BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121111T203000Z
DTEND:20121112T000000Z
LOCATION:251-F
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: In-situ visualization is a term for running a solver in tandem with visualization.  Catalyst is the new name for ParaViews 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.
SUMMARY:In-Situ Visualization with Catalyst
PRIORITY:3
END:VEVENT
END:VCALENDAR
BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121111T203000Z
DTEND:20121112T000000Z
LOCATION:251-F
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: In-situ visualization is a term for running a solver in tandem with visualization.  Catalyst is the new name for ParaViews 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.
SUMMARY:In-Situ Visualization with Catalyst
PRIORITY:3
END:VEVENT
END:VCALENDAR