Provided by: scalapack-doc_1.5-10_all 
NAME
PSSYEV - compute all eigenvalues and, optionally, eigenvectors of a real symmetric matrix
A by calling the recommended sequence of ScaLAPACK routines
SYNOPSIS
SUBROUTINE PSSYEV( JOBZ, UPLO, N, A, IA, JA, DESCA, W, Z, IZ, JZ, DESCZ, WORK, LWORK, INFO
)
CHARACTER JOBZ, UPLO
INTEGER IA, INFO, IZ, JA, JZ, LWORK, N
INTEGER DESCA( * ), DESCZ( * )
REAL A( * ), W( * ), WORK( * ), Z( * )
INTEGER BLOCK_CYCLIC_2D, DLEN_, DTYPE_, CTXT_, M_, N_, MB_, NB_, RSRC_, CSRC_,
LLD_
PARAMETER ( BLOCK_CYCLIC_2D = 1, DLEN_ = 9, DTYPE_ = 1, CTXT_ = 2, M_ = 3, N_ =
4, MB_ = 5, NB_ = 6, RSRC_ = 7, CSRC_ = 8, LLD_ = 9 )
REAL ZERO, ONE
PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 )
INTEGER ITHVAL
PARAMETER ( ITHVAL = 10 )
LOGICAL LOWER, WANTZ
INTEGER CONTEXTC, CSRC_A, I, IACOL, IAROW, ICOFFA, IINFO, INDD, INDD2, INDE,
INDE2, INDTAU, INDWORK, INDWORK2, IROFFA, IROFFZ, ISCALE, IZROW, J, K,
LCM, LCMQ, LDC, LLWORK, LWMIN, MB_A, MB_Z, MYCOL, MYPCOLC, MYPROWC,
MYROW, NB, NB_A, NB_Z, NN, NP, NPCOL, NPCOLC, NPROCS, NPROW, NPROWC,
NQ, NRC, QRMEM, RSRC_A, RSRC_Z, SIZEMQRLEFT, SIZEMQRRIGHT
REAL ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM
INTEGER DESCQR( 10 ), IDUM1( 3 ), IDUM2( 3 )
LOGICAL LSAME
INTEGER ILCM, INDXG2P, NUMROC, SL_GRIDRESHAPE
REAL PSLAMCH, PSLANSY
EXTERNAL LSAME, ILCM, INDXG2P, NUMROC, SL_GRIDRESHAPE, PSLAMCH, PSLANSY
EXTERNAL BLACS_GRIDEXIT, BLACS_GRIDINFO, CHK1MAT, DESCINIT, PCHK2MAT, PSELGET,
PSGEMR2D, PSLASCL, PSLASET, PSORMTR, PSSYTRD, PXERBLA, SCOPY, SGAMN2D,
SGAMX2D, SSCAL, SSTEQR2
INTRINSIC ICHAR, MAX, MIN, MOD, REAL, SQRT
PURPOSE
PSSYEV computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A
by calling the recommended sequence of ScaLAPACK routines.
In its present form, PSSYEV assumes a homogeneous system and makes no checks for
consistency of the eigenvalues or eigenvectors across the different processes. Because of
this, it is possible that a heterogeneous system may return incorrect results without any
error messages.
NOTES
A description vector is associated with each 2D block-cyclicly dis- tributed matrix. This
vector stores the information required to establish the mapping between a matrix entry and
its corresponding process and memory location.
In the following comments, the character _ should be read as "of the distributed matrix".
Let A be a generic term for any 2D block cyclicly distributed matrix. Its description
vector is DESCA:
NOTATION STORED IN EXPLANATION
--------------- -------------- --------------------------------------
DTYPE_A(global) DESCA( DTYPE_) The descriptor type.
CTXT_A (global) DESCA( CTXT_ ) The BLACS context handle, indicating
the BLACS process grid A is distribu-
ted over. The context itself is glo-
bal, but the handle (the integer
value) may vary.
M_A (global) DESCA( M_ ) The number of rows in the distributed
matrix A.
N_A (global) DESCA( N_ ) The number of columns in the distri-
buted matrix A.
MB_A (global) DESCA( MB_ ) The blocking factor used to distribute
the rows of A.
NB_A (global) DESCA( NB_ ) The blocking factor used to distribute
the columns of A.
RSRC_A (global) DESCA( RSRC_ ) The process row over which the first
row of the matrix A is distributed.
CSRC_A (global) DESCA( CSRC_ ) The process column over which the
first column of A is distributed.
LLD_A (local) DESCA( LLD_ ) The leading dimension of the local
array storing the local blocks of the
distributed matrix A.
LLD_A >= MAX(1,LOCr(M_A)).
Let K be the number of rows or columns of a distributed matrix, and assume that its
process grid has dimension p x q. LOCr( K ) denotes the number of elements of K that a
process would receive if K were distributed over the p processes of its process column.S
Similarly, LOCc( K ) denotes the number of elements of K that a process would receive if K
were distributed over the q processes of its process row.
The values of LOCr() and LOCc() may be determined via a call to the ScaLAPACK tool
function, NUMROC:
LOCr( M ) = NUMROC( M, MB_A, MYROW, RSRC_A, NPROW ),
LOCc( N ) = NUMROC( N, NB_A, MYCOL, CSRC_A, NPCOL ).
