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Practical Parallel Computing.

By: Morse, H. Stephen.
Material type: materialTypeLabelBookPublisher: Saint Louis : Elsevier Science & Technology, 2014Copyright date: ©1994Description: 1 online resource (420 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9781483214191.Subject(s): Parallel processing (Electronic computers)Genre/Form: Electronic books.Additional physical formats: Print version:: Practical Parallel ComputingDDC classification: 004.35 Online resources: Click here to view book
Contents:
Front Cover -- Practical Parallel Computing -- Copyright Page -- Table of Contents -- Dedication -- Preface -- Acknowledgments -- PART 1: Preliminaries -- Chapter 1. The Status and Future of Massively Parallel Processing -- 1.1 Technology Trends Favoring Parallel Architectures -- 1.2 Obstacles Inhibiting Commercial Success -- 1.3 Trends and Considerations -- Chapter 2. Can Parallel Machines Be Used Efficiently? -- 2.1 A Parallel Parable: Building a Wall -- 2.2 Amdahl's Law -- 2.3 Examples -- Chapter 3. An Introduction to Hardware Architectures -- 3.1 Impacts of Hardware Architecture -- 3.2 A Primer on Interconnection Networks -- 3.3 SIMD Machines -- 3.4 Distributed Memory MIMD Machines -- 3.5 Shared Memory MIMD Machines -- PART 2: Software Issues -- Chapter 4. Shared Memory Parallel Language Constructs -- 4.1 Basic Concepts for Shared Memory Parallel Programming -- 4.2 The Sample Problem on an SGI Challenge SMP -- 4.3 Observations and Considerations -- Chapter 5. Message Passing -- 5.1 An Overview of the Message-Passing Library -- 5.2 The Sample Problem on an nCube 2 -- 5.3 Express -- 5.4 Intel Paragon -- 5.5 Observations and Considerations -- Chapter 6. SIMD and Array-Based Languages -- 6.1 An Overview -- 6.2 MPL on the MasPar MP-1 -- 6.3 C* on the Connection Machine -- Chapter 7. Linda -- 7.1 A Linda Primer -- 7.2 The Sample Problem in Linda -- 7.3 Observations and Considerations -- Chapter 8. The Development Environment for Parallel Software -- 8.1 Compilers -- 8.2 Debugging Parallel Code -- 8.3 Profilers and Load Balancing -- 8.4 Other Tools -- Chapter 9. Operating System Issues -- 9.1 Multiple Users -- 9.2 Virtual Address Spaces -- 9.3 Scheduling -- 9.4 Virtual Processors -- 9.5 I/O -- 9.6 Open Systems -- PART 3: Management Issues -- Chapter 10. Benchmarking Parallel Applications -- 10.1 Dependence on Problem Size and Machine Size.
10.2 Publicly Available Parallel Benchmarks -- 10.3 Scaling Sequential Performance to Parallel Performance -- 10.4 Estimating Performance -- 10.5 Questions to Ask Vendors -- Chapter 11. Porting and Developing Parallel Applications -- 11.1 Porting Strategies -- 11.2 Developing Parallel Applications -- 11.3 Examples -- Chapter 12. Matching Applications to Architectures -- 12.1 A Methodology -- 12.2 Integrating a Parallel Machine into Existing Operations -- Appendix A: The Sample Problem -- Appendix B: SGI Challenge -- Appendix C: nCube -- Appendix D: Express -- Appendix E: Intel Paragon -- Appendix F: MasPar MP-1 -- Appendix G: C* on the Connection Machine -- Appendix H: Linda -- Appendix I: Two Recent Machines -- I.1 The SP-Series from IBM -- I.2 Exemplar Series from Convex Corp -- I.3 Summary and Comparison -- References -- Index.
Summary: Practical Parallel Computing provides information pertinent to the fundamental aspects of high-performance parallel processing. This book discusses the development of parallel applications on a variety of equipment. Organized into three parts encompassing 12 chapters, this book begins with an overview of the technology trends that converge to favor massively parallel hardware over traditional mainframes and vector machines. This text then gives a tutorial introduction to parallel hardware architectures. Other chapters provide worked-out examples of programs using several parallel languages. This book deals as well with benchmarking and performance estimation on parallel machines. The final chapter provides a structured, flexible methodology for selecting a parallel machine and for integrating it into operations. This book is a valuable resource for readers who are confronted with the practical realities of parallel computing for the first time. Mid-level technical managers, algorithm designers, computer scientists, and doctorate-level mathematicians will also find this book extremely useful.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
QA76.58 -- .M67 1994 (Browse shelf) http://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=1876817 Available EBC1876817

