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This book shows by example how to solve complex scientific problems with programs that run on high performance computers. Combining case studies from a variety of problem domains and written by experts in those domains, it shows how to map or transform an abstract problem into a concrete solution that executes rapidly and efficiently on available high performance hardware. Each chapter describes some technical or engineering problem to which computers are commonly applied, then leads readers through the choice and development of appropriate algorithms and through an evaluation of resulting implementations. Although each chapter centers on a single application area, they all focus on general techniques useful for any area rather than on application-specific details. Readers should have some programming experience in a language like FORTRAN or C and some familiarity with computing issues involved in scientific problems; but no expertise in parallel computing is required.
This book investigates the methodology for mapping complex scientific problems onto parallel and vector computing architectures to achieve efficient execution. Author Gary Sabot compiles contributions from domain experts to demonstrate how abstract computational challenges are transformed into concrete, high-performance software solutions. The text emphasizes generalizable techniques over application-specific coding, providing a framework for developers to evaluate algorithm performance across diverse hardware environments.
What You Will Find
Experts identify this as a practical resource for programmers transitioning into high-performance computing who already possess foundational knowledge in languages like C or FORTRAN. Readers frequently note that the book effectively bridges the gap between theoretical computer science and applied engineering through its focus on transferable problem-solving techniques.
Page Count:
246
Publication Date:
1995-01-01
Publisher:
Addison-Wesley
ISBN-10:
0201598302
ISBN-13:
9780201598308
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