SUBROUTINE PSSYGVX( IBTYPE, JOBZ, RANGE, UPLO, N, A, IA, JA,
$ DESCA, B, IB, JB, DESCB, VL, VU, IL, IU,
$ ABSTOL, M, NZ, W, ORFAC, Z, IZ, JZ, DESCZ,
$ WORK, LWORK, IWORK, LIWORK, IFAIL, ICLUSTR,
$ GAP, INFO )
*
* -- ScaLAPACK routine (version 1.7) --
* University of Tennessee, Knoxville, Oak Ridge National Laboratory,
* and University of California, Berkeley.
* October 15, 1999
*
* .. Scalar Arguments ..
CHARACTER JOBZ, RANGE, UPLO
INTEGER IA, IB, IBTYPE, IL, INFO, IU, IZ, JA, JB, JZ,
$ LIWORK, LWORK, M, N, NZ
REAL ABSTOL, ORFAC, VL, VU
* ..
* .. Array Arguments ..
*
INTEGER DESCA( * ), DESCB( * ), DESCZ( * ),
$ ICLUSTR( * ), IFAIL( * ), IWORK( * )
REAL A( * ), B( * ), GAP( * ), W( * ), WORK( * ),
$ Z( * )
* ..
*
* Purpose
*
* =======
*
* PSSYGVX computes all the eigenvalues, and optionally,
* the eigenvectors
* of a real generalized SY-definite eigenproblem, of the form
* sub( A )*x=(lambda)*sub( B )*x, sub( A )*sub( B )x=(lambda)*x, or
* sub( B )*sub( A )*x=(lambda)*x.
* Here sub( A ) denoting A( IA:IA+N-1, JA:JA+N-1 ) is assumed to be
* SY, and sub( B ) denoting B( IB:IB+N-1, JB:JB+N-1 ) is assumed
* to be symmetric positive definite.
*
* 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
* =========
*
* IBTYPE (global input) INTEGER
* Specifies the problem type to be solved:
* = 1: sub( A )*x = (lambda)*sub( B )*x
* = 2: sub( A )*sub( B )*x = (lambda)*x
* = 3: sub( B )*sub( A )*x = (lambda)*x
*
* JOBZ (global input) CHARACTER*1
* = 'N': Compute eigenvalues only;
* = 'V': Compute eigenvalues and eigenvectors.
*
* RANGE (global input) CHARACTER*1
* = 'A': all eigenvalues will be found.
* = 'V': all eigenvalues in the interval [VL,VU] will be found.
* = 'I': the IL-th through IU-th eigenvalues will be found.
*
* UPLO (global input) CHARACTER*1
* = 'U': Upper triangles of sub( A ) and sub( B ) are stored;
* = 'L': Lower triangles of sub( A ) and sub( B ) are stored.
*
* N (global input) INTEGER
* The order of the matrices sub( A ) and sub( B ). N >= 0.
*
* A (local input/local output) REAL pointer into the
* local memory to an array of dimension (LLD_A, LOCc(JA+N-1)).
* On entry, this array contains the local pieces of the
* N-by-N symmetric distributed matrix sub( A ). If UPLO = 'U',
* the leading N-by-N upper triangular part of sub( A ) contains
* the upper triangular part of the matrix. If UPLO = 'L', the
* leading N-by-N lower triangular part of sub( A ) contains
* the lower triangular part of the matrix.
*
* On exit, if JOBZ = 'V', then if INFO = 0, sub( A ) contains
* the distributed matrix Z of eigenvectors. The eigenvectors
* are normalized as follows:
* if IBTYPE = 1 or 2, Z**T*sub( B )*Z = I;
* if IBTYPE = 3, Z**T*inv( sub( B ) )*Z = I.
* If JOBZ = 'N', then on exit the upper triangle (if UPLO='U')
* or the lower triangle (if UPLO='L') of sub( A ), including
* the diagonal, is 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 and local input) INTEGER array of dimension DLEN_.
* The array descriptor for the distributed matrix A.
* If DESCA( CTXT_ ) is incorrect, PSSYGVX cannot guarantee
* correct error reporting.
*
* B (local input/local output) REAL pointer into the
* local memory to an array of dimension (LLD_B, LOCc(JB+N-1)).
