Provided by: scalapack-doc_1.5-11_all 
NAME
PDGESVD - compute the singular value decomposition (SVD) of an M-by-N matrix A, optionally
computing the left and/or right singular vectors
SYNOPSIS
SUBROUTINE PDGESVD( JOBU, JOBVT, M, N, A, IA, JA, DESCA, S, U, IU, JU, DESCU, VT, IVT,
JVT, DESCVT, WORK, LWORK, INFO )
CHARACTER JOBU, JOBVT
INTEGER IA, INFO, IU, IVT, JA, JU, JVT, LWORK, M, N
INTEGER DESCA( * ), DESCU( * ), DESCVT( * )
DOUBLE PRECISION A( * ), S( * ), U( * ), VT( * ), WORK( * )
PURPOSE
PDGESVD computes the singular value decomposition (SVD) of an M-by-N matrix A, optionally
computing the left and/or right singular vectors. The SVD is written as
A = U * SIGMA * transpose(V)
where SIGMA is an M-by-N matrix which is zero except for its min(M,N) diagonal elements, U
is an M-by-M orthogonal matrix, and V is an N-by-N orthogonal matrix. The diagonal
elements of SIGMA are the singular values of A and the columns of U and V are the
corresponding right and left singular vectors, respectively. The singular values are
returned in array S in decreasing order and only the first min(M,N) columns of U and rows
of VT = V**T are computed.
Notes
=====
Each global data object is described by an associated description vector. This vector
stores the information required to establish the mapping between an object element and its
corresponding process and memory location.
Let A be a generic term for any 2D block cyclicly distributed array. Such a global array
has an associated description vector DESCA. In the following comments, the character _
should be read as "of the global array".
NOTATION STORED IN EXPLANATION
--------------- -------------- -------------------------------------- DTYPE_A(global)
DESCA( DTYPE_ )The descriptor type. In this case,
DTYPE_A = 1.
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 global
array A.
N_A (global) DESCA( N_ ) The number of columns in the global
array A.
MB_A (global) DESCA( MB_ ) The blocking factor used to distribute
the rows of the array.
NB_A (global) DESCA( NB_ ) The blocking factor used to distribute
the columns of the array.
RSRC_A (global) DESCA( RSRC_ ) The process row over which the first
row of the array A is distributed. CSRC_A (global) DESCA(
CSRC_ ) The process column over which the
first column of the array A is
distributed.
LLD_A (local) DESCA( LLD_ ) The leading dimension of the local
array. 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.
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 ). An upper bound for these
quantities may be computed by:
LOCr( M ) <= ceil( ceil(M/MB_A)/NPROW )*MB_A
LOCc( N ) <= ceil( ceil(N/NB_A)/NPCOL )*NB_A
ARGUMENTS
MP = number of local rows in A and U NQ = number of local columns in A and VT SIZE = min(
M, N ) SIZEQ = number of local columns in U SIZEP = number of local rows in VT
JOBU (global input) CHARACTER*1
Specifies options for computing all or part of the matrix U:
= 'V': the first SIZE columns of U (the left singular vectors) are returned in
the array U; = 'N': no columns of U (no left singular vectors) are computed.
JOBVT (global input) CHARACTER*1
Specifies options for computing all or part of the matrix V**T:
= 'V': the first SIZE rows of V**T (the right singular vectors) are returned in
the array VT; = 'N': no rows of V**T (no right singular vectors) are computed.
M (global input) INTEGER
The number of rows of the input matrix A. M >= 0.
N (global input) INTEGER
The number of columns of the input matrix A. N >= 0.
A (local input/workspace) block cyclic DOUBLE PRECISION array,
global dimension (M, N), local dimension (MP, NQ) On exit, the contents of A are
destroyed.
IA (global input) INTEGER
The row index in the global array A indicating the first row of sub( A ).
JA (global input) INTEGER
The column index in the global array A indicating the first column of sub( A ).
DESCA (global input) INTEGER array of dimension DLEN_
The array descriptor for the distributed matrix A.
S (global output) DOUBLE PRECISION array, dimension SIZE
The singular values of A, sorted so that S(i) >= S(i+1).
U (local output) DOUBLE PRECISION array, local dimension
(MP, SIZEQ), global dimension (M, SIZE) if JOBU = 'V', U contains the first
min(m,n) columns of U if JOBU = 'N', U is not referenced.
