3rd Workshop on Visual Performance Analysis (VPA)

Held in conjunction with SC16: The International Conference on High Performance Computing, Networking, Storage and Analysis

Salt Lake City, USA

November 18, 2016



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Over the last decades an incredible amount of resources has been devoted to building ever more powerful supercomputers. However, exploiting the full capabilities of these machines is becoming exponentially more difficult with each new generation of hardware. To help understand and optimize the behavior of massively parallel simulations the performance analysis community has created a wide range of tools and APIs to collect performance data, such as flop counts, network traffic or cache behavior at the largest scale. However, this success has created a new challenge, as the resulting data is far too large and too complex to be analyzed in a straightforward manner. Therefore, new automatic analysis approaches must be developed to allow application developers to intuitively understand the multiple, interdependent effects that their algorithmic choices have on the final performance.

This workshop will bring together researchers and practitioners from the areas of performance analysis, application optimization, visualization, and data analysis and provide a forum to discuss novel ideas on how to improve performance understanding, analysis and optimization through novel techniques in scientific and information visualization.

Workshop Topics

  • Scalable displays of performance data
  • Interactive visualization of performance data
  • Data models to enable data analysis and visualization
  • Graph representation of unstructured performance data
  • Collection and representation of meta data to enable fine grained attribution
  • Message trace visualization
  • Memory and network traffic visualization
  • Representation of hardware architectures

Paper Submission

We solicit two types of papers both covering original and previously unpublished ideas: 8 page regular papers and 4 page position papers. To be considered, your manuscript should be formatted according to the double-column IEEE format for Conference Proceedings (IEEEtran LaTeX Class (template) V1.8 packages and IEEEtran V1.12 BibTeX (bibliography)). Margins and font sizes should not be modified. The templates for "IEEEtran LaTeX Class (template) V1.8 packages and IEEEtran V1.12 BibTeX (bibliography)" can be found at http://www.ieee.org/conferences_events/conferences/publishing/templates.html

All papers must be submitted through Easychair at: https://easychair.org/conferences/?conf=vpa2016


All logistics, including registration, hotel reservations, and visa requests, will be handled by SC16.

Important Dates

  • August 15th: submission deadline for full papers
  • September 12th: notification of acceptance
  • October 3rd: final paper and copyrights due


Friday Nov 18th

Welcome and Introduction
Keynote: State of Practice: Visual Performance Analysis
Katherine Isaacs, University of Arizona
Edge Bundling for Visualizing Communication Behavior
Ronny Brendel, Michael Heyde, Holger Brunst, Tobias Hilbrich and Matthias Weber
Coffee Break
Using Directed Variance to Identify Meaningful Views in Call-Path Performance Profiles
Tom Vierjahn, Marc-André Hermanns, Bernd Mohr, Matthias S. Müller, Torsten W. Kuhlen and Bernd Hentschel
Analyzing Dynamic Task-Based Applications on Hybrid Platforms: An Agile Scripting Approach
Vinícius Garcia Pinto, Luka Stanisic, Arnaud Legrand, Lucas Mello Schnorr, Samuel Thibault and Vincent Danjean
VIPACT: A Visualization Interface for Analyzing Calling Context Trees
Huu Tan Nguyen, Lai Wei, Abhinav Bhatele, Todd Gamblin, David Boehme, Martin Schulz, Kwan-Liu Ma and Peer-Timo Bremer



Workshop Organizers

  • Peer-Timo Bremer, Lawrence Livermore National Laboratory
  • Judit Gimenez, Barcelona Supercomputing Center
  • Joshua Levine, University of Arizona
  • Martin Schulz, Lawrence Livermore National Laboratory


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Program Committee

  • Holger Brunst, TU Dresden
  • Remco Chang, Tufts University
  • Hank Childs, University of Oregon
  • Damien Dosimont, Barcelona Supercomputing Center
  • Nivan Ferreira, University of Arizona
  • Karl Fuerlinger, LMU München
  • Todd Gamblin, Lawrence Livermore National Laboratory
  • Marc-Andre Hermanns, Jülich Supercomputing Centre
  • Kevin Huck, University of Oregon
  • Kate Isaacs, University of Arizona
  • Naoya Maruyama, RIKEN AICS
  • John Mellor-Crummey, Rice University
  • Bernd Mohr, Jülich Supercomputing Centre
  • Ananya Muddukrishna, KTH Royal Institute of Technology
  • Matthias Mueller, RWTH Aachen University
  • Valerio Pascucci, University of Utah
  • Paul Rosen, University of South Florida
  • Carlos Scheidegger, University of Arizona
  • Felix Wolf, Technische Universität Darmstadt