License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.4.1.17
URN: urn:nbn:de:0030-drops-45166
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2014/4516/
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Bremer, Peer-Timo ; Mohr, Bernd ; Pascucci, Valerio ; Schulz, Martin
Weitere Beteiligte (Hrsg. etc.): Peer-Timo Bremer and Bernd Mohr and Valerio Pascucci and Martin Schulz

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing (Dagstuhl Perspectives Workshop 14022)

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dagrep_v004_i001_p017_s14022.pdf (0.7 MB)

Abstract

In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on
"Connecting Performance Analysis and Visualization to Advance Extreme Scale
Computing". The event brought together two previously separate communities - from Visualization and HPC Performance Analysis - to discuss a long term joined research agenda. The goal was to identify and address the challenges in using visual representations to understand and optimize the performance of extreme-scale applications running on today's most powerful computing systems like climate modeling, combustion, material science or astro-physics simulations.

BibTeX - Entry

@Article{bremer_et_al:DR:2014:4516,
  author =	{Peer-Timo Bremer and Bernd Mohr and Valerio Pascucci and Martin Schulz},
  title =	{{Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing (Dagstuhl Perspectives Workshop 14022)}},
  pages =	{17--35},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{4},
  number =	{1},
  editor =	{Peer-Timo Bremer and Bernd Mohr and Valerio Pascucci and Martin Schulz},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2014/4516},
  URN =		{urn:nbn:de:0030-drops-45166},
  doi =		{10.4230/DagRep.4.1.17},
  annote =	{Keywords: Large scale data presentation and analysis, Exascale class machine optimization, Performance data analysis and root cause detection, High dimensional }
}

Keywords: Large scale data presentation and analysis, Exascale class machine optimization, Performance data analysis and root cause detection, High dimensional
Collection: Dagstuhl Reports, Volume 4, Issue 1
Issue Date: 2014
Date of publication: 23.04.2014

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