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Tools for High Performance Computing 2009
Details
As more and more hardware platforms support parallelism, parallel programming is gaining momentum. Applications can only leverage the performance of multi-core processors or graphics processing units if they are able to split a problem into smaller ones that can be solved in parallel. The challenges emerging from the development of parallel applications have led to the development of a great number of tools for debugging, performance analysis and other tasks. The proceedings of the 3rd International Workshop on Parallel Tools for High Performance Computing provide a technical overview in order to help engineers, developers and computer scientists decide which tools are best suited to enhancing their current development processes.
Includes supplementary material: sn.pub/extras
Inhalt
PERISCOPE: An Online-Based Distributed Performance Analysis Tool.- Comprehensive Performance Tracking with Vampir 7.- Performance Analysis and Workload Characterization with IPM.- Recent Developments in the Scalasca Toolset.- MUST: A Scalable Approach to Runtime Error Detection in MPI Programs.- HPC Profiling with the Sun Studio™ Performance Tools.- Performance Tuning of x86 OpenMP Codes with MAQAO.- Scalable Parallel Debugging with g-Eclipse.- New Analysis Techniques in the CEPBA-Tools Environment.- The Importance of Run-Time Error Detection.- Collecting Performance Data with PAPI-C.- ISP Tool Update: Scalable MPI Verification.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783642437526
- Editor Matthias S. Müller, Wolfgang E. Nagel, Alexander Schulz, Michael M. Resch
- Sprache Englisch
- Auflage 2010
- Größe H235mm x B155mm x T12mm
- Jahr 2014
- EAN 9783642437526
- Format Kartonierter Einband
- ISBN 3642437524
- Veröffentlichung 07.10.2014
- Titel Tools for High Performance Computing 2009
- Untertitel Proceedings of the 3rd International Workshop on Parallel Tools for High Performance Computing, September 2009, ZIH, Dresden
- Gewicht 312g
- Herausgeber Springer Berlin Heidelberg
- Anzahl Seiten 200
- Lesemotiv Verstehen
- Genre Informatik