* On entry, this array contains the local pieces of the
* N-by-N symmetric distributed matrix sub( B ). If UPLO = 'U',
* the leading N-by-N upper triangular part of sub( B ) contains
* the upper triangular part of the matrix. If UPLO = 'L', the
* leading N-by-N lower triangular part of sub( B ) contains
* the lower triangular part of the matrix.
*
* On exit, if INFO <= N, the part of sub( B ) containing the
* matrix is overwritten by the triangular factor U or L from
* the Cholesky factorization sub( B ) = U**T*U or
* sub( B ) = L*L**T.
*
* IB (global input) INTEGER
* The row index in the global array B indicating the first
* row of sub( B ).
*
* JB (global input) INTEGER
* The column index in the global array B indicating the
* first column of sub( B ).
*
* DESCB (global and local input) INTEGER array of dimension DLEN_.
* The array descriptor for the distributed matrix B.
* DESCB( CTXT_ ) must equal DESCA( CTXT_ )
*
* VL (global input) REAL
* If RANGE='V', the lower bound of the interval to be searched
* for eigenvalues. Not referenced if RANGE = 'A' or 'I'.
*
* VU (global input) REAL
* If RANGE='V', the upper bound of the interval to be searched
* for eigenvalues. Not referenced if RANGE = 'A' or 'I'.
*
* IL (global input) INTEGER
* If RANGE='I', the index (from smallest to largest) of the
* smallest eigenvalue to be returned. IL >= 1.
* Not referenced if RANGE = 'A' or 'V'.
*
* IU (global input) INTEGER
* If RANGE='I', the index (from smallest to largest) of the
* largest eigenvalue to be returned. min(IL,N) <= IU <= N.
* Not referenced if RANGE = 'A' or 'V'.
*
* ABSTOL (global input) REAL
* If JOBZ='V', setting ABSTOL to PSLAMCH( CONTEXT, 'U') yields
* the most orthogonal eigenvectors.
*
* The absolute error tolerance for the eigenvalues.
* An approximate eigenvalue is accepted as converged
* when it is determined to lie in an interval [a,b]
* of width less than or equal to
*
* ABSTOL + EPS * max( |a|,|b| ) ,
*
* where EPS is the machine precision. If ABSTOL is less than
* or equal to zero, then EPS*norm(T) will be used in its place,
* where norm(T) is the 1-norm of the tridiagonal matrix
* obtained by reducing A to tridiagonal form.
*
* Eigenvalues will be computed most accurately when ABSTOL is
* set to twice the underflow threshold 2*PSLAMCH('S') not zero.
* If this routine returns with ((MOD(INFO,2).NE.0) .OR.
* (MOD(INFO/8,2).NE.0)), indicating that some eigenvalues or
* eigenvectors did not converge, try setting ABSTOL to
* 2*PSLAMCH('S').
*
* See "Computing Small Singular Values of Bidiagonal Matrices
* with Guaranteed High Relative Accuracy," by Demmel and
* Kahan, LAPACK Working Note #3.
*
* See "On the correctness of Parallel Bisection in Floating
* Point" by Demmel, Dhillon and Ren, LAPACK Working Note #70
*
* M (global output) INTEGER
* Total number of eigenvalues found. 0 <= M <= N.
*
* NZ (global output) INTEGER
* Total number of eigenvectors computed. 0 <= NZ <= M.
* The number of columns of Z that are filled.
* If JOBZ .NE. 'V', NZ is not referenced.
* If JOBZ .EQ. 'V', NZ = M unless the user supplies
* insufficient space and PSSYGVX is not able to detect this
* before beginning computation. To get all the eigenvectors
* requested, the user must supply both sufficient
* space to hold the eigenvectors in Z (M .LE. DESCZ(N_))
* and sufficient workspace to compute them. (See LWORK below.)
* PSSYGVX is always able to detect insufficient space without
* computation unless RANGE .EQ. 'V'.
*
* W (global output) REAL array, dimension (N)
* On normal exit, the first M entries contain the selected
* eigenvalues in ascending order.
*
* ORFAC (global input) REAL
* Specifies which eigenvectors should be reorthogonalized.
* Eigenvectors that correspond to eigenvalues which are within
* tol=ORFAC*norm(A) of each other are to be reorthogonalized.
* However, if the workspace is insufficient (see LWORK),
* tol may be decreased until all eigenvectors to be
* reorthogonalized can be stored in one process.
* No reorthogonalization will be done if ORFAC equals zero.
* A default value of 10^-3 is used if ORFAC is negative.
* ORFAC should be identical on all processes.
*
* 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 an eigenvector
* fails to converge, then that column of Z contains the latest
* approximation to the eigenvector, and the index of the
* eigenvector is returned in IFAIL.
* If JOBZ = 'N', then Z is not referenced.
*
* IZ (global input) INTEGER
* The row index in the global array Z indicating the first
* row of sub( Z ).
*
* JZ (global input) INTEGER
* The column index in the global array Z indicating the
* first column of sub( Z ).
*
* 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 max(3,LWORK)
* if JOBZ='N' WORK(1) = optimal amount of workspace
* required to compute eigenvalues efficiently
* if JOBZ='V' WORK(1) = optimal amount of workspace
* required to compute eigenvalues and eigenvectors
* efficiently with no guarantee on orthogonality.
* If RANGE='V', it is assumed that all eigenvectors
* may be required.
*
* 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 + MAX( 5 * NN, NB * ( NP0 + 1 ) )
* If eigenvectors are requested (JOBZ = 'V' ) then
* the amount of workspace required to guarantee that all
* eigenvectors are computed is:
* LWORK >= 5 * N + MAX( 5*NN, NP0 * MQ0 + 2 * NB * NB ) +
* ICEIL( NEIG, NPROW*NPCOL)*NN
*
* The computed eigenvectors may not be orthogonal if the
* minimal workspace is supplied and ORFAC is too small.
* If you want to guarantee orthogonality (at the cost
* of potentially poor performance) you should add
* the following to LWORK:
* (CLUSTERSIZE-1)*N
* where CLUSTERSIZE is the number of eigenvalues in the
* largest cluster, where a cluster is defined as a set of
* close eigenvalues: { W(K),...,W(K+CLUSTERSIZE-1) |
* W(J+1) <= W(J) + ORFAC*2*norm(A) }
* Variable definitions:
* NEIG = number of eigenvectors requested
* NB = DESCA( MB_ ) = DESCA( NB_ ) = DESCZ( MB_ ) =
* DESCZ( NB_ )
* NN = MAX( N, NB, 2 )
* DESCA( RSRC_ ) = DESCA( NB_ ) = DESCZ( RSRC_ ) =
* DESCZ( CSRC_ ) = 0
* NP0 = NUMROC( NN, NB, 0, 0, NPROW )
* MQ0 = NUMROC( MAX( NEIG, NB, 2 ), NB, 0, 0, NPCOL )
* ICEIL( X, Y ) is a ScaLAPACK function returning
* ceiling(X/Y)
*
* When LWORK is too small:
* If LWORK is too small to guarantee orthogonality,
* PSSYGVX attempts to maintain orthogonality in
* the clusters with the smallest
* spacing between the eigenvalues.
* If LWORK is too small to compute all the eigenvectors
* requested, no computation is performed and INFO=-23
* is returned. Note that when RANGE='V', PSSYGVX does
* not know how many eigenvectors are requested until
* the eigenvalues are computed. Therefore, when RANGE='V'
* and as long as LWORK is large enough to allow PSSYGVX to
* compute the eigenvalues, PSSYGVX will compute the
* eigenvalues and as many eigenvectors as it can.
*
* Relationship between workspace, orthogonality & performance:
* Greater performance can be achieved if adequate workspace
* is provided. On the other hand, in some situations,
* performance can decrease as the workspace provided
* increases above the workspace amount shown below:
*
* For optimal performance, greater workspace may be
* needed, i.e.
