Virtual Institute — High Productivity Supercomputing

2019 Workshop on Programming and Performance Visualization Tools

Workshop website

ProTools 2019

Contact

E-mail: sc-ws-protools@info.supercomputing.org

Date and Location

November 17, 2019

Held in conjunction with SC19: The International Conference for High Performance Computing, Networking, Storage and Analysis Denver, Colorado, USA

Sponsors:
This workshop is supported by SPPEXA, the DFG Priority Program 1648 Software for Exascale Computing.

Description

Understanding program behavior is critical to overcome the expected architectural and programming complexities, such as limited power budgets, heterogeneity, hierarchical memories, shrinking I/O bandwidths, and performance variability, that arise on modern HPC platforms. To do so, HPC software developers need intuitive support tools for debugging, performance measurement, analysis, and tuning of large-scale HPC applications. Moreover, data collected from these tools such as hardware counters, communication traces, and network traffic can be far too large and too complex to be analyzed in a straightforward manner. We need new automatic analysis and visualization approaches to help application developers intuitively understand the multiple, interdependent effects that algorithmic choices have on application correctness or performance. The ProTools workshop combines two prior SC workshops: the Workshop on Visual Performance Analytics (VPA) and the Workshop on Extreme-Scale Programming Tools (ESPT).

The Workshop on Programming and Performance Visualization Tools (ProTools) intends to bring together HPC application developers, tool developers, and researchers from the visualization, performance, and program analysis fields for an exchange of new approaches to assist developers in analyzing, understanding, and optimizing programs for extreme-scale platforms.

Topics

  • Performance tools for scalable parallel platforms
  • Debugging and correctness tools for parallel programming paradigms
  • Scalable displays of performance data
  • Case studies demonstrating the use of performance visualization in practice
  • Program development tool chains (incl. IDEs) for parallel systems
  • Methodologies for performance engineering
  • Data models to enable scalable visualization
  • Graph representation of unstructured performance data
  • Tool technologies for extreme-scale challenges (e.g., scalability, resilience, power)
  • Tool support for accelerated architectures and large-scale multi-cores
  • Presentation of high-dimensional data
  • Visual correlations between multiple data source
  • Measurement and optimization tools for networks and I/O
  • Tool infrastructures and environments
  • Human-Computer Interfaces for exploring performance data
  • Multi-scale representations of performance data for visual exploration
  • Application developer experiences with programming and performance tools

Program

The workshop program can be found on the main workshop website.

Organizing committee

Abhinav Bhatele, University of Maryland, USA
David Böhme, Lawrence Livermore National Laboratory, USA
Tom Vierjahn, Westphalian University of Applied Sciences, Germany
Josef Weidendorfer, Leibniz Supercomputing Centre Munich, Germany
Felix Wolf, Technical University Darmstadt, Germany

Program committee

Jean-Baptiste Besnard, ParaTools, France
Harsh Bhatia, Lawrence Livermore National Laboratory
Holger Brunst, TU Dresden
Alexandru Calotoiu, Technical University Darmstadt
Karl Fürlinger, Ludwig Maximilian University of Munich, Germany
Todd Gamblin, Lawrence Livermore National Laboratory
Judit Gimenez, Barcelona Supercomputing Center
Marc-Andre Hermanns, RWTH Aachen University
Katherine Isaacs, University of Arizona
Andreas Knüpfer, Technical University Dresden,Germany
Joshua A. Levine, University of Arizona
John Linford, ARM, USA
Allen D. Malony, University of Oregon, USA
Naoya Maruyama, Lawrence Livermore National Laboratory
Bart Miller, University of Wisconsin Madison, USA
Paul Rosen, University of South Florida
Martin Schulz, Technical University Munich, Germany
Nathan Tallent, Pacific Northwestern National Laboratory, USA
Brian Wylie, Jülich Supercomputing Centre, Germany