1. Nuclear Energy Work Hank Childs & Christoph Garth April 15, 2010

2. Customers, team, & goals Customers: Argonne NEAMS personnel, especially INCITE awardee Paul Fischer VACET team members: Hank Childs & Christoph Garth –Activity normally leveraged by NEAMS vis $’s Goal: ensure visualization and analysis needs continued to be met successfully and analysis aid in advanced analysis. Customers: Argonne NEAMS personnel, especially INCITE awardee Paul Fischer VACET team members: Hank Childs & Christoph Garth –Activity normally leveraged by NEAMS vis $’s Goal: ensure visualization and analysis needs continued to be met successfully and analysis aid in advanced analysis.

5. This work depends on efficient streamline generation (described in later talks) We needed parallel efficient streamline techniques to do this work. (SC09)

11. Astrophysics Work Hank Childs & Gunther Weber April 15, 2010

12. Computational Astrophysics Consortium Team: Hank Childs, Gunther Weber, Allen Sanderson Customers: –Jay Salmonson, LLNL –Christian Ott & Reiswig, CalTech –John Bell & Ann Almgren, LBL (Maestro) –Adam Burrows, Jason Nordhaus & Princeton team (Castro) Note: much of this effort is leveraged by NERSC Analytics Goal: Ensure CAC visualization and analysis needs are met Team: Hank Childs, Gunther Weber, Allen Sanderson Customers: –Jay Salmonson, LLNL –Christian Ott & Reiswig, CalTech –John Bell & Ann Almgren, LBL (Maestro) –Adam Burrows, Jason Nordhaus & Princeton team (Castro) Note: much of this effort is leveraged by NERSC Analytics Goal: Ensure CAC visualization and analysis needs are met

13. Many, many movies

14. Streamlines with astrophysics data Upcoming analysis: use streamlines to study flow through the center of the star and better understand how neutrinos get irradiated.

15. It took a CET to deploy streamline technology Flexible serial streamline library Research effort: Efficient parallel streamline generation Deployment effort in VisIt Usage by VisIt community Nuclear Energy Fusion Astrophysics: radiation patterns Hybrid Parallelism