* LWORK >= MAX( LWORK, 5 * N + NSYTRD_LWOPT,
* NSYGST_LWOPT )
* Where:
* LWORK, as defined previously, depends upon the number
* of eigenvectors requested, and
* NSYTRD_LWOPT = N + 2*( ANB+1 )*( 4*NPS+2 ) +
* ( NPS + 3 ) * NPS
* NSYGST_LWOPT = 2*NP0*NB + NQ0*NB + NB*NB
*
* ANB = PJLAENV( DESCA( CTXT_), 3, 'PSSYTTRD', 'L',
* 0, 0, 0, 0)
* SQNPC = INT( SQRT( DBLE( NPROW * NPCOL ) ) )
* NPS = MAX( NUMROC( N, 1, 0, 0, SQNPC ), 2*ANB )
* NB = DESCA( MB_ )
* NP0 = NUMROC( N, NB, 0, 0, NPROW )
* NQ0 = NUMROC( N, NB, 0, 0, NPCOL )
*
* NUMROC is a ScaLAPACK tool functions;
* PJLAENV is a ScaLAPACK envionmental inquiry function
* MYROW, MYCOL, NPROW and NPCOL can be determined by
* calling the subroutine BLACS_GRIDINFO.
*
* For large N, no extra workspace is needed, however the
* biggest boost in performance comes for small N, so it
* is wise to provide the extra workspace (typically less
* than a Megabyte per process).
*
* If CLUSTERSIZE >= N/SQRT(NPROW*NPCOL), then providing
* enough space to compute all the eigenvectors
* orthogonally will cause serious degradation in
* performance. In the limit (i.e. CLUSTERSIZE = N-1)
* PSSTEIN will perform no better than SSTEIN on 1 processor.
* For CLUSTERSIZE = N/SQRT(NPROW*NPCOL) reorthogonalizing
* all eigenvectors will increase the total execution time
* by a factor of 2 or more.
* For CLUSTERSIZE > N/SQRT(NPROW*NPCOL) execution time will
* grow as the square of the cluster size, all other factors
* remaining equal and assuming enough workspace. Less
* workspace means less reorthogonalization but faster
* execution.
*
* If LWORK = -1, then LWORK is global input and a workspace
* query is assumed; the routine only calculates the size
* required for optimal performance on all work arrays.
* Each of these values is returned in the first entry of the
* corresponding work array, and no error message is issued by
* PXERBLA.
*
*
* IWORK (local workspace) INTEGER array
* On return, IWORK(1) contains the amount of integer workspace
* required.
*
* LIWORK (local input) INTEGER
* size of IWORK
* LIWORK >= 6 * NNP
* Where:
* NNP = MAX( N, NPROW*NPCOL + 1, 4 )
*
* If LIWORK = -1, then LIWORK is global input and a workspace
* query is assumed; the routine only calculates the minimum
* and optimal size for all work arrays. Each of these
* values is returned in the first entry of the corresponding
* work array, and no error message is issued by PXERBLA.
*
* IFAIL (output) INTEGER array, dimension (N)
* IFAIL provides additional information when INFO .NE. 0
* If (MOD(INFO/16,2).NE.0) then IFAIL(1) indicates the order of
* the smallest minor which is not positive definite.
* If (MOD(INFO,2).NE.0) on exit, then IFAIL contains the
* indices of the eigenvectors that failed to converge.
*
* If neither of the above error conditions hold and JOBZ = 'V',
* then the first M elements of IFAIL are set to zero.
*
* ICLUSTR (global output) integer array, dimension (2*NPROW*NPCOL)
* This array contains indices of eigenvectors corresponding to
* a cluster of eigenvalues that could not be reorthogonalized
* due to insufficient workspace (see LWORK, ORFAC and INFO).
* Eigenvectors corresponding to clusters of eigenvalues indexed
* ICLUSTR(2*I-1) to ICLUSTR(2*I), could not be
* reorthogonalized due to lack of workspace. Hence the
* eigenvectors corresponding to these clusters may not be
* orthogonal. ICLUSTR() is a zero terminated array.
* (ICLUSTR(2*K).NE.0 .AND. ICLUSTR(2*K+1).EQ.0) if and only if
* K is the number of clusters
* ICLUSTR is not referenced if JOBZ = 'N'
*
* GAP (global output) REAL array,
* dimension (NPROW*NPCOL)
* This array contains the gap between eigenvalues whose
* eigenvectors could not be reorthogonalized. The output
* values in this array correspond to the clusters indicated
* by the array ICLUSTR. As a result, the dot product between
* eigenvectors correspoding to the I^th cluster may be as high
* as ( C * n ) / GAP(I) where C is a small constant.
*
* 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 (MOD(INFO,2).NE.0), then one or more eigenvectors
* failed to converge. Their indices are stored
* in IFAIL. Send e-mail to scalapack@cs.utk.edu
* if (MOD(INFO/2,2).NE.0),then eigenvectors corresponding
* to one or more clusters of eigenvalues could not be
* reorthogonalized because of insufficient workspace.
