PSSYTD2(l)
π PSSYTD2 π
okay bestie, buckle up, because this is PSSYTD2, a LAPACK auxiliary routine (we're living in version 1.5 era, vintage queen π), and she's here to take a real symmetric matrix and β¨ reduce it β¨ into symmetric tridiagonal form. iconic behavior, honestly.
πΈ NAME πΈ
PSSYTD2 β she reduces a real symmetric matrix sub( A ) to symmetric tridiagonal form T by an orthogonal similarity transformation. that's the whole vibe. π¦
β¨ SYNOPSIS β¨
SUBROUTINE PSSYTD2( UPLO, N, A, IA, JA, DESCA, D, E, TAU, WORK, LWORK,
INFO )
CHARACTER UPLO
INTEGER IA, INFO, JA, LWORK, N
INTEGER DESCA( * )
REAL A( * ), D( * ), E( * ), TAU( * ), WORK( * )
look at all those arguments, she's high maintenance but she delivers π
π PURPOSE π
PSSYTD2 reduces a real symmetric matrix sub( A ) to symmetric tridiagonal form T by an orthogonal similarity transformation:
Q' * sub( A ) * Q = T
where sub( A ) = A(IA:IA+N-1,JA:JA+N-1). slay. π
π Notes π
okay so here's the lore you need, bestie β every global data object is described by an associated description vector. this vector stores all the info you need to map an object element to its corresponding process and memory location. it's giving address book energy. πΊοΈ
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 comments below, the character _ should be read as "of the global array". iykyk.
DTYPE_A(global) β stored inDESCA( DTYPE_ ). the descriptor type. in this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ ). the BLACS context handle, indicating the BLACS process grid A is distributed over. the context itself is global, but the handle (the integer value) may vary.M_A(global) β stored inDESCA( M_ ). the number of rows in the global arrayA.N_A(global) β stored inDESCA( N_ ). the number of columns in the global arrayA.MB_A(global) β stored inDESCA( MB_ ). the blocking factor used to distribute the rows of the array.NB_A(global) β stored inDESCA( NB_ ). the blocking factor used to distribute the columns of the array.RSRC_A(global) β stored inDESCA( RSRC_ ). the process row over which the first row of the arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ ). the process column over which the first column of the arrayAis distributed.LLD_A(local) β stored inDESCA( LLD_ ). the leading dimension of the local array.LLD_A >= MAX(1,LOCr(M_A)).
now let K be the number of rows or columns of a distributed matrix, and assume 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. π«
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
UPLOβ (global input)CHARACTER. specifies whether the upper or lower triangular part of the symmetric matrixsub( A )is stored:= 'U': upper triangular= 'L': lower triangular
Nβ (global input)INTEGER. the number of rows and columns to be operated on, i.e. the order of the distributed submatrixsub( A ).N >= 0.Aβ (local input/local output)REALpointer 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 leadingN-by-Nupper triangular part ofsub( A )contains the upper triangular part of the matrix, and its strictly lower triangular part is not referenced. ifUPLO = 'L', the leadingN-by-Nlower 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. πIAβ (global input)INTEGER. the row index in the global arrayAindicating the first row ofsub( A ).JAβ (global input)INTEGER. the column index in the global arrayAindicating the first column ofsub( A ).DESCAβ (global and local input)INTEGERarray of dimensionDLEN_. the array descriptor for the distributed matrixA.Dβ (local output)REALarray, dimensionLOCc(JA+N-1). the diagonal elements of the tridiagonal matrixT:D(i) = A(i,i).Dis tied to the distributed matrixA. π«ΆEβ (local output)REALarray, dimensionLOCc(JA+N-1)ifUPLO = 'U',LOCc(JA+N-2)otherwise. 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.TAUβ (local output)REAL, array, dimensionLOCc(JA+N-1). this array contains the scalar factorsTAUof the elementary reflectors.TAUis tied to the distributed matrixA.WORKβ (local workspace/local output)REALarray, dimension(LWORK). on exit,WORK( 1 )returns the minimal and optimalLWORK.LWORKβ (local or global input)INTEGER. 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. sneaky but valid, bestie. π
INFOβ (local output)INTEGER.= 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). so pretty, so structured, main character matrix energy honestly. π
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 )
ICOFFA = MOD( JA-1, NB_A )
β οΈ bestie this is not optional. if the alignment doesn't check out, we have a problem. no cap.
and that's the whole page, fr fr. this one's from LAPACK version 1.5, dated 12 May 1997 β yes she's an elder icon and she still ate π π periodt. take care of your descriptors and she'll take care of you 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