Monday October 26 4:00 - 4:50 PM Kelley 1001 [map] <http://oregonstate.edu/cw_tools/campusmap/?&offsetX=1576&offsetY=526&po int=?298,111>
Peter Lindstrom Lawrence Livermore National Laboratory Towards peta-scale data analysis and visualization With scientific data sets from observation and simulation reaching peta- and even exabytes in the near future, our data analysis and visualization capabilities are being outstripped by our ability to generate such enormous volumes of data. This problem is further exacerbated by the widening gap in processing speed afforded by multicore architectures and virtually stagnating disk I/O performance. To address this data explosion challenge, our research group at LLNL is developing new scalable techniques that minimize data transfer through compression and I/O optimal data access such as single-pass stream processing, and via cache-oblivious data reordering for improved cache utilization. This talk will focus on key advances in I/O efficient processing in the context of scientific visualization, with an emphasis on managing unstructured data such as computational meshes, isosurfaces, graphs, and floating-point geometry and fields. Biography Dr. Peter Lindstrom is a Computer Scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. He currently leads several research projects on analysis and visualization of large-scale spatial data to support science applications such as climate modeling, inertial confinement fusion, and fluid dynamics. His recent research spans areas such as data compression, out-of-core and cache-efficient algorithms, multiresolution modeling, terrain visualization, mesh generation, and computer vision. Dr. Lindstrom earned B.S. degrees in Computer Science, Mathematics, and Physics from Elon University in 1994, received a Ph.D. in Computer Science from Georgia Institute of Technology in 2000, and joined LLNL shortly thereafter.
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