Award Abstract #0723060
MRI: Acquisition of Tera-Scale Data Analytic Platforms for Research in the Combinatorial and Graph Sciences Consortium

NSF Org:	CNS Division of Computer and Network Systems
Initial Amendment Date:	August 14, 2007
Latest Amendment Date:	August 14, 2007
Award Number:	0723060
Award Instrument:	Standard Grant
Program Manager:	Rita V. Rodriguez CNS Division of Computer and Network Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	August 1, 2007
Expires:	July 31, 2009 (Estimated)
Awarded Amount to Date:	$150000
Investigator(s):	Clay Gloster, Jr. cgloster@howard.edu (Principal Investigator) Murali Ramanathan (Co-Principal Investigator) Ron Zacharski (Co-Principal Investigator) Kevin Boyack (Co-Principal Investigator) George Davidson (Co-Principal Investigator)
Sponsor:	Howard University 2400 Sixth Street N W Washington, DC 20059 202/806-5567
NSF Program(s):	MAJOR RESEARCH INSTRUMENTATION
Field Application(s):	0000912 Computer Science
Program Reference Code(s):	HPCC,9218
Program Element Code(s):	1189

ABSTRACT

Proposal #: CNS 07-23060

PI(s): Gloster, Jr., Clay

Boyack, Kevin W.; Davidson, George S.; Ramanathan, Murali; Zacharski, Ron

Institution: Howard University

Washington, DC 20059-0001

Title: MRI/Acq.: Terascale Data Analytic Platforms for Research in the Combinatorial and Graph Sciences Consortium

Project Proposed:

This project, acquiring analytic platforms for research in combinatorial and graph sciences, attacks a critical problem, that of extracting information from massive sets of data. The requested instrumentation, a large system for production (Netezza Performance Server(s)), are to be housed at Howard and Sandia National Lab and serve scientific projects on DNA binding mechanisms, protein structure prediction, data mining for computational science at Sandia, multi-dimensional visualization at SUNY-Buffalo, and natural language processing at NMSU. The work responds to the data deluge/tsunami/explosion/avalanche

that presently overwhelms the scientific community. The data intensive computer resource, National Terabyte Data Analysis Centers (NTDAC), provides the ability to analyze tera-scale data sets 10 to 100 times faster than current alternatives at a lower cost. Over time, NTDAC is expected to house and analyze peta-bytes of raw data, to have back-up and support capabilities, and to use parallel relational data warehouse appliance technology that is orders of magnitude faster and easier to use. The initial focus, exploitation of massively parallel relational database appliance technology, enables solution problems in computational biology, chemistry, physics, text mining, bibliographic coupling, and natural language processing.

Broader Impact: The infrastructure benefits all areas of science through faster data analysis. The interrogation of massive data sets allows practitioners and students to deliver/gain new knowledge at a more rapid pace, and to create needed solutions. Moreover, the institution is an HBCU, where minority students are likely to gain from the experience.

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