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chb2st_kernels.f(3) LAPACK chb2st_kernels.f(3)

NAME

chb2st_kernels.f

SYNOPSIS

Functions/Subroutines


subroutine chb2st_kernels (UPLO, WANTZ, TTYPE, ST, ED, SWEEP, N, NB, IB, A, LDA, V, TAU, LDVT, WORK)
CHB2ST_KERNELS

Function/Subroutine Documentation

subroutine chb2st_kernels (character UPLO, logical WANTZ, integer TTYPE, integer ST, integer ED, integer SWEEP, integer N, integer NB, integer IB, complex, dimension( lda, * ) A, integer LDA, complex, dimension( * ) V, complex, dimension( * ) TAU, integer LDVT, complex, dimension( * ) WORK)

CHB2ST_KERNELS

Purpose:


CHB2ST_KERNELS is an internal routine used by the CHETRD_HB2ST
subroutine.

Parameters:

n The order of the matrix A.
nb The size of the band.
A A pointer to the matrix A.
lda The leading dimension of the matrix A.
V COMPLEX array, dimension 2*n if eigenvalues only are requested or to be queried for vectors.
TAU COMPLEX array, dimension (2*n). The scalar factors of the Householder reflectors are stored in this array.
st internal parameter for indices.
ed internal parameter for indices.
sweep internal parameter for indices.
Vblksiz internal parameter for indices.
wantz logical which indicate if Eigenvalue are requested or both Eigenvalue/Eigenvectors.
work Workspace of size nb.

Further Details:


Implemented by Azzam Haidar.
All details are available on technical report, SC11, SC13 papers.
Azzam Haidar, Hatem Ltaief, and Jack Dongarra.
Parallel reduction to condensed forms for symmetric eigenvalue problems
using aggregated fine-grained and memory-aware kernels. In Proceedings
of 2011 International Conference for High Performance Computing,
Networking, Storage and Analysis (SC '11), New York, NY, USA,
Article 8 , 11 pages.
http://doi.acm.org/10.1145/2063384.2063394
A. Haidar, J. Kurzak, P. Luszczek, 2013.
An improved parallel singular value algorithm and its implementation
for multicore hardware, In Proceedings of 2013 International Conference
for High Performance Computing, Networking, Storage and Analysis (SC '13).
Denver, Colorado, USA, 2013.
Article 90, 12 pages.
http://doi.acm.org/10.1145/2503210.2503292
A. Haidar, R. Solca, S. Tomov, T. Schulthess and J. Dongarra.
A novel hybrid CPU-GPU generalized eigensolver for electronic structure
calculations based on fine-grained memory aware tasks.
International Journal of High Performance Computing Applications.
Volume 28 Issue 2, Pages 196-209, May 2014.
http://hpc.sagepub.com/content/28/2/196

Author

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