Practical Parallel Computing (eBook, PDF)
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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. Thi...
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.
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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