dsb2st_kernels.f

Section: LAPACK (3)
Updated: Tue Nov 14 2017
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NAME

dsb2st_kernels.f

SYNOPSIS

Functions/Subroutines

subroutine dsb2st_kernels (UPLO, WANTZ, TTYPE, ST, ED, SWEEP, N, NB, IB, A, LDA, V, TAU, LDVT, WORK)
DSB2ST_KERNELS

Function/Subroutine Documentation

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)

DSB2ST_KERNELS

Purpose:

 DSB2ST_KERNELS is an internal routine used by the DSYTRD_SB2ST
 subroutine.

Parameters:

UPLO

          UPLO is CHARACTER*1

WANTZ

          WANTZ is LOGICAL which indicate if Eigenvalue are requested or both
          Eigenvalue/Eigenvectors.

TTYPE

          TTYPE is INTEGER

          ST is INTEGER
          internal parameter for indices.

          ED is INTEGER
          internal parameter for indices.

SWEEP

          SWEEP is INTEGER
          internal parameter for indices.

          N is INTEGER. The order of the matrix A.

          NB is INTEGER. The size of the band.

          IB is INTEGER.

          A is DOUBLE PRECISION array. A pointer to the matrix A.

LDA

          LDA is INTEGER. The leading dimension of the matrix A.

          V is DOUBLE PRECISION array, dimension 2*n if eigenvalues only are
          requested or to be queried for vectors.

TAU

          TAU is DOUBLE PRECISION array, dimension (2*n).
          The scalar factors of the Householder reflectors are stored
          in this array.

LDVT

          LDVT is INTEGER.

WORK

          WORK is DOUBLE PRECISION array. 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

Definition at line 170 of file dsb2st_kernels.f.

Author

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