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NAME

       PDLASSQ  - return the values scl and smsq such that   ( scl**2 )*smsq =
       x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,

SYNOPSIS

       SUBROUTINE PDLASSQ( N, X, IX, JX, DESCX, INCX, SCALE, SUMSQ )

           INTEGER         IX, INCX, JX, N

           DOUBLE          PRECISION SCALE, SUMSQ

           INTEGER         DESCX( * )

           DOUBLE          PRECISION X( * )

PURPOSE

       PDLASSQ  returns the values  scl  and  smsq  such that

       where  x( i ) = sub( X ) = X(  IX+(JX-1)*DESCX(M_)+(i-1)*INCX  ).   The
       value of sumsq is assumed to be non-negative and scl returns the value

          scl = max( scale, abs( x( i ) ) ).

       scale  and  sumsq  must  be  supplied  in SCALE and SUMSQ respectively.
       SCALE and SUMSQ are overwritten by scl and ssq respectively.

       The routine makes only one pass through the vector sub( X ).

       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

       Because  vectors may be viewed as a subclass of matrices, a distributed
       vector is considered to be a distributed matrix.

       The result are only available in the scope of sub( X ), i.e if sub( X )
       is  distributed  along  a  process  row,  the  correct results are only
       available in this process row of the grid. Similarly if  sub(  X  )  is
       distributed  along  a  process  column,  the  correct  results are only
       available in this process column of the grid.

ARGUMENTS

       N       (global input) INTEGER
               The length of the distributed vector sub( X ).

       X       (input) DOUBLE PRECISION
               The vector for which a scaled sum of squares is computed.  x( i
               )  = X(IX+(JX-1)*M_X +(i-1)*INCX ), 1 <= i <= n.

       IX      (global input) INTEGER
               The row index in the global array X indicating the first row of
               sub( X ).

       JX      (global input) INTEGER
               The column index in the global array  X  indicating  the  first
               column of sub( X ).

       DESCX   (global and local input) INTEGER array of dimension DLEN_.
               The array descriptor for the distributed matrix X.

       INCX    (global input) INTEGER
               The  global increment for the elements of X. Only two values of
               INCX are supported in this version, namely  1  and  M_X.   INCX
               must not be zero.

       SCALE   (local input/local output) DOUBLE PRECISION
               On  entry,  the  value  scale  in the equation above.  On exit,
               SCALE is overwritten with  scl , the scaling factor for the sum
               of squares.

       SUMSQ   (local input/local output) DOUBLE PRECISION
               On  entry,  the  value  sumsq  in the equation above.  On exit,
               SUMSQ is overwritten with  smsq , the basic sum of squares from
               which  scl  has been factored out.