International Workshop on Visual Analytics in Supercomputing and Performance Engineering (VASPE ‘19)
Held in conjunction with ICPE ‘19: The 10th ACM/SPEC International Conference on Performance Engineering
Both high performance computing (HPC) and performance engineering (PE) experts are facing the challenge of analyzing, comparing, visualizing, and reasoning about ever increasing volumes of performance-related data. While HPC typically deals with massively parallel simulation codes being executed on supercomputers, PE focuses on distributed, reliable software systems.
Due to the scale of performance-related data and the open-ended nature of analyzing it, visualization (VIS) and data analytics are often the only feasible tools to comprehend, debug, and improve the performance behavior of systems and/or codes. This is becoming ever more important, since the scale of performance-related data keeps rapidly growing. However the research communities in HPC, PE, and VIS are mostly disjunct.
VASPE ‘19 aims at gathering experts from (i) the HPC community, (ii) the PE community, and (iii) the VIS community in order to breed cross-community algorithms, techniques, and systems for analyzing and visualizing performance-related data.
Topics include, but are not limited to:
- 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
- Data analytics of historical performance data
- Machine learning or statistical techniques for data exploration
Call for Papers
We solicit 6–8 page full papers and 2–4 page short papers that focus on techniques at the intersection of the three communities HPC, PE, and VIS that either use visualization techniques to display large scale performance data or that develop new visualization or visual analytics methods that help create new insights. We welcome submissions presenting novel and experimental ideas as well as tool descriptions.
Papers must be submitted as a PDF file in the ACM Standard proceedings format, and formatted for 8.5” x 11” (U.S. Letter). The 4-page and 8-page limits include figures, tables, and references.
Papers will be peer-reviewed by members of the program committee and accepted papers will be published by ACM as part of ICPE 2019 proceedings. Accepted papers will also be presented during the workshop as a paper talk (~20 min) or a lightning presentation (~10 min).
All papers must be submitted through EasyChair.
- Submission deadline: Jan 7, 2019
- Notification of acceptance: Feb 1, 2019
- Camera-ready deadline: Feb 15, 2019
- Workshop: TBD, one day between 6th and 12th April 2019
Davide Arcelli, Università de L’Aquila, Italy
Fabian Beck, University of Duisburg-Essen, Germany
Cor-Paul Bezemer, University of Alberta, Canada
David Boehme, Lawrence Livermore National Laboratory, USA
Jinfu Chen, Concordia University, Canada
Patrick Gralka, University of Stuttgart, Germany
Kevin Griffin, Lawrence Livermore National Laboratory, USA
André van Hoorn, University of Stuttgart, Germany
Philipp Leitner, Chalmers – University of Gothenburg, Sweden
Leonel Merino, University of Stuttgart, Germany
Oliver Moseler, Trier University, Germany
Dušan Okanović, University of Stuttgart, Germany
Paul Rosen, University of South Florida, USA
Juan Pablo Sandoval Alcocer, Universidad Católica Boliviana, Bolivia
Luka Stanisic, Max Planck Computing and Data Facility, Germany