PSCSUM1(l)

πŸ“¦ version 1.5, in ubuntu jammy

πŸ’– NAME πŸ’–

PSCSUM1 β€” okay so bestie, this one returns the sum of absolute values of a complex distributed vector sub( X ) in ASUM, ✨


πŸ“œ SYNOPSIS πŸ“œ

SUBROUTINE PSCSUM1( N, ASUM, X, IX, JX, DESCX, INCX )

    INTEGER         IX, INCX, JX, N

    REAL            ASUM

    INTEGER         DESCX( * )

    COMPLEX         X( * )

🎯 PURPOSE 🎯

PSCSUM1 returns the sum of absolute values of a complex distributed vector sub( X ) in ASUM, πŸ’…

where sub( X ) denotes

X(IX:IX+N-1,JX:JX), if INCX = 1,
X(IX:IX,JX:JX+N-1), if INCX = M_X.

ngl, this is based on PSCASUM from the Level 1 PBLAS. The change is that it uses the 'genuine' absolute value. 🫢

The serial version of this routine was originally contributed by Nick Higham for use with CLACON. iconic tbh πŸ‘‘


πŸ“ Notes πŸ“

fr fr, 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".

The notation, lowkey laid out like a vibe check for your descriptor:

  • 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.
  • 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

Because vectors may be viewed as a subclass of matrices, a distributed vector is considered to be a distributed matrix. yes bestie, it's giving "vectors are just skinny matrices" πŸ¦‹

When the result of a vector-oriented PBLAS call is a scalar, it will be made available only within the scope which owns the vector(s) being operated on. Let X be a generic term for the input vector(s). Then, the processes which receive the answer will be (note that if an operation involves more than one vector, the processes which receive the result will be the union of the following calculation for each vector):

  • If N = 1, M_X = 1 and INCX = 1, then one can't determine if a process row or process column owns the vector operand, therefore only the process of coordinate {RSRC_X, CSRC_X} receives the result;
  • If INCX = M_X, then sub( X ) is a vector distributed over a process row. Each process part of this row receives the result;
  • If INCX = 1, then sub( X ) is a vector distributed over a process column. Each process part of this column receives the result;

✨ PARAMETERS ✨

  • N β€” (global input) pointer to INTEGER. The number of components of the distributed vector sub( X ). N >= 0. πŸ“
  • ASUM β€” (local output) pointer to REAL. The sum of absolute values of the distributed vector sub( X ) only in its scope. πŸŽ€
  • X β€” (local input) COMPLEX array containing the local pieces of a distributed matrix of dimension of at least ( (JX-1)*M_X + IX + ( N - 1 )*abs( INCX ) ) This array contains the entries of the distributed vector sub( X ). πŸ‘‘
  • IX β€” (global input) pointer to INTEGER. The global row index of the submatrix of the distributed matrix X to operate on. 🌈
  • JX β€” (global input) pointer to INTEGER. The global column index of the submatrix of the distributed matrix X to operate on. 🌈
  • DESCX β€” (global and local input) INTEGER array of dimension 8. The array descriptor of the distributed matrix X. πŸ’œ
  • INCX β€” (global input) pointer to INTEGER. The global increment for the elements of X. Only two values of INCX are supported in this version, namely 1 and M_X. πŸ”₯
heads up bestie: INCX is lowkey picky β€” it's 1 or M_X and literally nothing else in this version. don't try to be creative. πŸ’€

LAPACK version 1.5 Β· 12 May 1997 β€” that's the tea, the whole manual page, no cap πŸ’–βœ¨πŸŽ€ slay responsibly, and remember: only the scope that owns the vector gets the answer, periodt πŸ«ΆπŸ¦‹πŸŒΈ

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