Front Cover -- Practical Parallel Computing -- Copyright Page -- Table of Contents -- Dedication -- Preface -- Acknowledgments -- PART 1: Preliminaries -- Chapter 1. The Status and Future of Massively Parallel Processing -- 1.1 Technology Trends Favoring Parallel Architectures -- 1.2 Obstacles Inhibiting Commercial Success -- 1.3 Trends and Considerations -- Chapter 2. Can Parallel Machines Be Used Efficiently? -- 2.1 A Parallel Parable: Building a Wall -- 2.2 Amdahl's Law -- 2.3 Examples -- Chapter 3. An Introduction to Hardware Architectures -- 3.1 Impacts of Hardware Architecture -- 3.2 A Primer on Interconnection Networks -- 3.3 SIMD Machines -- 3.4 Distributed Memory MIMD Machines -- 3.5 Shared Memory MIMD Machines -- PART 2: Software Issues -- Chapter 4. Shared Memory Parallel Language Constructs -- 4.1 Basic Concepts for Shared Memory Parallel Programming -- 4.2 The Sample Problem on an SGI Challenge SMP -- 4.3 Observations and Considerations -- Chapter 5. Message Passing -- 5.1 An Overview of the Message-Passing Library -- 5.2 The Sample Problem on an nCube 2 -- 5.3 Express -- 5.4 Intel Paragon -- 5.5 Observations and Considerations -- Chapter 6. SIMD and Array-Based Languages -- 6.1 An Overview -- 6.2 MPL on the MasPar MP-1 -- 6.3 C* on the Connection Machine -- Chapter 7. Linda -- 7.1 A Linda Primer -- 7.2 The Sample Problem in Linda -- 7.3 Observations and Considerations -- Chapter 8. The Development Environment for Parallel Software -- 8.1 Compilers -- 8.2 Debugging Parallel Code -- 8.3 Profilers and Load Balancing -- 8.4 Other Tools -- Chapter 9. Operating System Issues -- 9.1 Multiple Users -- 9.2 Virtual Address Spaces -- 9.3 Scheduling -- 9.4 Virtual Processors -- 9.5 I/O -- 9.6 Open Systems -- PART 3: Management Issues -- Chapter 10. Benchmarking Parallel Applications -- 10.1 Dependence on Problem Size and Machine Size.

10.2 Publicly Available Parallel Benchmarks -- 10.3 Scaling Sequential Performance to Parallel Performance -- 10.4 Estimating Performance -- 10.5 Questions to Ask Vendors -- Chapter 11. Porting and Developing Parallel Applications -- 11.1 Porting Strategies -- 11.2 Developing Parallel Applications -- 11.3 Examples -- Chapter 12. Matching Applications to Architectures -- 12.1 A Methodology -- 12.2 Integrating a Parallel Machine into Existing Operations -- Appendix A: The Sample Problem -- Appendix B: SGI Challenge -- Appendix C: nCube -- Appendix D: Express -- Appendix E: Intel Paragon -- Appendix F: MasPar MP-1 -- Appendix G: C* on the Connection Machine -- Appendix H: Linda -- Appendix I: Two Recent Machines -- I.1 The SP-Series from IBM -- I.2 Exemplar Series from Convex Corp -- I.3 Summary and Comparison -- References -- Index.

Practical Parallel Computing provides information pertinent to the fundamental aspects of high-performance parallel processing. This book discusses the development of parallel applications on a variety of equipment. Organized into three parts encompassing 12 chapters, this book begins with an overview of the technology trends that converge to favor massively parallel hardware over traditional mainframes and vector machines. This text then gives a tutorial introduction to parallel hardware architectures. Other chapters provide worked-out examples of programs using several parallel languages. This book deals as well with benchmarking and performance estimation on parallel machines. The final chapter provides a structured, flexible methodology for selecting a parallel machine and for integrating it into operations. This book is a valuable resource for readers who are confronted with the practical realities of parallel computing for the first time. Mid-level technical managers, algorithm designers, computer scientists, and doctorate-level mathematicians will also find this book extremely useful.

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