[hpc-announce] ProTools 2019: Call for Papers

Bhatele, Abhinav bhatele1 at llnl.gov
Mon Jun 17 02:24:00 CDT 2019

                                 Call for Papers

   Workshop on Programming and Performance Visualization Tools (ProTools 19)
           Held in conjunction with SC19, in cooperation with TCHPC.

                                Denver, CO, USA
                               November 17, 2019


                    Submission Deadline: August 26, 2019

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.

Workshop Topics:

Topics include, but are not limited to:
* 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

Paper Submission:

We solicit 8-page full papers as well as 4-page short papers and position
papers that focus on performance, debugging, and correctness tools for parallel
programming paradigms as well as techniques and case studies at the
intersection of performance analysis and visualization.

Papers must be submitted in PDF format (readable by Adobe Acrobat Reader 5.0
and higher) and formatted for 8.5” x 11” (U.S. Letter). Submissions are limited
to 8 pages in the IEEE Conference format
(https://www.ieee.org/conferences/publishing/templates.html), using the
sample-sigconf template.  The 8-page limit includes figures, tables, and

All papers must be submitted through the Supercomputing 2019 Linklings site:

Important Dates:

* Submission deadline: August 26, 2019 (AoE)
* Notification of acceptance: September 30, 2019 (AoE)
* Camera-ready deadline: October 7, 2019 (AoE)
* Workshop: November 17, 2019

Workshop Chairs:

Abhinav Bhatele, Lawrence Livermore National Laboratory, USA
David Boehme, Lawrence Livermore National Laboratory, USA
Tom Vierjahn, Westphalian University of Applied Sciences, Germany
Josef Weidendorfer, Leibniz Supercomputing Centre Munich, Germany

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