This story is from the category World Specific Developments
Date posted: 30/06/2012
Modern research tools like supercomputers, particle colliders, and telescopes are generating so much data, so quickly, many scientists fear that soon they will not be able to keep up with the deluge.
"These instruments are capable of answering some of our most fundamental scientific questions, but it is all for nothing if we can't get a handle on the data and make sense of it," says Surendra Byna of the Lawrence Berkeley National Laboratory's (Berkeley Lab's) Scientific Data Management Group.
That's why Byna and several of his colleagues from the Berkeley Lab's Computational Research Division teamed up with researchers from the University of California, San Diego (UCSD), Los Alamos National Laboratory, Tsinghua University, and Brown University to develop novel software strategies for storing, mining, and analyzing massive datasets -- more specifically, for data generated by a state-of-the-art plasma physics code called VPIC.
When the team ran VPIC on the Department of Energy's National Energy Research Scientific Computing Center's (NERSC's) Cray XE6 "Hopper" supercomputer, they generated a three-dimensional (3D) magnetic reconnection dataset of a trillion particles. VPIC simulated the process in thousands of time-steps, periodically writing a massive 32 terabyte (TB) file to disk at specified times.
Using their tools, the researchers wrote each 32 TB file to disk in about 20 minutes, at a sustained rate of 27 gigabytes per second (GB/s). By applying an enhanced version of the FastQuery tool, the team indexed this massive dataset in about 10 minutes, then queried the dataset in three seconds for interesting features to visualize.
"This is the first time anyone has ever queried and visualized 3D particle datasets of this size," says Homa Karimabadi, who leads the space physics group at UCSD.
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