pssepqtq.f

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*
*
      SUBROUTINE pssepqtq( MS, NV, THRESH, Q, IQ, JQ, DESCQ, C, IC, JC,
     $                     DESCC, PROCDIST, ICLUSTR, GAP, WORK, LWORK,
     $                     QTQNRM, INFO, RES )
*
*  -- ScaLAPACK routine (version 1.7) --
*     University of Tennessee, Knoxville, Oak Ridge National Laboratory,
*     and University of California, Berkeley.
*     May 1, 1997
*
*     .. Scalar Arguments ..
      INTEGER            IC, INFO, IQ, JC, JQ, LWORK, MS, NV, RES
      REAL               QTQNRM, THRESH
*     ..
*     .. Array Arguments ..
*
      INTEGER            DESCC( * ), DESCQ( * ), ICLUSTR( * ),
     $                   PROCDIST( * )
      REAL               C( * ), GAP( * ), Q( * ), WORK( * )
*     ..
*
*  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
*
*  Purpose
*  =======
*
*  Compute |I - QT * Q| / (ulp * n)
*
*  Arguments
*  =========
*
*     NP = number of local rows in C
*     NQ = number of local columns in C and Q
*
*  MS      (global input) INTEGER
*          Matrix size.
*          The number of global rows in Q
*
*  NV      (global input) INTEGER
*          Number of eigenvectors
*          The number of global columns in C and Q
*
*  THRESH  (global input) REAL
*          A test will count as "failed" if the "error", computed as
*          described below, exceeds THRESH.  Note that the error
*          is scaled to be O(1), so THRESH should be a reasonably
*          small multiple of 1, e.g., 10 or 100.  In particular,
*          it should not depend on the precision (single vs. double)
*          or the size of the matrix.  It must be at least zero.
*
*  Q       (local input) REAL array,
*          global dimension (MS, NV), local dimension (LDQ, NQ)
*
*          Contains the eigenvectors as computed by PSSTEIN
*
*  IQ      (global input) INTEGER
*          Q's global row index, which points to the beginning of the
*          submatrix which is to be operated on.
*
*  JQ      (global input) INTEGER
*          Q's global column index, which points to the beginning of
*          the submatrix which is to be operated on.
*
*  DESCQ   (global and local input) INTEGER array of dimension DLEN_.
*          The array descriptor for the distributed matrix Q.
*
*  C       (local workspace)  REAL array,
*          global dimension (NV, NV), local dimension (DESCC(DLEN_), NQ)
*
*          Accumulator for computing I - QT * Q
*
*  IC      (global input) INTEGER
*          C's global row index, which points to the beginning of the
*          submatrix which is to be operated on.
*
*  JC      (global input) INTEGER
*          C's global column index, which points to the beginning of
*          the submatrix which is to be operated on.
*
*  DESCC   (global and local input) INTEGER array of dimension DLEN_.
*          The array descriptor for the distributed matrix C.
*
*  W       (input) REAL array, dimension (NV)
*          All procesors have an identical copy of W()
*
*          Contains the computed eigenvalues
*
*  PROCDIST (global input) INTEGER array dimension (NPROW*NPCOL+1)
*          Identifies which eigenvectors are the last to be computed
*          by a given process
*
*  ICLUSTR (global input) INTEGER array dimension (2*P)
*          This input array contains indices of eigenvectors
*          corresponding to a cluster of eigenvalues that could not be
*          orthogonalized due to insufficient workspace.
*          This should be the output of PSSTEIN.
*
*  GAP     (global input) REAL array, dimension (P)
*          This input array contains the gap between eigenvalues whose
*          eigenvectors could not be orthogonalized.
*
*  WORK    (local workspace) REAL array, dimension (LWORK)
*
*  LWORK   (local input) INTEGER
*          The length of the array WORK.
*          LWORK >= 2 + MAX( DESCC( MB_ ), 2 )*( 2*NP0+MQ0 )
*          Where:
*          NP0 = NUMROC( NV, DESCC( MB_ ), 0, 0, NPROW )
*          MQ0 = NUMROC( NV, DESCC( NB_ ), 0, 0, NPCOL )
*
*  QTQNRM  (global output) REAL
*          |QTQ -I| / EPS
*
*  RES     (global output) INTEGER
*          0 if the test passes i.e. |I - QT * Q| / (ulp * n) <= THRESH
*          1 if the test fails  i.e. |I - QT * Q| / (ulp * n) > THRESH
*
*
*     .. 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               ZERO, ONE, NEGONE
      PARAMETER          ( ZERO = 0.0e+0, one = 1.0e+0,
     $                   negone = -1.0e+0 )
*     ..
