Random Number Generation for High Performance Computing

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$99,965.00
Award Year:
2010
Program:
STTR
Phase:
Phase I
Contract:
W911NF-11-C-0026
Agency Tracking Number:
A10A-012-0292
Solicitation Year:
n/a
Solicitation Topic Code:
ARMY 10T012
Solicitation Number:
n/a
Small Business Information
Silicon Informatics, Inc.
6500 Parnell Ave, Edina, MN, 55435
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Rajendra Boppana
Professor
(210) 458-5692
boppana@cs.utsa.edu
Business Contact:
Robert Keller
President and CEO
(612) 327-0682
rkeller@siliconinformatics.com
Research Institution:
Univ of Texas at San Antonio
Noe Saldana
Office of Sponsored Programs
One UTSA Circle
San Antonio, TX, 78248
(210) 458-4340
Nonprofit college or university
Abstract
Highly scalable parallel random number generators (RNGs) will be developed, evaluated and implemented for use in high performance computing on thousands of multi-core processors and general purpose graphics processing units. The main contributions are: (a) design and implementation of new parallel test methods that capture the inter-stream correlations exhibited in practice and complement the currently widely used sequential test batteries, (b) development of new parallel RNGs that produce 100s of thousands of high quality individual random number streams and explicitly minimize inter-stream correlations, and (c) preliminary implementation of the new test methods and parallel RNGs. The proposed RNGs will also be evaluated and tuned to generate cryptographically-secure random number streams that resist cryptanalysis attacks by insiders and eavesdroppers when used in large-scale peer-to-peer and distributed security applications. The investigators have extensive experience in the applications of random number generators, the test methods for random number generators, and the implementation of Monte Carlo applications on large clusters of processors and graphics processing units. The proposed approach balances the theoretical research with the implementation efficiencies and the use in real applications.

* information listed above is at the time of submission.

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