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University of Texas at Austin Supercomputing Center to Receive $10 Million in Private Funding

The Texas Advanced Computing Center (TACC) at The University of Texas at Austin today announced it has received a commitment of $10 million from the O’Donnell Foundation to advance data-driven science, also called data-enabled or data-intensive science.

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The Texas Advanced Computing Center (TACC) at The University of Texas at Austin today announced it has received a commitment of $10 million from the O’Donnell Foundation to advance data-driven science, also called data-enabled or data-intensive science.

TACC, one of the world’s leading supercomputing centers, will use the funding for new data infrastructure to sustain and broaden the university’s leadership in advanced computing and computational science. When completed, these projects will benefit research in dozens of departments and labs at the university, especially in the Institute for Computational Engineering and Sciences (ICES).

The new resources will also augment TACC’s ability to support research at University of Texas System institutions such as biomedical research at UT Southwestern Medical Center. Novel data-driven projects such as consumer energy usage behaviors being studied at Austin’s Pecan Street Inc. will also benefit, as will major national projects in which the university is a key partner such as the iPlant project, a $50 million National Science Foundation-funded project to help with plant research, including improving food yields and producing more effective biofuels.

Specifically, the new data infrastructure plans include:

  • high-performance, petascale data storage system accessible to all of TACC’s computing and visualization systems, and easily expandable to hundreds of petabytes in the coming years;
  • a computational system with embedded high-speed storage that is optimized for data-intensive computing, including massive data processing and analysis; and
  • new servers and storage to host innovative Web-based and cloud computing services, including science portals and gateways that enable researchers around the world to use the university’s research applications.

“For decades, Peter O’Donnell has been quietly but generously investing in UT Austin,” said Bill Powers, president of The University of Texas at Austin. “We’re once more humbled by his generosity and impressed by his expansive vision of Texas as a world leader in science and technology. The importance of UT’s advanced computing capabilities, embodied by TACC, will only increase over time. We have every reason to believe that Peter’s wisdom will be borne out by ever more dramatic research successes. And as advanced computing enables more sophisticated research across all of the sciences, an investment of this kind is among the most strategic any philanthropist or granting institution could make. It also has the significant side-benefit of attracting even more faculty talent to Texas.”

Peter O’Donnell said, “Dr. Jay Boisseau and his staff have built several of the top high-performance systems in the world. TACC’s new data infrastructure will speed up discoveries in critical areas including cell biology, imaging, astronomy and nano-engineering. Under Jay’s leadership, TACC has become a strong value-creator for Texas.”

Data-driven science is a new mode of computational science emerging alongside modeling and simulation. Vast amounts of digital data are being collected by new generations of digital instruments — such as gene sequencers, electron microscopes, satellite-based imagers and distributed sensor networks — that can be mined for scientific insights.

“Having large amounts of accurate data enables us to make inferences, correlations and even predictions where theoretical foundations — mathematical governing equations and models — are not yet derived,” said TACC Director Jay Boisseau. “Collecting digital data is increasingly cheap and easy. We need digital infrastructure that helps people manage it and make sense of it.”

The O’Donnell Foundation has already contributed $6 million of the commitment to The University of Texas at Austin and will provide $2 million more in each of the next two years. The university will also provide an additional $2 million over five years to hire new technology professionals at TACC, who will support and accelerate new research in ICES and other university programs that leverage these data resources.

Here are some of the researchers across the state who will be helped by TACC’s expanded capacity:

Bioinformatics — Nobel Laureate Bruce Beutler, Center for the Genetics of Host Defense at UT Southwestern Medical Center

Email: Bruce.Beutler@UTSouthwestern.edu  Phone: 214-648-5836

Beutler and his group are using random mutagenesis to dissect innate immunity, the first step in the body’s immune response. They sequence the whole genomes of mice with immune deficiencies and then search for the causative mutations by computational comparisons between mutant and wild-type strains, analyzing trillions of nucleotides (units of inheritance) per month to find “needles in haystacks.”

Neuroscience — Assistant Professor Alison Preston, Department of Psychology and Section of Neurobiology, The University of Texas at Austin

Email: apreston@mail.clm.utexas.edu  Phone: 512-475-7255

Preston’s research focuses on understanding how predictive memory operates in the human brain using functional brain imaging techniques. The data-intensive infrastructure at TACC will enable Preston and her trainees to increase the speed at which they analyze the complex patterns of brain responses and how they relate to behavior, substantially increasing the rate of scientific discovery.

Structural Biology — Professor Ron Elber, Department of Chemistry and Biochemistry, Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin

Email: ron@ices.utexas.edu   Phone: 512-232-5415

Elber and his group are using computationally generated models of protein complexes and comparing them to experimentally determined structures. They exploit these comparisons to build predictive tools of protein assembly.

Astrophysics — Professor Karl Gebhardt, 2012 Edith and Peter O’Donnell Award in Science, Department of Astronomy, The University of Texas at Austin

Email: gebhardt@astro.as.utexas.edu   Phone: 512-590-5206

Gebhardt and his team have designed an observing program to understand the accelerated expansion of the universe. The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) will observe more than a million galaxies during a three-year observing campaign and make the largest map of the universe in order to trace out its expansion in detail. TACC provides a vital resource as the survey will generate a petabyte of data and require substantial computing power.

Energy — Brewster McCracken, Executive Director, Pecan Street Inc.

Email: bmccracken@pecanstreet.org   Phone: 512-222-9603

Pecan Street Inc. is a research and development organization focused on applying and testing advanced technology, new business models and customer behavior to better understand the potential of smart grids. Data-intensive computing is used as a large-scale response to data hosting, novel visualizations and data portal opportunities.

Plant Biology — Dan Stanzione, Co-Director for Infrastructure, iPlant Collaborative

Email: dan@tacc.utexas.edu   Phone:  512-475-9411

Gene sequencing and high-resolution imaging technologies require significant computer power. The iPlant Collaborative builds advanced cyberinfrastructure for researchers and developers to take maximum advantage of the deluge of biological data to help solve the world’s growing food challenges.

Social Science — Kent Norsworthy, Latin American Government Documents Archive (LAGDA), The University of Texas at Austin

Email: k.norsworthy@austin.utexas.edu   Phone: 512-471-7714

The LAGDA project seeks to preserve and provide access to ministerial and presidential documents from 18 Latin American and Caribbean countries. LAGDA is composed of approximately 66.6 million documents archived from the Internet, totaling 5.6 terabytes of data. The current effort is to apply state-of-art text mining algorithms with cloud computing to facilitate the automatic classification of and access to this collection.