Computer Science


Scientific Data Management and Analysis at Extreme Scale

The CS Scientific Data Management and Analysis at Extreme Scale call for proposals was issued January, 29, 2010 and closed March 18, 2010.  Ten projects were awarded funding for a total of $5 million per year.

The following proposals were selected for funding:

Adding Data Management Services to Parallel File Systems.pdf file (518KB)

 • University of California, Santa Cruz; Lawrence Livermore National Laboratory

An Information-Theoretic Framework for Enabling Extreme-Scale Science Discovery.pdf file (442KB)

 • Ohio State University; Polytechnic Institute of New York University; Argonne National Laboratory

Dax: Data Analysis at Extreme.pdf file (797KB)

 • Sandia National Laboratories; Kitware, Inc.; University of California, Davis

Dynamic Non-Hierarchical File Systems for Exascale Storage.pdf file (102KB)

 • University of California, Santa Cruz

Enabling Scientific Discovery in Exascale Simulations.pdf file (937KB)

 • Lawrence Livermore National Laboratory; University of Minnesota

ExaHDF5: An I/O Platform for Exascale Data Models, Analysis and Performance.pdf file (408KB)

 • Lawrence Berkeley National Laboratory; Pacific Northwest National Laboratory

Graph-Based 3D Flow Field Visual Analysis.pdf file (278KB)

 • Pacific Northwest National Laboratory; Ohio State University

Runtime System for I/O Staging in Support of In-Situ Processing of Extreme Scale Data.pdf file (261KB)

 • Oak Ridge National Laboratory; Lawrence Berkeley National Laboratory; Georgia Institute of Technology

Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems.pdf file (374KB)

 • Northwestern University; Lawrence Berkeley National Laboratory; Oak Ridge National Laboratory

Topology-based Visualization and Analysis of Multi-dimensional Data and Time-varying Data at the Extreme Scale.pdf file (49KB)

 • Lawrence Berkeley National Laboratory

Last modified: 3/5/2016 7:57:24 PM