Tools for high performance computing 2014 : proceedings of the 8th International Workshop on Parallel Tools for High Performance Computing, October 2014, HLRS, Stuttgart, Germany / Christoph Niethammer, José Gracia, Andreas Knü̈pfer, Michael M. Resch, Wolfgang E. Nagel, editors.
Numerical simulation and modelling using High Performance Computing has evolved into an established technique in academic and industrial research. At the same time, the High Performance Computing infrastructure is becoming ever more complex. For instance, most of the current top systems around the w...
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| Format: | Ebook |
| Language: | English |
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Springer,
[2015]
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| Online Access: | Springer eBooks |
Table of Contents:
- Ilya Zhukov, Christian Feld, Markus Geimer, Michael Knobloch, Bernd Mohr and Pavel Saviankou: Scalasca v2: Back To The Future
- Christopher January, Jonathan Byrd, Xavier Oró, and Mark O'Connor: Allinea MAP: Adding Energy and OpenMP Profiling Without Increasing Overhead
- Zhen Li, Rohit Atre, Zia Ul-Huda, Ali Jannesari, and Felix Wolf: DiscoPoP: A Profiling Tool to Identify Parallelization Opportunities
- Vladimir Subotic, Arturo Campos, Alejandro Velasco, Eduard Ayguade, Jesus Labarta, and Mateo Valero: Tareador: The Unbearable Lightness of Exploring Parallelism
- Isaías A. Comprés Ureña, and Michael Gerndt: Tuning Plugin Development for the Periscope Tuning Framework
- Thomas Ilsche, Joseph Schuchart, Robert Schöne and Daniel Hackenberg: Combining Instrumentation and Sampling for Trace-based Application Performance Analysis
- Damien Dosimont, Youenn Corre, Lucas Mello Schnorr, Guillaume Huard and Jean-Marc Vincent: Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation
- Felix Schmitt, Robert Dietrich and Jonas Stolle: Integrating Critical-Blame Analysis for Heterogeneous Applications into the Score-P Workflow
- Germán Llort, Harald Servat, Juan Gonzalez, Judit Gimenez and Jesús Labarta: Studying Performance Changes with Tracking Analysis
- Martin Schulz, Abhinav Bhatele, David Böhme1, Peer-Timo Bremer, Todd Gamblin, Alfredo Gimenez and Kate Isaacs: A Flexible Data Model to Support Multi-Domain Performance Analysis.