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Documents authored by Pascucci, Valerio

Document
DOI: 10.4230/DagMan.5.1.1
Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022)

Authors: Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, Martin Schulz, Todd Gamblin, and Holger Brunst

Published in: Dagstuhl Manifestos, Volume 5, Issue 1 (2015)

Abstract
In the first week of January 2014 Schloss Dagstuhl hosted a Perspectives Workshop on “Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing”. The workshop brought together two previously separate communities – from Visualization and Performance Analysis for High Performance Computing – to discuss a long term joint 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.
Cite as

Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, Martin Schulz, Todd Gamblin, and Holger Brunst. Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022). In Dagstuhl Manifestos, Volume 5, Issue 1, pp. 1-24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{bremer_et_al:DagMan.5.1.1,
  author =	{Bremer, Peer-Timo and Mohr, Bernd and Pascucci, Valerio and Schulz, Martin and Gamblin, Todd and Brunst, Holger},
  title =	{{Connecting Performance Analysis and Visualization (Dagstuhl Perspectives Workshop 14022)}},
  pages =	{1--24},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2015},
  volume =	{5},
  number =	{1},
  editor =	{Bremer, Peer-Timo and Mohr, Bernd and Pascucci, Valerio and Schulz, Martin and Gamblin, Todd and Brunst, Holger},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.5.1.1},
  URN =		{urn:nbn:de:0030-drops-55099},
  doi =		{10.4230/DagMan.5.1.1},
  annote =	{Keywords: Performance Analysis, Performance Tools, Information Visualization, Visual Analytics}
}
Document
DOI: 10.4230/DagRep.4.1.17
Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing (Dagstuhl Perspectives Workshop 14022)

Authors: Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, and Martin Schulz

Published in: Dagstuhl Reports, Volume 4, Issue 1 (2014)

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.
Cite as

Peer-Timo Bremer, Bernd Mohr, Valerio Pascucci, and Martin Schulz. Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing (Dagstuhl Perspectives Workshop 14022). In Dagstuhl Reports, Volume 4, Issue 1, pp. 17-35, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@Article{bremer_et_al:DagRep.4.1.17,
  author =	{Bremer, Peer-Timo and Mohr, Bernd and Pascucci, Valerio and Schulz, Martin},
  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 =	{Bremer, Peer-Timo and Mohr, Bernd and Pascucci, Valerio and Schulz, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.1.17},
  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}
}
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