* The indices of the clusters are stored in the array
* ICLUSTR.
* if (MOD(INFO/4,2).NE.0), then space limit prevented
* PSSYGVX from computing all of the eigenvectors
* between VL and VU. The number of eigenvectors
* computed is returned in NZ.
* if (MOD(INFO/8,2).NE.0), then PSSTEBZ failed to
* compute eigenvalues.
* Send e-mail to scalapack@cs.utk.edu
* if (MOD(INFO/16,2).NE.0), then B was not positive
* definite. IFAIL(1) indicates the order of
* the smallest minor which is not positive definite.
*
* Alignment requirements
* ======================
*
* The distributed submatrices A(IA:*, JA:*), C(IC:IC+M-1,JC:JC+N-1),
* and B( IB:IB+N-1, JB:JB+N-1 ) must verify some alignment properties,
* namely the following expressions should be true:
*
* DESCA(MB_) = DESCA(NB_)
* IA = IB = IZ
* JA = IB = JZ
* DESCA(M_) = DESCB(M_) =DESCZ(M_)
* DESCA(N_) = DESCB(N_)= DESCZ(N_)
* DESCA(MB_) = DESCB(MB_) = DESCZ(MB_)
* DESCA(NB_) = DESCB(NB_) = DESCZ(NB_)
* DESCA(RSRC_) = DESCB(RSRC_) = DESCZ(RSRC_)
* DESCA(CSRC_) = DESCB(CSRC_) = DESCZ(CSRC_)
* MOD( IA-1, DESCA( MB_ ) ) = 0
* MOD( JA-1, DESCA( NB_ ) ) = 0
* MOD( IB-1, DESCB( MB_ ) ) = 0
* MOD( JB-1, DESCB( NB_ ) ) = 0
*
* =====================================================================
*
* .. Parameters ..
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 ONE
PARAMETER ( ONE = 1.0E+0 )
REAL FIVE, ZERO
PARAMETER ( FIVE = 5.0E+0, ZERO = 0.0E+0 )
INTEGER IERRNPD
PARAMETER ( IERRNPD = 16 )
* ..
* .. Local Scalars ..
LOGICAL ALLEIG, INDEIG, LQUERY, UPPER, VALEIG, WANTZ
CHARACTER TRANS
INTEGER ANB, IACOL, IAROW, IBCOL, IBROW, ICOFFA,
$ ICOFFB, ICTXT, IROFFA, IROFFB, LIWMIN, LWMIN,
$ LWOPT, MQ0, MYCOL, MYROW, NB, NEIG, NN, NP0,
$ NPCOL, NPROW, NPS, NQ0, NSYGST_LWOPT,
$ NSYTRD_LWOPT, SQNPC
REAL EPS, SCALE
* ..
* .. Local Arrays ..
INTEGER IDUM1( 5 ), IDUM2( 5 )
* ..
* .. External Functions ..
LOGICAL LSAME
INTEGER ICEIL, INDXG2P, NUMROC, PJLAENV
REAL PSLAMCH
EXTERNAL LSAME, ICEIL, INDXG2P, NUMROC, PJLAENV, PSLAMCH
* ..
* .. External Subroutines ..
EXTERNAL BLACS_GRIDINFO, CHK1MAT, PCHK1MAT, PCHK2MAT,
$ PSPOTRF, PSSYEVX, PSSYNGST, PSTRMM, PSTRSM,
$ PXERBLA, SGEBR2D, SGEBS2D, SSCAL
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, DBLE, ICHAR, INT, MAX, MIN, MOD, REAL,
$ SQRT
* ..
* .. Executable Statements ..
* This is just to keep ftnchek and toolpack/1 happy
IF( BLOCK_CYCLIC_2D*CSRC_*CTXT_*DLEN_*DTYPE_*LLD_*MB_*M_*NB_*N_*
$ RSRC_.LT.0 )RETURN
*
* Get grid parameters
*
ICTXT = DESCA( CTXT_ )
CALL BLACS_GRIDINFO( ICTXT, NPROW, NPCOL, MYROW, MYCOL )
*
* Test the input parameters
*
INFO = 0
IF( NPROW.EQ.-1 ) THEN
INFO = -( 900+CTXT_ )
ELSE IF( DESCA( CTXT_ ).NE.DESCB( CTXT_ ) ) THEN
INFO = -( 1300+CTXT_ )
ELSE IF( DESCA( CTXT_ ).NE.DESCZ( CTXT_ ) ) THEN
INFO = -( 2600+CTXT_ )
ELSE
*
* Get machine constants.
