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Finding Meaning in Massive Datasets

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Ranger supercomputer

Ranger supercomputer at the Texas Advanced Computing Center

University of Texas at Austin

Researchers at the Texas Advanced Computing Center (TACC) are exploring data-driven science, and early projects are showing the benefits of using advanced computing to find meaning in massive datasets.

For example, University of Sussex professor Ilian Iliev is working with TACC, the University of Texas at Austin, and Pervasive Software to analyze dark matter simulations. Iliev developed a method for data-mining scientific simulations using Google's MapReduce. The researchers developed a search mechanism that identified regions of interest in the midst of chaotic visualizations.

TACC also is working on an experimental smart grid project with Austin Energy, the University of Texas Energy Institute, and Mueller Development. The smart grid project equipped 100 new homes with sensors to measure consumer energy usage. TACC and Austin Energy are organizing the data to develop an accurate baseline of energy usage in Austin, as well as creating new visualization tools to clearly represent energy usage to consumers, energy operators, and officials.

Meanwhile, the 1,000 Plant Genomes Project, which includes researchers from China, Canada, and the United States, is using distributed information to research plant genetic and genomic diversity. The project aims to understand the structures of the major genes in 1,000 different species of plants.

From Texas Advanced Computing Center
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