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Who are you and why you care about this

Who are you and why you care about this . I am Hank Childs, Lawrence Berkeley and UC Davis My professional career to date has been developing and delivering big data visualization solutions to users

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Who are you and why you care about this

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  1. Who are you and why you care about this • I am Hank Childs, Lawrence Berkeley and UC Davis • My professional career to date has been developing and delivering big data visualization solutions to users • I am currently responsible for delivering HPC visualization and analysis software to many different communities: • VACET / SciDAC (CSWA) • Longhorn / XSEDE (CSWA) • 10-05 Climate community (CSWA) • NEAMS (PI) • NERSC Analytics team

  2. What research activities are you doing in this area? 1 trillion cell mesh rendered on 16K cores of LBNL Franklin • Non-research activities: • Software development • Frontline support • Research: • What are the bottlenecks at massive concurrency? • How can we utilize hybrid parallelism to achieve better performance and scalability? • How can we make non-embarrassingly parallel algorithms more scalable? • & more… 4608^2 image using 216K cores of ORNL Jaguar

  3. What have you developed, where can people download it, and why should they use it? • VisItis an open source, richly featured, turn-key application for large data. • http://www.llnl.gov/visit • Popular • R&D 100 award in 2005 • Used on many of the Top500 • >>>100K downloads 1 billion grid points / time slice 217 pin reactor cooling simulation Run on ¼ of Argonne BG/P Image credit: Paul Fischer, ANL

  4. What are the GAPS in this area? • I will let everyone else talk about in situ processing, massively concurrency, fault tolerance, etc. • Our community has invested massively in CPU-based software. • This investment is in the hundreds of person-years. • (VisItalone represents 75 man-years, 1.5M lines of code) • How are we going to translate this investment to the accelerator environment?

  5. Tell us what you think the future is • We are envisioning machines where we won’t be able to: • get the data off the machine for later storage • regularly post-process data • This is a step backwards for the user. • We must innovate approaches that allow users to continue to do critical activities, such as interactive exploration

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