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Performance Tuning of Scientific Applications

Paperback Engels 2019 9780367383305
€ 101,52
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Samenvatting

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.

Read about the book on HPCwire and insideHPC

Specificaties

ISBN13:9780367383305
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:400
Uitgever:Taylor & Francis Ltd

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Inhoudsopgave

Introduction. Parallel Computer Architecture. Software Interfaces to Hardware Counters. Measurement and Analysis of Parallel Program Performance using TAU and HPCToolkit. Trace-Based Tools. Large-Scale Numerical Simulations on High-End Computational Platforms. Performance Modeling: The Convolution Approach. Analytic Modeling for Memory Access Patterns Based on Apex-MAP. The Roofline Model. End-to-End Auto-Tuning with Active Harmony. Languages and Compilers for Auto-Tuning. Empirical Performance Tuning of Dense Linear Algebra Software. Auto-Tuning Memory-Intensive Kernels for Multicore. Flexible Tools Supporting a Scalable First-Principles MD Code. The Community Climate System Model. Tuning an Electronic Structure Code. Bibliography. Index.

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