PDSYTD2(l)
π PDSYTD2 π
okay bestie, gather round, because we're doing PDSYTD2 from the LAPACK auxiliary routine crew (version 1.5, she's vintage, she's iconic) π
β¨ NAME β¨
PDSYTD2 β reduce a real symmetric matrix sub( A ) to symmetric tridiagonal form T by an orthogonal similarity transformation π
πΈ SYNOPSIS πΈ
SUBROUTINE PDSYTD2( UPLO, N, A, IA, JA, DESCA, D, E, TAU, WORK, LWORK,
INFO )
CHARACTER UPLO
INTEGER IA, INFO, JA, LWORK, N
INTEGER DESCA( * )
DOUBLE PRECISION A( * ), D( * ), E( * ), TAU( * ), WORK( *
)
π¦ PURPOSE π¦
So what she does: PDSYTD2 reduces a real symmetric matrix sub( A ) to symmetric tridiagonal form T by an orthogonal similarity transformation, and the whole glow-up is:
Q' * sub( A ) * Q = T
where sub( A ) = A(IA:IA+N-1,JA:JA+N-1). literally transforming, no cap π₯
π Notes π
okay this part is the lore. read it. iykyk.
Every 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. π«Ά
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". π
Here's the notation tea, spelled out:
DTYPE_A(global) β stored inDESCA( DTYPE_ )β the descriptor type. In this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ )β the BLACS context handle, indicating the BLACS process gridAis distributed over. The context itself is global, but the handle (the integer value) may vary.M_A(global) β stored inDESCA( M_ )β the number of rows in the global arrayA.N_A(global) β stored inDESCA( N_ )β the number of columns in the global arrayA.MB_A(global) β stored inDESCA( MB_ )β the blocking factor used to distribute the rows of the array.NB_A(global) β stored inDESCA( NB_ )β the blocking factor used to distribute the columns of the array.RSRC_A(global) β stored inDESCA( RSRC_ )β the process row over which the first row of the arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β the process column over which the first column of the arrayAis distributed.LLD_A(local) β stored inDESCA( LLD_ )β 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
π ARGUMENTS π
UPLO(global input) CHARACTER β specifies whether the upper or lower triangular part of the symmetric matrixsub( A )is stored:= 'U': Upper triangular= 'L': Lower triangular
N(global input) INTEGER β the number of rows and columns to be operated on, i.e. the order of the distributed submatrixsub( A ).N >= 0. πA(local input/local output) DOUBLE PRECISION 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 symmetric distributed matrixsub( A ). IfUPLO = 'U', the leading N-by-N upper triangular part ofsub( A )contains the upper triangular part of the matrix, and its strictly lower triangular part is not referenced. IfUPLO = 'L', the leading N-by-N lower triangular part ofsub( A )contains the lower triangular part of the matrix, and its strictly upper triangular part is not referenced. On exit, ifUPLO = 'U', the diagonal and first superdiagonal ofsub( A )are overwritten by the corresponding elements of the tridiagonal matrixT, and the elements above the first superdiagonal, with the arrayTAU, represent the orthogonal matrixQas a product of elementary reflectors; ifUPLO = 'L', the diagonal and first subdiagonal ofsub( A )are overwritten by the corresponding elements of the tridiagonal matrixT, and the elements below the first subdiagonal, with the arrayTAU, represent the orthogonal matrixQas a product of elementary reflectors. See Further Details. πIA(global input) INTEGER β the row index in the global arrayAindicating the first row ofsub( A ).JA(global input) INTEGER β the column index in the global arrayAindicating the first column ofsub( A ).DESCA(global and local input) INTEGER array of dimensionDLEN_β the array descriptor for the distributed matrixA.D(local output) DOUBLE PRECISION array, dimensionLOCc(JA+N-1)β the diagonal elements of the tridiagonal matrixT:D(i) = A(i,i).Dis tied to the distributed matrixA.E(local output) DOUBLE PRECISION array, dimensionLOCc(JA+N-1)ifUPLO = 'U',LOCc(JA+N-2)otherwise β the off-diagonal elements of the tridiagonal matrixT:E(i) = A(i,i+1)ifUPLO = 'U',E(i) = A(i+1,i)ifUPLO = 'L'.Eis tied to the distributed matrixA.TAU(local output) DOUBLE PRECISION, array, dimensionLOCc(JA+N-1)β this array contains the scalar factorsTAUof the elementary reflectors.TAUis tied to the distributed matrixA.WORK(local workspace/local output) DOUBLE PRECISION array, dimension(LWORK)β on exit,WORK( 1 )returns the minimal and optimalLWORK. β¨LWORK(local or global input) INTEGER β the dimension of the arrayWORK.LWORKis local input and must be at leastLWORK >= 3*N.
If LWORK = -1, then LWORK 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. π«’
INFO(local output) INTEGER β= 0: successful exit π< 0: If the i-th argument is an array and the j-entry had an illegal value, thenINFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, thenINFO = -i.
π FURTHER DETAILS π
If UPLO = 'U', the matrix Q is represented as a product of elementary reflectors
Q = H(n-1) . . . H(2) H(1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in A(ia:ia+i-2,ja+i), and tau in TAU(ja+i-1).
If UPLO = 'L', the matrix Q is represented as a product of elementary reflectors
Q = H(1) H(2) . . . H(n-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(ia+i+1:ia+n-1,ja+i-1), and tau in TAU(ja+i-1).
The contents of sub( A ) on exit are illustrated by the following examples with n = 5:
if UPLO = 'U': if UPLO = 'L':
( d e v2 v3 v4 ) ( d )
( d e v3 v4 ) ( e d )
( d e v4 ) ( v1 e d )
( d e ) ( v1 v2 e d )
( d ) ( v1 v2 v3 e d )
where d and e denote diagonal and off-diagonal elements of T, and vi denotes an element of the vector defining H(i).
π§ Alignment requirements π§
The distributed submatrix sub( A ) must verify some alignment properties, namely the following expression should be true:
( MB_A.EQ.NB_A .AND. IROFFA.EQ.ICOFFA )
with
IROFFA = MOD( IA-1, MB_A )
and
ICOFFA = MOD( JA-1, NB_A ).
β οΈ bestie if that alignment check isn't giving what it needs to give, that's a whole situation.MB_A.EQ.NB_AANDIROFFA.EQ.ICOFFA. both. periodt. π
and that's the whole page!! π she's LAPACK version 1.5, dated 12 May 1997, and she's still serving tridiagonal realness to this day. mwah, love u, go reduce something symmetric πβ¨π¦
π¦ where this page comes from
- ubuntu jammy: scalapack-doc 1.5-11
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms