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By: David H. Bailey (Edited by) , Robert F. Lucas (Edited by) , Samuel Williams (Edited by)
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Describing useful current research in modern performance science and engineering, this book helps real-world users of parallel computer systems to better understand both the performance vagaries arising in scientific applications and the practical means for improving performance. Some of the most notable experts in the field focus on the areas of performance monitoring, performance analysis, performance modeling, automatic performance tuning, and application tuning. The book also provides an overview of modern computer architecture. It includes examples from such areas as solid mechanics, astrophysics, quantum chromodynamics, molecular dynamics, and environmental science.
With contributions from some of the most notable experts in the field, Performance Tuning of Scientific Applications presents current research in performance analysis. The book focuses on the following areas.
Performance monitoring: Describes the state of the art in hardware and software tools that are commonly used for monitoring and measuring performance and managing large quantities of data
Performance analysis: Discusses modern approaches to computer performance benchmarking and presents results that offer valuable insight into these studies
Performance modeling: Explains how researchers deduce accurate performance models from raw performance data or from other high-level characteristics of a scientific computation
Automatic performance tuning: Explores ongoing research into automatic and semi-automatic techniques for optimizing computer programs to achieve superior performance on any computer platform
Application tuning: Provides examples that show how the appropriate analysis of performance and some deft changes have resulted in extremely high performance
Performance analysis has grown into a full-fledged, sophisticated field of empirical science. Describing useful research in modern performance science and engineering, this book helps real-world users of parallel computer systems to better understand both the performance vagaries arising in scientific applications and the practical means for improving performance.
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