IU (global input) INTEGER
The row index in the global array U indicating the first row of sub( U ).
JU (global input) INTEGER
The column index in the global array U indicating the first column of sub( U ).
DESCU (global input) INTEGER array of dimension DLEN_
The array descriptor for the distributed matrix U.
VT (local output) DOUBLE PRECISION array, local dimension
(SIZEP, NQ), global dimension (SIZE, N). If JOBVT = 'V', VT contains the first
SIZE rows of V**T. If JOBVT = 'N', VT is not referenced.
IVT (global input) INTEGER
The row index in the global array VT indicating the first row of sub( VT ).
JVT (global input) INTEGER
The column index in the global array VT indicating the first column of sub( VT ).
DESCVT (global input) INTEGER array of dimension DLEN_
The array descriptor for the distributed matrix VT.
WORK (local workspace/output) DOUBLE PRECISION array, dimension
(LWORK) On exit, if INFO = 0, WORK(1) returns the optimal LWORK;
LWORK (local input) INTEGER
The dimension of the array WORK.
LWORK > 2 + 6*SIZEB + MAX(WATOBD, WBDTOSVD),
where SIZEB = MAX(M,N), and WATOBD and WBDTOSVD refer, respectively, to the
workspace required to bidiagonalize the matrix A and to go from the bidiagonal
matrix to the singular value decomposition U*S*VT.
For WATOBD, the following holds:
WATOBD = MAX(MAX(WPDLANGE,WPDGEBRD), MAX(WPDLARED2D,WPDLARED1D)),
where WPDLANGE, WPDLARED1D, WPDLARED2D, WPDGEBRD are the workspaces required
respectively for the subprograms PDLANGE, PDLARED1D, PDLARED2D, PDGEBRD. Using the
standard notation
MP = NUMROC( M, MB, MYROW, DESCA( CTXT_ ), NPROW), NQ = NUMROC( N, NB, MYCOL,
DESCA( LLD_ ), NPCOL),
the workspaces required for the above subprograms are
WPDLANGE = MP, WPDLARED1D = NQ0, WPDLARED2D = MP0, WPDGEBRD = NB*(MP + NQ + 1) +
NQ,
where NQ0 and MP0 refer, respectively, to the values obtained at MYCOL = 0 and
MYROW = 0. In general, the upper limit for the workspace is given by a workspace
required on processor (0,0):
WATOBD <= NB*(MP0 + NQ0 + 1) + NQ0.
In case of a homogeneous process grid this upper limit can be used as an estimate
of the minimum workspace for every processor.
For WBDTOSVD, the following holds:
WBDTOSVD = SIZE*(WANTU*NRU + WANTVT*NCVT) + MAX(WDBDSQR, MAX(WANTU*WPDORMBRQLN,
WANTVT*WPDORMBRPRT)),
where
1, if left(right) singular vectors are wanted WANTU(WANTVT) = 0, otherwise
and WDBDSQR, WPDORMBRQLN and WPDORMBRPRT refer respectively to the workspace required for
the subprograms DBDSQR, PDORMBR(QLN), and PDORMBR(PRT), where QLN and PRT are the values of
the arguments VECT, SIDE, and TRANS in the call to PDORMBR. NRU is equal to the local
number of rows of the matrix U when distributed 1-dimensional "column" of processes.
Analogously, NCVT is equal to the local number of columns of the matrix VT when distributed
across 1-dimensional "row" of processes. Calling the LAPACK procedure DBDSQR requires
WDBDSQR = MAX(1, 2*SIZE + (2*SIZE - 4)*MAX(WANTU, WANTVT))
on every processor. Finally,
WPDORMBRQLN = MAX( (NB*(NB-1))/2, (SIZEQ+MP)*NB)+NB*NB, WPDORMBRPRT = MAX( (MB*(MB-1))/2,
(SIZEP+NQ)*MB )+MB*MB,
If LIWORK = -1, then LIWORK 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 (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if SBDSQR did not converge If INFO = MIN(M,N) + 1, then PDGESVD has detected
heterogeneity by finding that eigenvalues were not identical across the process
grid. In this case, the accuracy of the results from PDGESVD cannot be guaranteed.