- 12.5 Numerical Results211
- 12.6 Summary222
- Acknowledgments223
- References224
- Chapter 13. Simulation of Plasma Reactors227
- 13.1 Introduction227
- 13.2 Computational Considerations229
- 13.3 Simulation Results238
- 13.4 Performance Results239
- 13.5 Summary243
- Acknowledgments244
- References246
- Chapter 14. Electron-Molecule Collisions for Plasma Modeling247
- 14.1 Introduction247
- 14.2 Computing Electron-Molecule Cross Sections251
- 14.3 Performance262
- 14.4 Summary264
- Acknowledgments265
- References266
- Chapter 15. Three-Dimensional Plasma Particle-in-Cell Calculations of Ion Thruster Backflow Contamin267
- 15.1 Introduction267
- 15.2 The Physical Model268
- 15.3 The Numerical Model273
- 15.4 Parallel Implementation276
- 15.5 Results340
- 15.6 Parallel Study349
- 15.7 Summary351
- Acknowledgments352
- References353
- Chapter 16. Advanced Atomic-Level Materials Design356
- 16.1 Introduction356
- 16.2 Industrial Considerations361
- 16.3 Computational Considerations and Parallel Implementations362
- 16.4 Applications to Grain Boundaries in Polycrystalline Diamond370
- 16.5 Summary371
- Acknowledgments373
- References374
- Chapter 17. Solving Symmetric Eigenvalue Problems376
- 17.1 Introduction376
- 17.2 Jacobi’s Method377
- 17.3 Classical Jacobi Method378
- 17.4 Serial Jacobi Method379
- 17.5 Tournament Orderings380
- 17.6 Parallel Jacobi Method381
- 17.7 Macro Jacobi Method386
- 17.8 Computational Experiments388
- 17.9 Summary392
- Acknowledgments396
- References397
- Chapter 18. Nuclear Magnetic Resonance Simulations398
- 18.1 Introduction398
- 18.2 Scientific Considerations399
- 18.3 Description of the Application400
- 18.4 Computational Considerations402
- 18.5 Computational Results405
- 18.6 Scientific Results405
- 18.7 Summary410
- Acknowledgments411
- References412
- Chapter 19. Molecular Dynamics Simulations Using Particle-Mesh Ewald Methods414
- 19.1 Introduction: Industrial Considerations414
- 19.2 Computational Considerations422
- 19.3 Computational Results430
- 19.4 Industrial Strength Results439
- 19.5 The Future442
- 19.6 Summary443
- References444
- Chapter 20. Radar Scattering and Antenna Modeling448
- 20.1 Introduction448
- 20.2 Electromagnetic Scattering and Radiation449
- 20.3 Finite Element Modeling453
- 20.4 Computational Formulation and Results462
- 20.5 Results for Radar Scattering and Antenna Modeling475
- 20.6 Summary and Future Challenges486
- Acknowledgments487
- References488
- Chapter 21. Functional Magnetic Resonance Imaging Dataset Analysis490
- 21.1 Introduction490
- 21.2 Industrial Considerations491
- 21.3 Computational Considerations494
- 21.4 Computational Results497
- 21.5 Clinical and Scientific Results503
- 21.6 Summary507
- Acknowledgments508
- References509
- Chapter 22. Selective and Sensitive Comparison of Genetic Sequence Data512
- 22.1 Introduction512
- 22.2 Industrial Considerations512
- 22.3 Approaches Used to Compare Sequences516
- 22.4 Computational Considerations521
- 22.5 Computational Results526
- 22.6 Industrial and Scientific Considerations529
- 22.7 The Next Problems to Tackle532
- 22.8 Summary534
- Acknowledgments534
- References535
- Chapter 23. Interactive Optimization of Video Compression Algorithms540
- 23.1 Introduction540
- 23.2 Industrial Considerations541
- 23.3 General Description of the System542
- 23.4 Parallel Implementation548
- 23.5 Description of the Compression Algorithm552
- 23.6 Experimental Results553
- 23.7 Summary554
- Acknowledgments555
- References556
- Part III: Conclusions and Predictions558
- Chapter 24. Designing Industrial Parallel Applications560
- 24.1 Design Lessons from the Applications560
- 24.2 Design Issues565
- 24.3 Additional Design Issues568
- Chapter 25. The Future of Industrial Parallel Computing570
- 25.1 The Role of Parallel Computing in Industry571
- 25.2 Microarchitecture Issues572
- 25.3 Macroarchitecture Issues573
- 25.4 System Software Issues577
- 25.5 Programming Environment Issues578
- 25.6 Applications Issues580
- 25.7 Parallel Computing in Industry583
- 25.8 Looking Forward: The Role of Parallel Computing in the Digital Information Age587
- References592
- Appendix. Mixed Models with Pthreads and MPI594
- Glossary612
- Index622
- Contributors650
Today, parallel computing experts can solve problems previously deemed impossible and make the "merely difficult" problems economically feasible to solve. This book presents and synthesizes the recent experiences of reknown expert developers who design robust and complex parallel computing applications. They demonstrate how to adapt and implement today's most advanced, most effective parallel computing techniques.
The book begins with a highly focused introductory course designed to provide a working knowledge of all the relevant architectures, programming models, and performance issues, as well as the basic approaches to assessment, optimization, scheduling, and debugging.
Next comes a series of seventeen detailed case studies—all dealing with production-quality industrial and scientific applications, all presented firsthand by the actual code developers. Each chapter follows the same comparison-inviting format, presenting lessons learned and algorithms developed in the course of meeting real, non-academic challenges. A final section highlights the case studies' most important insights and turns an eye to the future of the discipline.
* Provides in-depth case studies of seventeen parallel computing applications, some built from scratch, others developed through parallelizing existing applications.
* Explains elements critical to all parallel programming environments, including:
** Terminology and architectures
** Programming models and methods
** Performance analysis and debugging tools
* Teaches primarily by example, showing how scientists in many fields have solved daunting problems using parallel computing.
* Covers a wide range of application areas—biology, aerospace, semiconductor design, environmental modeling, data imaging and analysis, fluid dynamics, and more.
* Summarizes the state of the art while looking to the future of parallel computing.
Presents technical animations and visualizations from many of the applications detailed in the case studies via a companion web site.