
Tools for High Performance Computing 2014
Description
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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. This book represents the proceedings of the 8 th International Parallel Tools Workshop, held October 1-2, 2014 in Stuttgart, Germany - which is a forum to discuss the latest advancements in theparallel tools.
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Content
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.
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