*     .. Intrinsic Functions ..
*
      INTRINSIC          max, real
*     ..
*     .. Local Scalars ..
      INTEGER            CLUSTER, FIRSTP, IMAX, IMIN, JMAX, JMIN, LWMIN,
     $                   MQ0, MYCOL, MYROW, NEXTP, NP0, NPCOL, NPROW
      REAL               NORM, QTQNRM2, ULP
*     ..
*     .. External Functions ..
      INTEGER            NUMROC
      REAL               PSLAMCH, PSLANGE
      EXTERNAL           numroc, pslamch, pslange
*     ..
*     .. External Subroutines ..
      EXTERNAL           blacs_gridinfo, chk1mat, psgemm, pslaset,
     $                   psmatadd, pxerbla
*     ..
*     .. Executable Statements ..
*       This is just to keep ftnchek happy
      IF( block_cyclic_2d*csrc_*ctxt_*dlen_*dtype_*lld_*mb_*m_*nb_*n_*
     $    rsrc_.LT.0 )RETURN
*
*
      res = 0
      ulp = pslamch( descc( ctxt_ ), 'P' )
*
      CALL blacs_gridinfo( descc( ctxt_ ), nprow, npcol, myrow, mycol )
      info = 0
      CALL chk1mat( ms, 1, ms, 2, iq, jq, descq, 7, info )
      CALL chk1mat( nv, 1, ms, 2, ic, jc, descc, 11, info )
*
      IF( info.EQ.0 ) THEN
         np0 = numroc( nv, descc( mb_ ), 0, 0, nprow )
         mq0 = numroc( nv, descc( nb_ ), 0, 0, npcol )
*
         lwmin = 2 + max( descc( mb_ ), 2 )*( 2*np0+mq0 )
*
         IF( iq.NE.1 ) THEN
            info = -5
         ELSE IF( jq.NE.1 ) THEN
            info = -6
         ELSE IF( ic.NE.1 ) THEN
            info = -9
         ELSE IF( jc.NE.1 ) THEN
            info = -10
         ELSE IF( lwork.LT.lwmin ) THEN
            info = -16
         END IF
      END IF
*
      IF( info.NE.0 ) THEN
         CALL pxerbla( descc( ctxt_ ), 'PSSEPQTQ', -info )
         RETURN
      END IF
*
*     C = Identity matrix
*
      CALL pslaset( 'A', nv, nv, zero, one, c, ic, jc, descc )
*
*     C = C - QT * Q
*
      IF( nv*ms.GT.0 ) THEN
         CALL psgemm( 'Transpose', 'N', nv, nv, ms, negone, q, 1, 1,
     $                descq, q, 1, 1, descq, one, c, 1, 1, descc )
      END IF
*
*     Allow for poorly orthogonalized eigenvectors for large clusters
*
      norm = pslange( '1', nv, nv, c, 1, 1, descc, work )
      qtqnrm = norm / ( real( max( ms, 1 ) )*ulp )
*
      cluster = 1
   10 CONTINUE
      DO 20 firstp = 1, nprow*npcol
         IF( procdist( firstp ).GE.iclustr( 2*( cluster-1 )+1 ) )
     $      GO TO 30
   20 CONTINUE
   30 CONTINUE
*
      imin = iclustr( 2*cluster-1 )
      jmax = iclustr( 2*cluster )
*
*
      IF( imin.EQ.0 )
     $   GO TO 60
*
      DO 40 nextp = firstp, nprow*npcol
         imax = procdist( nextp )
         jmin = imax + 1
*
*
         CALL psmatadd( imax-imin+1, jmax-jmin+1, zero, c, imin, jmin,
     $                  descc, gap( cluster ) / 0.01e+0, c, imin, jmin,
     $                  descc )
         CALL psmatadd( jmax-jmin+1, imax-imin+1, zero, c, jmin, imin,
     $                  descc, gap( cluster ) / 0.01e+0, c, jmin, imin,
     $                  descc )
         imin = imax
*
         IF( iclustr( 2*cluster ).LT.procdist( nextp+1 ) )
     $      GO TO 50
   40 CONTINUE
   50 CONTINUE
*
      cluster = cluster + 1
      GO TO 10
   60 CONTINUE
*
*     Compute the norm of C
*
      norm = pslange( '1', nv, nv, c, 1, 1, descc, work )
*
      qtqnrm2 = norm / ( real( max( ms, 1 ) )*ulp )
*
      IF( qtqnrm2.GT.thresh ) THEN
         res = 1
         qtqnrm = qtqnrm2
      END IF
      RETURN
*
*     End of PSSEPQTQ
*
      END