Tools for High Performance Computing 2014: Proceedings of the 8th International Workshop on Parallel Tools for High Performance Computing, October 2014, HLRS, Stuttgart, Germany
Автор: Christoph Niethammer Название: Tools for High Performance Computing 2014: Proceedings of the 8th International Workshop on Parallel Tools for High Performance Computing, October 2014, HLRS, Stuttgart, Germany Издательство: Springer Год: 2015 ISBN: 9783319160115 / 3319160117 Язык: English Формат: pdf Размер: 10,3 mb Страниц: 229
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 world use thousands of nodes in which classical CPUs are combined with accelerator cards in order to enhance their compute power and energy efficiency. This complexity can only be mastered with adequate development and optimization tools. Key topics addressed by these tools include parallelization on heterogeneous systems, performance optimization for CPUs and accelerators, debugging of increasingly complex scientific applications, and optimization of energy usage in the spirit of green IT.
Scalasca v2: Back to the Future Ilya Zhukov, Christian Feld, Markus Geimer, Michael Knobloch, Bernd Mohr, and Pavel Saviankou
Allinea MAP: Adding Energy and OpenMP Profiling Without Increasing Overhead Christopher January, Jonathan Byrd, Xavier Or?, and Mark O’Connor
DiscoPoP: A Profiling Tool to Identify Parallelization Opportunities Zhen Li, Rohit Atre, Zia Ul-Huda, Ali Jannesari, and Felix Wolf
Tareador: The Unbearable Lightness of Exploring Parallelism Vladimir Subotic, Arturo Campos, Alejandro Velasco, Eduard Ayguade, Jesus Labarta, and Mateo Valero
Tuning Plugin Development for the Periscope Tuning Framework Isa?as A. Compr?s Ure?a and Michael Gerndt
Combining Instrumentation and Sampling for Trace-Based Application Performance Analysis Thomas Ilsche, Joseph Schuchart, Robert Sch?ne, and Daniel Hackenberg
Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation Damien Dosimont, Youenn Corre, Lucas Mello Schnorr, Guillaume Huard, and Jean-Marc Vincent
Integrating Critical-Blame Analysis for Heterogeneous Applications into the Score-PWorkflow Felix Schmitt, Robert Dietrich, and Jonas Stolle
Studying Performance Changes with Tracking Analysis Germ?n Llort, Harald Servat, Juan Gonzalez, Judit Gimenez, and Jes?s Labarta
A Flexible Data Model to Support Multi-domain Performance Analysis Martin Schulz, Abhinav Bhatele, David B?hme, Peer-Timo Bremer, Todd Gamblin, Alfredo Gimenez, and Kate Isaacs
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