PZPOTRI(l)

πŸ“¦ version 1.5, in ubuntu jammy

πŸ¦‹ PZPOTRI πŸ¦‹

okay bestie, welcome to PZPOTRI(l), a LAPACK routine from version 1.5, and she is so specific and we love her for it πŸ’–


✨ NAME ✨

PZPOTRI β€” compute the inverse of a complex Hermitian positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**H*U or L*L**H computed by PZPOTRF πŸ’…


🌸 SYNOPSIS 🌸

SUBROUTINE PZPOTRI( UPLO, N, A, IA, JA, DESCA, INFO )

    CHARACTER       UPLO

    INTEGER         IA, INFO, JA, N

    INTEGER         DESCA( * )

    COMPLEX*16      A( * )

πŸ‘‘ PURPOSE πŸ‘‘

PZPOTRI computes the inverse of a complex Hermitian positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**H*U or L*L**H computed by PZPOTRF. like, it takes your factor and hands you back the inverse, no big deal, only it IS a big deal 🫢

πŸ’œ Notes πŸ’œ

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".

so here's the whole notation tea, NOTATION β†’ STORED IN β†’ EXPLANATION, bestie:

  • DTYPE_A (global) β†’ stored in DESCA( DTYPE_ ) β€” the descriptor type. In this case, DTYPE_A = 1.
  • CTXT_A (global) β†’ stored in DESCA( CTXT_ ) β€” 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. it's giving "the vibe is shared but the pointer isn't" 😭
  • M_A (global) β†’ stored in DESCA( M_ ) β€” the number of rows in the global array A.
  • N_A (global) β†’ stored in DESCA( N_ ) β€” the number of columns in the global array A.
  • MB_A (global) β†’ stored in DESCA( MB_ ) β€” the blocking factor used to distribute the rows of the array.
  • NB_A (global) β†’ stored in DESCA( NB_ ) β€” the blocking factor used to distribute the columns of the array.
  • RSRC_A (global) β†’ stored in DESCA( RSRC_ ) β€” the process row over which the first row of the array A is distributed.
  • CSRC_A (global) β†’ stored in DESCA( CSRC_ ) β€” the process column over which the first column of the array A is distributed.
  • LLD_A (local) β†’ stored in DESCA( 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

πŸŽ€ ARGUMENTS πŸŽ€

  • UPLO β€” (global input) CHARACTER*1
    • = 'U': Upper triangle of sub( A ) is stored;
    • = 'L': Lower triangle of sub( A ) is stored.
  • N β€” (global input) INTEGER The number of rows and columns to be operated on, i.e. the order of the distributed submatrix sub( A ). N >= 0. (yes the nonnegativity is mandatory, she's strict πŸ’…)
  • A β€” (local input/local output) COMPLEX*16 pointer into the local memory to an array of dimension (LLD_A, LOCc(JA+N-1)). On entry, the local pieces of the triangular factor U or L from the Cholesky factorization of the distributed matrix sub( A ) = U**H*U or L*L**H, as computed by PZPOTRF. On exit, the local pieces of the upper or lower triangle of the (Hermitian) inverse of sub( A ), overwriting the input factor U or L. πŸ‘‘ so like, she takes your factor, and gives you back the inverse in the same spot β€” the input is GONE, no takebacks, she ate and left no crumbs.
  • IA β€” (global input) INTEGER The row index in the global array A indicating the first row of sub( A ).
  • JA β€” (global input) INTEGER The column index in the global array A indicating the first column of sub( A ).
  • DESCA β€” (global and local input) INTEGER array of dimension DLEN_. The array descriptor for the distributed matrix A. it's literally the whole map, don't lose it πŸ—ΊοΈ
  • INFO β€” (global output) INTEGER
    • = 0: successful exit ✨
    • < 0: If the i-th argument is an array and the j-entry had an illegal value, then INFO = -(i*100+j), if the i-th argument is a scalar and had an illegal value, then INFO = -i.
    • > 0: If INFO = i, the (i,i) element of the factor U or L is zero, and the inverse could not be computed. πŸ’€ no inverse for you, the factor said "not today"
lowkey important: a positive INFO means the (i,i) element of U or L is zero, and the inverse could not be computed. that's not a vibe, that's a real answer from the routine, so check it fr fr πŸ™ˆ

and that's the whole page bestie, go invert something Hermitian and positive definite, you absolute icon 🧚

this has been PZPOTRI(l) from LAPACK version 1.5, dated 12 May 1997 β€” mwah, slay, periodt πŸ’–βœ¨πŸŽ€

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