HPDAV 2016 - High Performance Data Analysis and Visualization (HPDAV) 2016

While the purpose of visualization and analysis is insight, realizing that objective requires solving complex problems related to crafting or adapting algorithms and applications to take advantage of evolving architectures, and to solve increasingly complex data understanding problems for ever larger and more complex data. These architectures, and the systems from which they are built, have increasingly deep memory hierarchies, increasing concurrency, decreasing relative per-core/per-node I/O capacity, lessening memory per core, are increasingly prone to failures, and face power limitations.
The purpose of this workshop is to bring together researchers, engineers, and architects of data-intensive computing technologies, which span visualization, analysis, and data management, to present and discuss research topics germane to high performance data analysis and visualization. Specifically, this workshop focuses on research topics related to adapting/creating algorithms, technologies, and applications for use on emerging computational architectures and platforms.
The workshop format includes traditional research papers (8-10 pages) for in-depth topics, short papers (4 pages) for works in progress, and a panel discussion.
Paper Topics
We invite papers on original, unpublished research in the following topic areas under the general umbrella of high performance visualization and analysis:
Increasing concurrency at the node level, and at the systemwide level.
Optimizations for improving performance, e.g., decreasing runtime, leveraging a deepening memory hierarchy, reducing data movement, reducing power consumption.
Applications of visualization and analysis, where there is a strong thematic element related to being able to solve a larger or more complex problem because of algorithmic or design advances that take advantage of increasing concurrency, architectural features, etc.
Data analysis and/or visualization systems/designs/architectures having an emphasis upon scalability, resilience, high-throughput/high-capacity, and that are able to take advantage of emerging architectures.
We anticipate a portion of the program to be dedicated to 20-minute research talks, and a portion to be dedicated to 10-minute short talks.