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Blue Waters Webinars

VisIT: Scalable HPC Visualization and Data Analysis

Photograph of Kevin Griffin Photograph of Eric Brugger Photograph of Cyrus Harrison
Kevin Griffin

VisIt Software Developer
Lawrence Livermore National Laboratory
University of California, Davis

Eric Brugger

VisIt Project Leader
Computer Scientist
Lawrence Livermore National Laboratory

Cyrus Harrison

Visit Software Architect
Computer Scientist
Lawrence Livermore National Laboratory

Griffin's Bio

Kevin Griffin works at Lawrence Livermore National Laboratory and is currently a software developer for VisIt. Kevin is also a Ph.D. student at the University of California, Davis with research interests in Scientific Visualization and High Performance Computing. His current research is on visualizing smoothed particle hydrodynamics simulation datasets on high performance computing platforms.

Brugger's Bio

Eric Brugger has over 25 years' experience developing and using scientific visualization and analysis software. He is the VisIt project leader and one of the original developers of the software. He received an R&D 100 award in 2005 as part of the development team of VisIt. He has extensive experience assisting users visualize and understand their simulation data as well as providing hands on VisIt training in workshop settings.

Harrison's Bio

Cyrus Harrison is a computer scientist and Associate Division Leader in the Applications, Simulations, and Quality (ASQ) division of Lawrence Livermore National Laboratory's Computation directorate. He is the software architect of the VisIt open source visualization tool and leads major aspects of the technical direction of the project. Cyrus also provides custom data analysis solutions for large scale scientific simulations.


VisIt, an open source parallel scientific visualization and data analysis platform, is deployed and used by scientists on a wide range of compute platforms ranging from laptops to the worlds most powerful supercomputers. VisIt provides data interfaces to more than one hundred scientific data formats and contains a large number of visualization and analysis tools for the data and mesh types typically found in physics simulations. More succinctly, VisIt provides a visualization and analysis platform that is well suited to leverage current and next generation HPC resources for scientific discovery. Our two hour webcast will provide participants with a practical introduction to mesh-based HPC visualization and analysis using VisIt.

Session details

When: 10:00 CST, March 15, 2017

Length of session: 2 hours

Target audience: This tutorial is targeted at scientists using HPC simulations, researchers and developers of HPC simulation applications, and any one intersted in scientific visualization. The content will focus on visualization and data analysis of mesh-based HPC physics simulations. The techniques presented are broadly applicable to several scientific domains (CFD, Hydrody- namics, Structural Mechanics, Astro Physics, etc).

Prerequisites: We do not have any prerequisites for domain knowledge. We have a small amount of Python content that requires only a very basic understanding of programming. Attendes can follow along on their own computers. Prior to the presentation we will provide a link to a wiki page with instructions on how to install VisIt and download the sample datasets used throughout the tutorial.?

User base: VisIt has thousands of customers throughout DOE, DoD, and is an internationally known and used visualization tool.

Software Availability: VisIt is open source and available for download at

In preparation for this webinar, please follow these instructions for loading the VisIT software prior to viewing the webinar.

Software Requirements: VisIt runs on all major platforms (Windows, OS X, Linux). We will provide links to the appropriate executables for attendees.

Webcast outline: The webcast will be organized as follows:

  • VisIt Project Introduction
  • Guided Tour of VisIt
  • Interface Overview
  • VisIt's Building Blocks: Databases, Plots, Operators, Expressions, Queries – Python Scripting
  • End-to-End Visualization of a Blood Flow (Aneurysm)
  • Description of Simulation and Datasets – Data Exploration
  • Python Scripting for Analysis

Training and reference materials: Here are links to where we host our tutorial content.

Webinar video

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Webinar slides: Download