NSF Org:	CCF Division of Computing and Communication Foundations
Recipient:	UNIVERSITY OF KANSAS CENTER FOR RESEARCH INC
Initial Amendment Date:	August 21, 2001
Latest Amendment Date:	August 21, 2001
Award Number:	0098150
Award Instrument:	Standard Grant
Program Manager:	Robert B Grafton CCF  Division of Computing and Communication Foundations CSE  Directorate for Computer and Information Science and Engineering
Start Date:	August 1, 2001
End Date:	July 31, 2005 (Estimated)
Total Intended Award Amount:	$202,520.00
Total Awarded Amount to Date:	$202,520.00
Funds Obligated to Date:	FY 2001 = $202,520.00
History of Investigator:	Ralph Byers (Principal Investigator) byers@math.ukans.edu
Recipient Sponsored Research Office:	University of Kansas Center for Research Inc 2385 IRVING HILL RD LAWRENCE KS  US  66045-7563 (785)864-3441
Sponsor Congressional District:	01
Primary Place of Performance:	University of Kansas Center for Research Inc 2385 IRVING HILL RD LAWRENCE KS  US  66045-7563
Primary Place of Performance Congressional District:	01
Unique Entity Identifier (UEI):	SSUJB3GSH8A5
Parent UEI:	SSUJB3GSH8A5
NSF Program(s):	NUMERIC, SYMBOLIC & GEO COMPUT
Primary Program Source:	01000102DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	9216, HPCC
Program Element Code(s):	286500
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

The investigator will study numerical algorithms for solving moderate to large scale eigenvalue and generalized eigenvalue problems. There are two lines of research. One is to investigate a new kind of parallelizable Hessenberg eigen-value algorithm termed "subdivision-by-deflation". The subdivision-by-deflation algorithm reduces the computational complexity and increases the parallelism of Hessenberg eigenvalue problems. This has the potential of reducing the computational cost of the Hessenberg eigenvalue problem significantly below current levels.

The other line of research involves continued development of TTQRE, a variant QR algorithm for solving the moderate scale algebraic eigenvalue problem. Although TTQRE has already proved itself to be a significant advance over traditional QR algorithms, it has not yet reached its full potential. Strategies will be designed that adjust its fundamental parameters dynamically during execution. This project supports a graduate student who will participate in the project. The student's training will benefit from practical computational experience on real parallel computers as from the work with theoretical problems.

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