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
H44 H33 H43H34 (global input) DOUBLE PRECISION These three values are for the double shift QR iteration.
Logic: ======
Two consecutive small subdiagonal elements will stall convergence of a double shift if their product is small relatively even if each is not very small. Thus it is necessary to scan the "tridiagonal portion of the matrix." In the LAPACK algorithm DLAHQR, a loop of M goes from I-2 down to L and examines H(m,m),H(m+1,m+1),H(m+1,m),H(m,m+1),H(m-1,m-1),H(m,m-1), and H(m+2,m-1). Since these elements may be on separate processors, the first major loop (10) goes over the tridiagonal and has each node store whatever values of the 7 it has that the node owning H(m,m) does not. This will occur on a border and can happen in no more than 3 locations per block assuming square blocks. There are 5 buffers that each node stores these values: a buffer to send diagonally down and right, a buffer to send up, a buffer to send left, a buffer to send diagonally up and left and a buffer to send right. Each of these buffers is actually stored in one buffer BUF where BUF(ISTR1+1) starts the first buffer, BUF(ISTR2+1) starts the second, etc.. After the values are stored, if there are any values that a node needs, they will be sent and received. Then the next major loop passes over the data and searches for two consecutive small subdiagonals.
Notes:
This routine does a global maximum and must be called by all processes.
Implemented by: G. Henry, November 17, 1996