The Visualization Toolkit (vtk.org) and ParaView (paraview.org) are two widely used open source, visualization and data processing tools for scientific computing. They are designed to be used on a variety of data forms, ranging from medical to computational meshes to unstructured data such as documents. ParaView in particular is used by many High Performance Computing centers such as the US National Labs, NSF HPC resource centers such as the San Diego Supercomputing Center, and internationally such as the new Ter@Tec French commercial/government HPC consortium. One of their major claims to fame is these tools can process huge amounts of data, demonstrated on petabyte datasets, and on hundreds of thousands of computing cores, for example 160,000 cores on Argonne’s Blue Gene supercomputer.
In this presentation, the two principal developers of VES and ParaViewWeb (Pat Marion and Utkarsh Ayachit, respectively) will describe the architecture, API, and usage of these systems, and provide real-time demonstrations, including client interface to a computing cluster. They will demonstrate the power of these tools through examples such as brain atlas on a phone, and interactive streamline generation and visualization on a tablet.
Pat joined Kitware as a student intern in 2007 where he contributed to the ParaView project. He received his B.S. in Computer Science from Rensselaer Polytechnic Institute in 2008 and moved to North Carolina to join Kitware’s Chapel Hill office as a research engineer. Pat is the lead developer of Kitware’s mobile development efforts.
Mr. Ayachit is the principal developer for ParaViewWeb and is part of the team that develops ParaView. He is a Technical Lead in the Scientific Computing Group at Kitware. Previously, he helped design and develop the Intrusion Detection Toolkit (IDtk) which uses glyph-based visualization techniques to help distinguish false positives from real intrusive attempts. Mr. Ayachit’s work is primarily focused on data visualization; agent architectures and multiagent systems; information retrieval; artificial intelligence; and the design and analysis of algorithms.
Mr. Ayachit obtained his B.S. in Computer Science from the Pune Institute of Computer Technology (India) in 2002. He earned his M.S. in Computer Science from the University of Maryland, Baltimore County (UMBC) in 2004; his master’s thesis explored the use of level-of-detail in 2D flow visualization techniques namely streamline visualizations, vector plots and texture-based techniques.
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