UID:
edoccha_9960073714502883
Format:
1 online resource (323 p.)
ISBN:
1-4832-9538-9
Series Statement:
Advances in Parallel Computing ; Volume 3
Content:
Papers presented within this volume cover a wide range of topics related to programming distributed memory machines. Distributed memory architectures, although having the potential to supply the very high levels of performance required to support future computing needs, present awkward programming problems. The major issue is to design methods which enable compilers to generate efficient distributed memory programs from relatively machine independent program specifications. This book is the compilation of papers describing a wide range of research efforts aimed at easing the task of programmin
Note:
Description based upon print version of record.
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Front Cover; Languages, Compilers and Run-Time Environments for Distributed Memory Machines; Copyright Page; PREFACE; Table of Contents; Chapter 1. SUPERB: Experiences and Future Research; Abstract; 1 Introduction; 2 Program Splitting; 3 Data Partitioning; 4 Interprocedural Partitioning Analysis; 5 Automatic Insertion of Masking and Communication; 6 Optimization; 7 System Structure; 8 Current and Future Research; 9 Conclusion; References; Chapter 2. Scientific Programming Languages for Distributed Memory Multiprocessors : Paradigms and Research Issues; Abstract; 1. Introduction
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2. An Emerging Paradigm for Distributed Parallel Languages3. An Example of the Paradigm : The DINO Language; 4. Research Issues Regarding Virtual Parallel Computers; 5. Research Issues Regarding Distributed Data Structures; 6. Research Issues Regarding Models of Parallel Computation; 7. Additional Research Issues Regarding Communication Features; 8. Research Issues Regarding Support for Complex Parallel Programs; 9. References; Chapter 3. VIENNA FORTRAN - A FORTRAN LANGUAGE EXTENSION FOR DISTRIBUTED MEMORY MULTIPROCESSORS*; Abstract; 1 Introduction; 2 The Basic Features of Vienna Fortran
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3 Examples4 Related Work; 5 Conclusions; Acknowledgments; References; Chapter 4. Compiler Parallelization of SIMPLE for a Distributed Memory Machine; Abstract; 1 Introduction; 2 What is SIMPLE?; 3 Machine Model; 4 Data Distribution; 5 Code Generation; 6 Results and Analysis; 7 Summary; Acknowledgements; References; Chapter 5. Applications of the ""Phase Abstractions"" for Portable and Scalable Parallel Programming; Abstract; 1 Introduction; 2 Preliminaries; 3 Jacobi Iteration Example; 4 Specification of the Processes, Level X; 5 Global Data Declaration; 6 Phase Definitions, Y Level
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7 Main Program Body, Æ Level8 Commentary on the Program and Abstractions; 9 Conclusions; 10 Acknowledgments; References; Chapter 6. Nicke - C Extensions for Programming on Distributed-Memory Machines; Abstract; 1 Introduction; 2 Basic Constructs; 3 Shared Variables; 4 Impiementation; 5 Conclusion; References; Chapter 7. A Static Performance Estimator in the Fortran D Programming System; Abstract; 1. INTRODUCTION; 2. DISTRIBUTED MEMORY PROGRAMMING MODEL; 3. CHOOSING THE DATA DECOMPOSITION SCHEME; 4. AN EXAMPLE; 5. THE TRAINING SET METHOD OF PERFORMANCE ESTIMATION
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6. THE PERFORMANCE ESTIMATION ALGORITHM7. A PROTOTYPE IMPLEMENTATION; 8. CONCLUSION AND FUTURE WORK; References; Chapter 8. Compiler Support for Machine-Independent Parallel Programming in Fortran D; Abstract; 1 Introduction; 2 Fortran D; 3 Basic Compilation Strategy; 4 Compilation of Whole Programs; 5 Validation; 6 Relationship to Other Research; 7 Conclusions and Future Work; 8 Acknowledgements; References; Chapter 9. PANDORE: A System to Manage Data Distribution; Abstract; 1. INTRODUCTION; 2. OVERVIEW OF THE PANDORE SYSTEM; 3. THE PANDORE LANGUAGE; 4. FURTHER WORK; References
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Chapter 10. DISTRIBUTED MEMORY COMPILER METHODS FOR IRREGULAR PROBLEMS - DATA COPY REUSE AND RUNTIME PARTITIONING1
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English
Additional Edition:
ISBN 0-444-88712-1
Language:
English
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