*
EPS = PSLAMCH( DESCA( CTXT_ ), 'Precision' )
*
WANTZ = LSAME( JOBZ, 'V' )
UPPER = LSAME( UPLO, 'U' )
ALLEIG = LSAME( RANGE, 'A' )
VALEIG = LSAME( RANGE, 'V' )
INDEIG = LSAME( RANGE, 'I' )
CALL CHK1MAT( N, 4, N, 4, IA, JA, DESCA, 9, INFO )
CALL CHK1MAT( N, 4, N, 4, IB, JB, DESCB, 13, INFO )
CALL CHK1MAT( N, 4, N, 4, IZ, JZ, DESCZ, 26, INFO )
IF( INFO.EQ.0 ) THEN
IF( MYROW.EQ.0 .AND. MYCOL.EQ.0 ) THEN
WORK( 1 ) = ABSTOL
IF( VALEIG ) THEN
WORK( 2 ) = VL
WORK( 3 ) = VU
ELSE
WORK( 2 ) = ZERO
WORK( 3 ) = ZERO
END IF
CALL SGEBS2D( DESCA( CTXT_ ), 'ALL', ' ', 3, 1, WORK, 3 )
ELSE
CALL SGEBR2D( DESCA( CTXT_ ), 'ALL', ' ', 3, 1, WORK, 3,
$ 0, 0 )
END IF
IAROW = INDXG2P( IA, DESCA( MB_ ), MYROW, DESCA( RSRC_ ),
$ NPROW )
IBROW = INDXG2P( IB, DESCB( MB_ ), MYROW, DESCB( RSRC_ ),
$ NPROW )
IACOL = INDXG2P( JA, DESCA( NB_ ), MYCOL, DESCA( CSRC_ ),
$ NPCOL )
IBCOL = INDXG2P( JB, DESCB( NB_ ), MYCOL, DESCB( CSRC_ ),
$ NPCOL )
IROFFA = MOD( IA-1, DESCA( MB_ ) )
ICOFFA = MOD( JA-1, DESCA( NB_ ) )
IROFFB = MOD( IB-1, DESCB( MB_ ) )
ICOFFB = MOD( JB-1, DESCB( NB_ ) )
*
* Compute the total amount of space needed
*
LQUERY = .FALSE.
IF( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 )
$ LQUERY = .TRUE.
*
LIWMIN = 6*MAX( N, ( NPROW*NPCOL )+1, 4 )
*
NB = DESCA( MB_ )
NN = MAX( N, NB, 2 )
NP0 = NUMROC( NN, NB, 0, 0, NPROW )
*
IF( ( .NOT.WANTZ ) .OR. ( VALEIG .AND. ( .NOT.LQUERY ) ) )
$ THEN
LWMIN = 5*N + MAX( 5*NN, NB*( NP0+1 ) )
IF( WANTZ ) THEN
MQ0 = NUMROC( MAX( N, NB, 2 ), NB, 0, 0, NPCOL )
LWOPT = 5*N + MAX( 5*NN, NP0*MQ0+2*NB*NB )
ELSE
LWOPT = LWMIN
END IF
NEIG = 0
ELSE
IF( ALLEIG .OR. VALEIG ) THEN
NEIG = N
ELSE IF( INDEIG ) THEN
NEIG = IU - IL + 1
END IF
MQ0 = NUMROC( MAX( NEIG, NB, 2 ), NB, 0, 0, NPCOL )
LWMIN = 5*N + MAX( 5*NN, NP0*MQ0+2*NB*NB ) +
$ ICEIL( NEIG, NPROW*NPCOL )*NN
LWOPT = LWMIN
*
END IF
*
* Compute how much workspace is needed to use the
* new TRD and GST algorithms
*
ANB = PJLAENV( ICTXT, 3, 'PSSYTTRD', 'L', 0, 0, 0, 0 )
SQNPC = INT( SQRT( DBLE( NPROW*NPCOL ) ) )
NPS = MAX( NUMROC( N, 1, 0, 0, SQNPC ), 2*ANB )
NSYTRD_LWOPT = 2*( ANB+1 )*( 4*NPS+2 ) + ( NPS+4 )*NPS
NB = DESCA( MB_ )
NP0 = NUMROC( N, NB, 0, 0, NPROW )
NQ0 = NUMROC( N, NB, 0, 0, NPCOL )
