Kitware will be exhibiting at SC12 at Booth 3951, where we will showcase and demonstrate some of our newest work.

In addition, we will present two collaborative tutorials: Large Scale Visualization with ParaView and In-Situ Visualization with Catalyst.

Large Scale Visualization with ParaView, Sunday November 11, 8:30 am – 12:00pm

Presenters: Kenneth Moreland, W. Alan Scott & Nathan Fabian from Sandia National Laboratories, and Utkarsh Ayachit & Robert Maynard from Kitware.

ABSTRACT: ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. Designed to be configurable, extendible, and scalable, ParaView is built upon the Visualization Toolkit (VTK) to allow rapid deployment of visualization components. This tutorial presents the architecture of ParaView and the fundamentals of parallel visualization. Attendees will learn the basics of using ParaView for scientific visualization with hands-on lessons. The tutorial features detailed guidance in visualizing the massive simulations run on today’s supercomputers and an introduction to scripting and extending ParaView. Attendees should bring laptops to install ParaView and follow along with the demonstrations.

In-Situ Visualization with Catalyst, Sunday November 11, 1:30 pm – 5:00 pm

Presenters: Nathan D. Fabian & Ron A. Oldfield from Sandia National Laboratories, Andrew C. Bauer & Utkarsh Ayachit from Kitware, and Norbert Podhorszki from Oak Ridge National Laboratory

ABSTRACT: In-situ visualization is a term for running a solver in tandem with visualization. Catalyst is the new name for ParaView’s coprocessing library. ParaView is a powerful open-source turnkey application for analyzing and visualizing large data sets in parallel. By coupling these together, we can utilize HPC platforms for analysis while circumventing bottlenecks associated with storing and retrieving data in disk storage. We demonstrate two methods for in-situ visualization using Catalyst. The first is linking Catalyst directly with simulation codes. It simplifies integration with the codes by providing a programmatic interface to algorithms in ParaView. Attendees will learn how to build pipelines for Catalyst, how the API is structured, how to bind it to C, C++, Fortran, and Python and how to build Catalyst for HPC architectures. The second method uses a variety of techniques, known as data staging or in-transit visualization, that involve passing the data through the network to a second running job. Data analysis applications, written using Catalyst, can operate on this networked data from within this second job minimizing interference with the simulation but also avoiding disk I/O. Attendees will learn three methods of handling this procedure as well as the APIs for ADIOS and NESSIE.

Physical Event

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