.TH "dsb2st_kernels.f" 3 "Wed May 24 2017" "Version 3.7.0" "LAPACK" \" -*- nroff -*-
.ad l
.nh
.SH NAME
dsb2st_kernels.f
.SH SYNOPSIS
.br
.PP
.SS "Functions/Subroutines"

.in +1c
.ti -1c
.RI "subroutine \fBdsb2st_kernels\fP (UPLO, WANTZ, TTYPE, ST, ED, SWEEP, \fBN\fP, NB, IB, A, \fBLDA\fP, V, TAU, LDVT, WORK)"
.br
.RI "\fBDSB2ST_KERNELS\fP "
.in -1c
.SH "Function/Subroutine Documentation"
.PP 
.SS "subroutine dsb2st_kernels (character UPLO, logical WANTZ, integer TTYPE, integer ST, integer ED, integer SWEEP, integer N, integer NB, integer IB, double precision, dimension( lda, * ) A, integer LDA, double precision, dimension( * ) V, double precision, dimension( * ) TAU, integer LDVT, double precision, dimension( * ) WORK)"

.PP
\fBDSB2ST_KERNELS\fP  
.PP
\fBPurpose: \fP
.RS 4

.PP
.nf
 DSB2ST_KERNELS is an internal routine used by the DSYTRD_SB2ST
 subroutine.
.fi
.PP
 
.RE
.PP
\fBParameters:\fP
.RS 4
\fIn\fP The order of the matrix A\&.
.br
\fInb\fP The size of the band\&.
.br
\fIA\fP A pointer to the matrix A\&.
.br
\fIlda\fP The leading dimension of the matrix A\&.
.br
\fIV\fP DOUBLE PRECISION array, dimension 2*n if eigenvalues only are requested or to be queried for vectors\&.
.br
\fITAU\fP DOUBLE PRECISION array, dimension (2*n)\&. The scalar factors of the Householder reflectors are stored in this array\&.
.br
\fIst\fP internal parameter for indices\&.
.br
\fIed\fP internal parameter for indices\&.
.br
\fIsweep\fP internal parameter for indices\&.
.br
\fIVblksiz\fP internal parameter for indices\&.
.br
\fIwantz\fP logical which indicate if Eigenvalue are requested or both Eigenvalue/Eigenvectors\&.
.br
\fIwork\fP Workspace of size nb\&.
.RE
.PP
\fBFurther Details: \fP
.RS 4

.PP
.nf
  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 
.fi
.PP
 
.RE
.PP

.SH "Author"
.PP 
Generated automatically by Doxygen for LAPACK from the source code\&.