NSYGST_LWOPT = 2*NP0*NB + NQ0*NB + NB*NB
LWOPT = MAX( LWOPT, N+NSYTRD_LWOPT, NSYGST_LWOPT )
*
* Version 1.0 Limitations
*
IF( IBTYPE.LT.1 .OR. IBTYPE.GT.3 ) THEN
INFO = -1
ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN
INFO = -2
ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN
INFO = -3
ELSE IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN
INFO = -4
ELSE IF( N.LT.0 ) THEN
INFO = -5
ELSE IF( IROFFA.NE.0 ) THEN
INFO = -7
ELSE IF( ICOFFA.NE.0 ) THEN
INFO = -8
ELSE IF( DESCA( MB_ ).NE.DESCA( NB_ ) ) THEN
INFO = -( 900+NB_ )
ELSE IF( DESCA( M_ ).NE.DESCB( M_ ) ) THEN
INFO = -( 1300+M_ )
ELSE IF( DESCA( N_ ).NE.DESCB( N_ ) ) THEN
INFO = -( 1300+N_ )
ELSE IF( DESCA( MB_ ).NE.DESCB( MB_ ) ) THEN
INFO = -( 1300+MB_ )
ELSE IF( DESCA( NB_ ).NE.DESCB( NB_ ) ) THEN
INFO = -( 1300+NB_ )
ELSE IF( DESCA( RSRC_ ).NE.DESCB( RSRC_ ) ) THEN
INFO = -( 1300+RSRC_ )
ELSE IF( DESCA( CSRC_ ).NE.DESCB( CSRC_ ) ) THEN
INFO = -( 1300+CSRC_ )
ELSE IF( DESCA( CTXT_ ).NE.DESCB( CTXT_ ) ) THEN
INFO = -( 1300+CTXT_ )
ELSE IF( DESCA( M_ ).NE.DESCZ( M_ ) ) THEN
INFO = -( 2200+M_ )
ELSE IF( DESCA( N_ ).NE.DESCZ( N_ ) ) THEN
INFO = -( 2200+N_ )
ELSE IF( DESCA( MB_ ).NE.DESCZ( MB_ ) ) THEN
INFO = -( 2200+MB_ )
ELSE IF( DESCA( NB_ ).NE.DESCZ( NB_ ) ) THEN
INFO = -( 2200+NB_ )
ELSE IF( DESCA( RSRC_ ).NE.DESCZ( RSRC_ ) ) THEN
INFO = -( 2200+RSRC_ )
ELSE IF( DESCA( CSRC_ ).NE.DESCZ( CSRC_ ) ) THEN
INFO = -( 2200+CSRC_ )
ELSE IF( DESCA( CTXT_ ).NE.DESCZ( CTXT_ ) ) THEN
INFO = -( 2200+CTXT_ )
ELSE IF( IROFFB.NE.0 .OR. IBROW.NE.IAROW ) THEN
INFO = -11
ELSE IF( ICOFFB.NE.0 .OR. IBCOL.NE.IACOL ) THEN
INFO = -12
ELSE IF( VALEIG .AND. N.GT.0 .AND. VU.LE.VL ) THEN
INFO = -15
ELSE IF( INDEIG .AND. ( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) )
$ THEN
INFO = -16
ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) )
$ THEN
INFO = -17
ELSE IF( VALEIG .AND. ( ABS( WORK( 2 )-VL ).GT.FIVE*EPS*
$ ABS( VL ) ) ) THEN
INFO = -14
ELSE IF( VALEIG .AND. ( ABS( WORK( 3 )-VU ).GT.FIVE*EPS*
$ ABS( VU ) ) ) THEN
INFO = -15
ELSE IF( ABS( WORK( 1 )-ABSTOL ).GT.FIVE*EPS*ABS( ABSTOL ) )
$ THEN
INFO = -18
ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN
INFO = -28
ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN
INFO = -30
END IF
END IF
IDUM1( 1 ) = IBTYPE
IDUM2( 1 ) = 1
IF( WANTZ ) THEN
IDUM1( 2 ) = ICHAR( 'V' )
ELSE
IDUM1( 2 ) = ICHAR( 'N' )
END IF
IDUM2( 2 ) = 2
IF( UPPER ) THEN
IDUM1( 3 ) = ICHAR( 'U' )
ELSE
IDUM1( 3 ) = ICHAR( 'L' )
END IF
IDUM2( 3 ) = 3
IF( ALLEIG ) THEN
IDUM1( 4 ) = ICHAR( 'A' )
ELSE IF( INDEIG ) THEN
IDUM1( 4 ) = ICHAR( 'I' )
ELSE
IDUM1( 4 ) = ICHAR( 'V' )
END IF
IDUM2( 4 ) = 4
IF( LQUERY ) THEN
IDUM1( 5 ) = -1
ELSE
IDUM1( 5 ) = 1
END IF
IDUM2( 5 ) = 5
CALL PCHK2MAT( N, 4, N, 4, IA, JA, DESCA, 9, N, 4, N, 4, IB,
$ JB, DESCB, 13, 5, IDUM1, IDUM2, INFO )
CALL PCHK1MAT( N, 4, N, 4, IZ, JZ, DESCZ, 26, 0, IDUM1, IDUM2,
$ INFO )
END IF
*
IWORK( 1 ) = LIWMIN
WORK( 1 ) = REAL( LWOPT )
*
IF( INFO.NE.0 ) THEN
CALL PXERBLA( ICTXT, 'PSSYGVX ', -INFO )
RETURN
ELSE IF( LQUERY ) THEN
RETURN
END IF
*
* Form a Cholesky factorization of sub( B ).
*
CALL PSPOTRF( UPLO, N, B, IB, JB, DESCB, INFO )
IF( INFO.NE.0 ) THEN
IWORK( 1 ) = LIWMIN
WORK( 1 ) = REAL( LWOPT )
IFAIL( 1 ) = INFO
INFO = IERRNPD
RETURN
END IF
*
* Transform problem to standard eigenvalue problem and solve.
*
CALL PSSYNGST( IBTYPE, UPLO, N, A, IA, JA, DESCA, B, IB, JB,
$ DESCB, SCALE, WORK, LWORK, INFO )
CALL PSSYEVX( JOBZ, RANGE, UPLO, N, A, IA, JA, DESCA, VL, VU, IL,
$ IU, ABSTOL, M, NZ, W, ORFAC, Z, IZ, JZ, DESCZ, WORK,
$ LWORK, IWORK, LIWORK, IFAIL, ICLUSTR, GAP, INFO )
*
IF( WANTZ ) THEN
*
* Backtransform eigenvectors to the original problem.
*
NEIG = M
IF( IBTYPE.EQ.1 .OR. IBTYPE.EQ.2 ) THEN
*
* For sub( A )*x=(lambda)*sub( B )*x and
* sub( A )*sub( B )*x=(lambda)*x; backtransform eigenvectors:
* x = inv(L)'*y or inv(U)*y
*
IF( UPPER ) THEN
TRANS = 'N'
ELSE
TRANS = 'T'
END IF
*
CALL PSTRSM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE,
$ B, IB, JB, DESCB, Z, IZ, JZ, DESCZ )
*
ELSE IF( IBTYPE.EQ.3 ) THEN
*
* For sub( B )*sub( A )*x=(lambda)*x;
* backtransform eigenvectors: x = L*y or U'*y
*
IF( UPPER ) THEN
TRANS = 'T'
ELSE
TRANS = 'N'
END IF
*
CALL PSTRMM( 'Left', UPLO, TRANS, 'Non-unit', N, NEIG, ONE,
$ B, IB, JB, DESCB, Z, IZ, JZ, DESCZ )
END IF
END IF
*
IF( SCALE.NE.ONE ) THEN
CALL SSCAL( N, SCALE, W, 1 )
END IF
*
IWORK( 1 ) = LIWMIN
WORK( 1 ) = REAL( LWOPT )
RETURN
*
* End of PSSYGVX
*
END