ARGUMENTS
NP = the number of rows local to a given process.
NQ = the number of columns local to a given process.
JOBZ (global input) CHARACTER*1
Specifies whether or not to compute the eigenvectors:
= 'N': Compute eigenvalues only.
= 'V': Compute eigenvalues and eigenvectors.
UPLO (global input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is stored:
= 'U': Upper triangular
= 'L': Lower triangular
N (global input) INTEGER
The number of rows and columns of the matrix A. N >= 0.
A (local input/workspace) block cyclic DOUBLE PRECISION array,
global dimension (N, N), local dimension ( LLD_A,
LOCc(JA+N-1) )
On entry, the symmetric matrix A. If UPLO = 'U', only the
upper triangular part of A is used to define the elements of
the symmetric matrix. If UPLO = 'L', only the lower
triangular part of A is used to define the elements of the
symmetric matrix.
On exit, the lower triangle (if UPLO='L') or the upper
triangle (if UPLO='U') of A, including the diagonal, is
destroyed.
IA (global input) INTEGER
A's global row index, which points to the beginning of the
submatrix which is to be operated on.
JA (global input) INTEGER
A's global column index, which points to the beginning of
the submatrix which is to be operated on.
DESCA (global and local input) INTEGER array of dimension DLEN_.
The array descriptor for the distributed matrix A.
If DESCA( CTXT_ ) is incorrect, PSSYEV cannot guarantee
correct error reporting.
W (global output) REAL array, dimension (N)
On normal exit, the first M entries contain the selected
eigenvalues in ascending order.
Z (local output) REAL array,
global dimension (N, N),
local dimension ( LLD_Z, LOCc(JZ+N-1) )
If JOBZ = 'V', then on normal exit the first M columns of Z
contain the orthonormal eigenvectors of the matrix
corresponding to the selected eigenvalues.
If JOBZ = 'N', then Z is not referenced.
IZ (global input) INTEGER
Z's global row index, which points to the beginning of the
submatrix which is to be operated on.
JZ (global input) INTEGER
Z's global column index, which points to the beginning of
the submatrix which is to be operated on.
DESCZ (global and local input) INTEGER array of dimension DLEN_.
The array descriptor for the distributed matrix Z.
DESCZ( CTXT_ ) must equal DESCA( CTXT_ )
WORK (local workspace/output) REAL array,
dimension (LWORK)
Version 1.0: on output, WORK(1) returns the workspace
needed to guarantee completion.
If the input parameters are incorrect, WORK(1) may also be
incorrect.
If JOBZ='N' WORK(1) = minimal=optimal amount of workspace
If JOBZ='V' WORK(1) = minimal workspace required to
generate all the eigenvectors.
LWORK (local input) INTEGER
See below for definitions of variables used to define LWORK.
If no eigenvectors are requested (JOBZ = 'N') then
LWORK >= 5*N + SIZESYTRD + 1
where
SIZESYTRD = The workspace requirement for PSSYTRD
and is MAX( NB * ( NP +1 ), 3 * NB )
If eigenvectors are requested (JOBZ = 'V' ) then
the amount of workspace required to guarantee that all
eigenvectors are computed is:
QRMEM = 2*N-2
LWMIN = 5*N + N*LDC + MAX( SIZEMQRLEFT, QRMEM ) + 1
Variable definitions:
NB = DESCA( MB_ ) = DESCA( NB_ ) =
DESCZ( MB_ ) = DESCZ( NB_ )
NN = MAX( N, NB, 2 )
DESCA( RSRC_ ) = DESCA( RSRC_ ) = DESCZ( RSRC_ ) =
DESCZ( CSRC_ ) = 0
NP = NUMROC( NN, NB, 0, 0, NPROW )
NQ = NUMROC( MAX( N, NB, 2 ), NB, 0, 0, NPCOL )
NRC = NUMROC( N, NB, MYPROWC, 0, NPROCS)
LDC = MAX( 1, NRC )
SIZEMQRLEFT = The workspace requirement for PSORMTR
when it's SIDE argument is 'L'.
With MYPROWC defined when a new context is created as:
CALL BLACS_GET( DESCA( CTXT_ ), 0, CONTEXTC )
CALL BLACS_GRIDINIT( CONTEXTC, 'R', NPROCS, 1 )
CALL BLACS_GRIDINFO( CONTEXTC, NPROWC, NPCOLC, MYPROWC,
MYPCOLC )
If LWORK = -1, the LWORK is global input and a workspace
query is assumed; the routine only calculates the minimum
size for the WORK array. The required workspace is returned
as the first element of WORK and no error message is issued
by PXERBLA.
INFO (global output) INTEGER
= 0: successful exit
< 0: If the i-th argument is an array and the j-entry had
an illegal value, then INFO = -(i*100+j), if the i-th
argument is a scalar and had an illegal value, then
INFO = -i.
> 0: If INFO = 1 through N, the i(th) eigenvalue did not
converge in SSTEQR2 after a total of 30*N iterations.
If INFO = N+1, then PSSYEV has detected heterogeneity
by finding that eigenvalues were not identical across
the process grid. In this case, the accuracy of
the results from PSSYEV cannot be guaranteed.