CfP: 4th International Workshop on Visual Performance Analysis (VPA17)

Held in conjunction with SC17: The International Conference on High Performance Computing, Networking, Storage and Analysis

Denver, CO, USA November 17, 2017

https://vpa17.github.io/

Submission Deadline: July 31, 2017

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 and
visualization 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 from the fields of
performance analysis and visualization to discuss new approaches of
applying visualization and visual analytics techniques to large scale
applications.

Workshop Topics:

* Scalable displays of performance data
* Data models to enable scalable visualization
* Graph representation of unstructured performance data
* Presentation of high-dimensional data
* Visual correlations between multiple data source
* Human-Computer Interfaces for exploring performance data
* Multi-scale representations of performance data for visual exploration

Paper Submission:

Solicit papers of up to 8 pages as well as 4 page short papers in
standard ACM format that focus on techniques in the intersection of the
two communities and either use visualization techniques to display large
scale performance data or that develop new visualization or visual
analytics methods that help create new insights.

All papers must be submitted through Easychair at:
https://easychair.org/conferences/?conf=vpa2017

Important Dates:

* Submission deadline: July 31, 2017
* Notification of acceptance: September 18, 2017
* Camera-ready deadline: October 9, 2017

Workshop Chairs:

* Fabian Beck, University of Duisburg-Essen
* Abhinav Bhatele, Lawrence Livermore National Laboratory
* Judit Gimenez, Barcelona Supercomputing Center
* Joshua A. Levine, University of Arizona

Contact:

* vpa17@easychair.org

Steering Committee:

* Peer-Timo Bremer, Lawrence Livermore National Laboratory
* Bernd Mohr, Juelich Supercomputing Center
* Valerio Pascucci, University of Utah
* Martin Schulz, Lawrence Livermore National Laboratory

Program Committee:

* Harsh Bhatia, Lawrence Livermore National Laboratory
* Holger Brunst, Technical University Dresden
* Alexandru Calotoiu, Technical University Darmstadt
* Todd Gamblin, Lawrence Livermore National Laboratory
* Marc-Andre Hermanns, Juelich Supercomputing Center
* Kevin Huck, University of Oregon
* Katherine Isaacs, University of Arizona
* Yarden Livnat, University of Utah
* Naoya Maruyama, Lawrence Livermore National Laboratory
* Bernd Mohr, Juelich Supercomputing Center
* 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
* Chad Steed, Oak Ridge National Laboratory

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