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- Gary W. Howell, James Demmel, Charles T. Fulton, Sven Hammarling, Karen Marmol
- ACM Trans. Math. Softw.
- 2008

On cache based computer architectures using current standard algorithms, Householder bidiagonalization requires a significant portion of the execution time for computing matrix singular values and vectors. In this paper we reorganize the sequence of operations for Householder bidiagonalization of a general <i>m</i> × <i>n</i> matrix, so that two… (More)

- George A. Geist, Gary W. Howell, David S. Watkins
- SIAM J. Matrix Analysis Applications
- 1999

The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrow-band, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the… (More)

- Gary W. Howell, Nadia Diaa
- ACM Trans. Math. Softw.
- 2005

BHESS uses Gaussian similarity transformations to reduce a general real square matrix to similar upper Hessenberg form. Multipliers are bounded in root mean square by a user-supplied parameter. If the input matrix is not highly nonnormal and the user-supplied tolerance on multipliers is of a size greater than ten, the returned matrix usually has small upper… (More)

- Gary W. Howell, Kamel Rekab
- Neural Parallel & Scientific Comp.
- 1995

- Jacqueline M. Hughes-Oliver, Atina D. Brooks, +7 authors Moody T. Chu
- In Silico Biology
- 2011

ChemModLab, written by the ECCR @ NCSU consortium under NIH support, is a toolbox for fitting and assessing quantitative structure-activity relationships (QSARs). Its elements are: a cheminformatic front end used to supply molecular descriptors for use in modeling; a set of methods for fitting models; and methods for validating the resulting model.… (More)

- Gary W. Howell, Donald W. Fausett, Laurene V. Fausett
- CVGIP: Graphical Model and Image Processing
- 1993

- V. Lakshmikantham, Syamal Kumar Sen, Gary W. Howell
- Neural Parallel & Scientific Comp.
- 1996

- Gary W. Howell
- SpringSim
- 2010

This paper introduces block Householder reduction of a rectangular sparse matrix to small band upper triangular form. The computation accesses a sparse matrix only for sparse matrix dense matrix (SMDM) multiplications and for "just in time" extractions of row and column blocks. For a bandwidth of <i>k</i> + 1, the dense matrices are the <i>k</i> rows or… (More)

- G W Howell
- 2009

This paper describes Householder reduction of a rectangular sparse matrix to small band upper triangular form. Using block Householder transformations gives good orthogonality, is computationally efficient, and has good potential for parallelization. The algorithm is similar to the standard dense Householder reduction used as part of the usual dense SVD… (More)