PCHEGVX(3)    ScaLAPACK routine of NEC Numeric Library Collection   PCHEGVX(3)



NAME
       PCHEGVX  computes all the eigenvalues, and optionally, the eigenvectors
       of a complex generalized Hermitian-definite eigenproblem.

SYNOPSIS
       SUBROUTINE PCHEGVX( 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, RWORK,
                           LRWORK, IWORK, LIWORK, IFAIL, ICLUSTR, GAP, INFO )

           CHARACTER       JOBZ, RANGE, UPLO

           INTEGER         IA, IB, IBTYPE, IL,  INFO,  IU,  IZ,  JA,  JB,  JZ,
                           LIWORK, LRWORK, LWORK, M, N, NZ

           REAL            ABSTOL, ORFAC, VL, VU

           INTEGER         DESCA(  *  ), DESCB( * ), DESCZ( * ), ICLUSTR( * ),
                           IFAIL( * ), IWORK( * )

           REAL            GAP( * ), RWORK( * ), W( * )

           COMPLEX*8 A( * ), B( * ), WORK( * ), Z( * )

PURPOSE
       PCHEGVX computes all the eigenvalues, and optionally, the  eigenvectors
       of  a  complex generalized Hermitian-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 Hermitian positive definite.

       Notes
       =====

       Each  global data object is described by an associated description vec-
       tor.  This vector stores the information required to establish the map-
       ping 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  col-
       umn.
       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) COMPLEX*8 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
               Hermitian distributed matrix sub( A ). If UPLO = 'U', the lead-
               ing 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  tri-
               angular 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**H*sub( B )*Z = I;
               if IBTYPE = 3, Z**H*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, PCHEGVX cannot  guarantee  correct  error
               reporting.

       B       (local input/local output) COMPLEX*8 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
               Hermitian distributed matrix sub( B ). If UPLO = 'U', the lead-
               ing 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 tri-
               angular part of the matrix.

               On exit, if INFO <= N, the part of sub( B )  containing  thema-
               trix  is  overwritten  by the triangular factor U or L from the
               Cholesky factorization sub( B ) = U**H*U or sub( B ) =  L*L**H.

       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 approxi-
               mate 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 num-
               ber 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 PCHEGVX 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.)  PCHEGVX is always able to  detect  insuffi-
               cient space without computation unless RANGE .EQ. 'V'.

       W       (global output) REAL array, dimension (N)
               On normal exit, the first M entries contain the selected eigen-
               values 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.
               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  correspond-
               ing  to  the  selected eigenvalues.  If an eigenvector fails to
               converge, then that column of Z contains the latest  approxima-
               tion  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) COMPLEX*8 array,
                  dimension(LWORK) WORK(1) returns the optimal workspace.

       LWORK   (local input) INTEGER
               Size of WORK array.  If only eigenvalues are requested:
                 LWORK >= N + MAX( NB * ( NP0 + 1 ), 3 )
               If eigenvectors are requested:
                 LWORK  >=  N + ( NP0 + MQ0 + NB ) * NB with NQ0 = NUMROC( NN,
               NB, 0, 0, NPCOL ).

               For optimal performance, greater workspace is needed, i.e.
                 LWORK >= MAX( LWORK, N + NHETRD_LWOPT,
                   NHEGST_LWOPT )
               Where LWORK is as defined above, and
                 NHETRD_LWORK = 2*( ANB+1 )*( 4*NPS+2 ) +
                   ( NPS + 1 ) * NPS
                 NHEGST_LWOPT =  2*NP0*NB + NQ0*NB + NB*NB

                 NB = DESCA( MB_ )
                 NP0 = NUMROC( N, NB, 0, 0, NPROW )
                 NQ0 = NUMROC( N, NB, 0, 0, NPCOL )
                 ICTXT = DESCA( CTXT_ )
                 ANB = PJLAENV( ICTXT, 3, 'PCHETTRD', 'L', 0, 0, 0, 0 )
                 SQNPC = SQRT( DBLE( NPROW * NPCOL ) )
                 NPS = MAX( NUMROC( N, 1, 0, 0, SQNPC ), 2*ANB )

                 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.

               If LWORK = -1, then LWORK is global input and a workspace query
               is  assumed;  the  routine only calculates the optimal size for
               all work arrays. Each of these values is returned in the  first
               entry  of  the correspondingwork array, and no error message is
               issued by PXERBLA.

       RWORK   (local workspace/output) REAL array,
                  dimension max(3,LRWORK)
               On return, RWORK(1) contains the amount of workspace
                  required for optimal efficiency
               if JOBZ='N' RWORK(1) = optimal amount of workspace
                  required to compute eigenvalues efficiently
               if JOBZ='V' RWORK(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 when computing optimal workspace.

       LRWORK  (local input) INTEGER
               Size of RWORK See below for definitions of  variables  used  to
               define  LRWORK.   If no eigenvectors are requested (JOBZ = 'N')
               then
                  LRWORK >= 5 * NN + 4 * N If eigenvectors are requested (JOBZ
               = 'V' ) then
                  the amount of workspace required to guarantee that all
                  eigenvectors are computed is:
                  LRWORK >= 4*N + MAX( 5*NN, NP0 * MQ0 ) +
                    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 LRWORK:
                     (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 LRWORK is too small:
                  If LRWORK is too small to guarantee orthogonality,
                  PCHEGVX attempts to maintain orthogonality in
                  the clusters with the smallest
                  spacing between the eigenvalues.
                  If LRWORK is too small to compute all the eigenvectors
                  requested, no computation is performed and INFO=-25
                  is returned.  Note that when RANGE='V', PCHEGVX does
                  not know how many eigenvectors are requested until
                  the eigenvalues are computed.  Therefore, when RANGE='V'
                  and as long as LRWORK is large enough to allow PCHEGVX to
                  compute the eigenvalues, PCHEGVX will compute the
                  eigenvalues and as many eigenvectors as it can.

               Relationship between workspace, orthogonality & performance:
                  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)
                  PCSTEIN will perform no better than CSTEIN 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  LRWORK  =  -1,  then LRWORK 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.


       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
               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 eigenvec-
               tors 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 cor-
               respoding  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
                       PCHEGVX 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 PCSTEBZ 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



ScaLAPACK routine               31 October 2017                     PCHEGVX(3)