Tools for High Performance Computing 2014 Front Cover

Tools for High Performance Computing 2014

  • Length: 229 pages
  • Edition: 2015
  • Publisher:
  • Publication Date: 2015-08-11
  • ISBN-10: 3319160117
  • ISBN-13: 9783319160115
Description

Tools for High Performance Computing 2014: Proceedings of the 8th International Workshop on Parallel Tools for High Performance Computing, October 2014, HLRS, Stuttgart, Germany

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 8th International Parallel Tools Workshop, held October 1-2, 2014 in Stuttgart, Germany – which is a forum to discuss the latest advancements in the parallel tools.

Table of Contents

Chapter 1. Scalasca v2: Back to the Future
Chapter 2. Allinea MAP: Adding Energy and OpenMP Profiling Without Increasing Overhead
Chapter 3. DiscoPoP: A Profiling Tool to Identify Parallelization Opportunities
Chapter 4. Tareador: The Unbearable Lightness of Exploring Parallelism
Chapter 5. Tuning Plugin Development for the Periscope Tuning Framework
Chapter 6. Combining Instrumentation and Sampling for Trace-Based Application Performance Analysis
Chapter 7. Ocelotl: Large Trace Overviews Based on Multidimensional Data Aggregation
Chapter 8. Integrating Critical-Blame Analysis for Heterogeneous Applications into the Score-P Workflow
Chapter 9. Studying Performance Changes with Tracking Analysis
Chapter 10. A Flexible Data Model to Support Multi-domain PerformanceAnalysis

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