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Languages, Compilers and Run-time Environments for Distributed Memory Machines
von: J. Saltz, P. Mehrotra
Elsevier Reference Monographs, 2014
ISBN: 9781483295381 , 320 Seiten
Format: PDF
Kopierschutz: DRM
Preis: 54,95 EUR
Front Cover
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Languages, Compilers and Run-Time Environments for Distributed Memory Machines
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Copyright Page
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Table of Contents
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PREFACE
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Chapter 1. SUPERB: Experiences and Future Research
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Abstract
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1 Introduction
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2 Program Splitting
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3 Data Partitioning
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4 Interprocedural Partitioning Analysis
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5 Automatic Insertion of Masking and Communication
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6 Optimization
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7 System Structure
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8 Current and Future Research
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9 Conclusion
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References
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Chapter 2. Scientific Programming Languages for Distributed Memory Multiprocessors : Paradigms and Research Issues
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Abstract
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1. Introduction
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2. An Emerging Paradigm for Distributed Parallel Languages
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3. An Example of the Paradigm : The DINO Language
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4. Research Issues Regarding Virtual Parallel Computers
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5. Research Issues Regarding Distributed Data Structures
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6. Research Issues Regarding Models of Parallel Computation
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7. Additional Research Issues Regarding Communication Features
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8. Research Issues Regarding Support for Complex Parallel Programs
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9. References
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Chapter 3. VIENNA FORTRAN - A FORTRAN LANGUAGE EXTENSION FOR DISTRIBUTED MEMORY MULTIPROCESSORS*
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Abstract
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1 Introduction
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2 The Basic Features of Vienna Fortran
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3 Examples
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4 Related Work
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5 Conclusions
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Acknowledgments
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References
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Chapter 4. Compiler Parallelization of SIMPLE for a Distributed Memory Machine
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Abstract
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1 Introduction
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2 What is SIMPLE?
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3 Machine Model
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4 Data Distribution
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5 Code Generation
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6 Results and Analysis
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7 Summary
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Acknowledgements
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References
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Chapter 5. Applications of the "Phase Abstractions" for Portable and Scalable Parallel Programming
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Abstract
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1 Introduction
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2 Preliminaries
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3 Jacobi Iteration Example
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4 Specification of the Processes, Level X
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5 Global Data Declaration
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6 Phase Definitions, Y Level
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7 Main Program Body, Æ Level
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8 Commentary on the Program and Abstractions
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9 Conclusions
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10 Acknowledgments
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References
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Chapter 6. Nicke - C Extensions for Programming on Distributed-Memory Machines
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Abstract
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1 Introduction
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2 Basic Constructs
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3 Shared Variables
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4 Impiementation
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5 Conclusion
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References
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Chapter 7. A Static Performance Estimator in the Fortran D Programming System
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Abstract
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1. INTRODUCTION
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2. DISTRIBUTED MEMORY PROGRAMMING MODEL
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3. CHOOSING THE DATA DECOMPOSITION SCHEME
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4. AN EXAMPLE
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5. THE TRAINING SET METHOD OF PERFORMANCE ESTIMATION
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6. THE PERFORMANCE ESTIMATION ALGORITHM
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7. A PROTOTYPE IMPLEMENTATION
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8. CONCLUSION AND FUTURE WORK
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References
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Chapter 8. Compiler Support for Machine-Independent Parallel Programming in Fortran D
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Abstract
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1 Introduction
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2 Fortran D
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3 Basic Compilation Strategy
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4 Compilation of Whole Programs
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5 Validation
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6 Relationship to Other Research
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7 Conclusions and Future Work
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8 Acknowledgements
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References
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Chapter 9. PANDORE: A System to Manage Data Distribution
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Abstract
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1. INTRODUCTION
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2. OVERVIEW OF THE PANDORE SYSTEM
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3. THE PANDORE LANGUAGE
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4. FURTHER WORK
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References
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Chapter 10. DISTRIBUTED MEMORY COMPILER METHODS FOR IRREGULAR PROBLEMS - DATA COPY REUSE AND RUNTIME PARTITIONING1
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Abstract
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1 Introduction
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2 Overview
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3 The PARTI Primitives
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4 PARTI Compiler
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5 Experimental Results
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6 Conclusions
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Acknowledgements
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References
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Chapter 11. Scheduling EPL Programs for Parallel Processing
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1 Introduction
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2 Basic Scheduling in EPL
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3 Case Study: Horizontal Partitioning for the CM
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4 Alignment Problem
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5 Optimum Direction of Computation
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6 Conclusion
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References
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Chapter 12. Parallelizing Programs for Distributed-Memory Machines using the Crystal System
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Abstract
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1 Introduction
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2 Summary of Our Position
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3 The Crystal Model and its Language and Metalanguage Features
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4 The Crystal Compiler
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5 Performance Results
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6 Crystalizing FORTRAN
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References
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A Appendix
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Chapter 13. Iteration Space Tiling for Distributed Memory Machines
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Abstract
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1 Introduction
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2 Background
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3 Issues in tiling of iteration spaces
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4 Extreme vectors and deadlock free tiling
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5 Computing the extreme vectors
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6 Choosing deadlock-free tiles
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7 Tile Space Graph (TSG)
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8 Optimizing tile size
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9 Discussion
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References
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Chapter 14. Systolic Loops
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Abstract
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1. SUMMARY
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2. TARGET PROCESSOR ARCHITECTURE
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3. EFFICIENT PARALLEL LOOPS
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4. UNIFORM RECURRENCE EQUATIONS AND SYSTOLIC ARRAYS
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5. SYSTOLIC ARRAYS, WAVEFRONTS AND LOOP SKEWING
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6. SYSTOLIC LOOP PROCESSING
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7. OTHER WORK
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References
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Chapter 15. An Optimizing C* Compiler for a Hypercube Multicomputer
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Abstract
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1 Introduction
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2 The C* Programming Language
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3 Design of the C* Compiler
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4 The Optimizer
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5 Supporting Program Analysis
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6 Evaluating the Optimizer
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7 Summary
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References
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Chapter 16. The Paragon Programming Paradigm and Distributed Memory Multicomputers
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Abstract
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1 Introduction
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2 Programming in Paragon
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3 Paragon Primitive Implementation
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4 Conclusion
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References
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