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Research Spending & Results

Award Detail

Doing Business As Name:University of Tennessee Knoxville
  • Sean D Ahern
  • (865) 408-8463
  • Scott Klasky
  • Edward W Bethel
  • Jian Huang
  • Bart D Semeraro
Award Date:07/24/2009
Estimated Total Award Amount: $ 10,000,000
Funds Obligated to Date: $ 10,000,000
  • FY 2009=$10,000,000
Start Date:08/01/2009
End Date:09/30/2013
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040101 RRA RECOVERY ACT
Award Title or Description:NICS Remote Data Analysis and Visualization Center
Federal Award ID Number:0906324
DUNS ID:003387891
Parent DUNS ID:003387891
Program:XD-Extreme Digital

Awardee Location

Street:1331 CIR PARK DR
Awardee Cong. District:02

Primary Place of Performance

Organization Name:University of Tennessee Knoxville
Street:1331 CIR PARK DR
Cong. District:02

Abstract at Time of Award

This proposal will be awarded using funds made available by the American Recovery and Reinvestment Act of 2009 (Public Law 111-5), and meets the requirements established in Section 2 of the White House Memorandum entitled, Ensuring Responsible Spending of Recovery Act Funds, dated March 20, 2009. I also affirm, as the cognizant Program Officer, that the proposal does not support projects described in Section 1604 of Division A of the Recovery Act. In recent years, researchers from a growing range of scientific domains have experienced a widening gap in their abilities to generate data on complex biological and physical systems and translate these data into scientific discovery. Our data analysis and visualization capabilities have failed to keep pace with advances in both the capacity of our computing infrastructure and the resolution and throughput of our data acquisition systems. Translating raw data generated by detailed simulation or collected by advanced instruments into scientific discovery requires a coherent suite of powerful hardware and software capabilities that is fully integrated into our national computational infrastructure. The volume of the data and the complexity of the underlying phenomena require an infrastructure that allows scientists to develop and operate flexible, and the same time dependable, end-to-end data analysis and visualization capabilities that span local and national resources. A 2007 report composed by data analysis, management, and visualization experts concluded that datasets being produced by experiments and simulations are rapidly outstripping our ability to explore and understand them. One of the most significant challenges to scientific discovery today is the extraction of knowledge and meaning from this vast array of data and the understanding of the correlations, trends, patterns, and interrelationships among disparate elements from an ever-growing array of data sources. Visualization, data analysis, and knowledge discovery are more vital than ever because they generate the data insight and intuition that enable scientific discovery. Scientific simulation has become the third pillar of science, supporting frameworks and experimental studies in our understanding of natural phenomena. As simulations become larger, more numerous, more complex, and as the scientific problems we seek to unlock become more challenging, so does the task of understanding the data generated. This award presents a data visualization and analysis center, based at the University of Tennessee and coupled with the NSF TeraGrid Kraken supercomputer, that will narrow this gap by bringing together a unique team, proven software technologies, and advanced computing and data-handling capabilities. The center will provide the eyes of the TeraGrid XD, our national cyberinfrastructure, as it evolves to the XD era by empowering scientists to see and understand very large collections of measured or simulated datasets. The hardware that undergirds the center is a large shared memory SGI UltraViolet system, able to provide 1,024 processors with 4 TB of shared memory for processing large datasets. No other system in the world has this level of shared memory concurrency for analysis and visualization. Supported by a large (1 PB) filesystem directly connected to the Kraken supercomputer and the TeraGrid network, this system will provide NSF researchers with an unparalleled data understanding resource. The team of people comprising the center will draw upon experience in visualization,statistical analysis, workflow delivery, portal and dashboard development, remote access, and application development to provide software resources for large scale data understanding. This team will also be supported by dedicated user assistance, system support, education, and application discovery staff.

Publications Produced as a Result of this Research

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A. Szczepa?ski, T. Baer, Y. Mack, J. Huang, S. Ahern "Usage of a HPC Data Analysis and Visualization System" Computer, v.46, 2013, p.84. doi: 

Tian, Yuan; Liu, Zhuo; Klasky, Scott; Wang, Bin; Abbasi, Hasan; Zhou, Shujia; Podhorszki, Norbert; Clune, Tom; Logan, Jeremy; Yu, Weikuan; IEEE "A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics" 2013 IEEE 29TH SYMPOSIUM ON MASS STORAGE SYSTEMS AND TECHNOLOGIES (MSST), v., 2013, p..

Liu, Q., Logan, J., Tian, Y., Abbasi, H., Podhorszki, N., Choi, J. Y., Klasky, S., Tchoua, R., Lofstead, J., Oldfield, R., Parashar, M., Samatova, N., Schwan, K., Shoshani, A., Wolf, M., Wu, K. and Yu, W. "Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks" Concurrency and Computation: Practice and Experience, v., 2012, p.. doi:10.1002/cpe.3125 

Amy F. Szczepa?ski, Jian Huang, Troy Baer, Yashema C. Mack, and Sean Ahern "Data analysis and visualization in high-performance computing" IEEE Computer, v.46, 2013, p.84. doi:10.1109/MC.2012.192 

Homayoun Karimabadi, Vadim Roytershteyn, Minping Wan, William H. Matthaeus, William Daughton, P. Wu, Michael A. Shay, Burlen Loring, Joseph Borovsky, Ersilia Leonardis, Sandra C. Chapman, and Takuma Nakamura "Coherent structures, intermittent turbulence and dissipation in high-temperature plasmas" Physics of Plasma, v.20, 2013, p.. doi: 

M. Wan, W. H. Matthaeus, H. Karimabadi, V. Roytershteyn, M. Shay, P. Wu, W. Daughton, B. Loring, and S. C. Chapman "Intermittent dissipation at kinetic scales in collisionless plasma turbulence" Physics Review Letters, v.109, 2012, p.. doi:10.1103/PhysRevLett.109.195001 

Abbasi, Hasan; Wolf, Matthew; Eisenhauer, Greg; Klasky, Scott; Schwan, Karsten; Zheng, Fang "DataStager: scalable data staging services for petascale applications" CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.13, 2010, p.277-290.

Tian, Yuan; Klasky, Scott; Abbasi, Hasan; Lofstead, Jay; Grout, Ray; Podhorszki, Norbert; Liu, Qing; Wang, Yandong; Yu, Weikuan; IEEE "EDO: Improving Read Performance for Scientific Applications Through Elastic Data Organization" 2011 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER), v., 2011, p.93-102.

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