PSLANGE(l)
π PSLANGE π
okay so bestie, you typed man PSLANGE and here we are β this is the manual page PSLANGE(l), a LAPACK auxiliary routine, version 1.5. she's a REAL FUNCTION and she's booked and busy. let's get into it π«Ά
β¨ NAME β¨
PSLANGE β return the value of the one norm, or the Frobenius norm,
(yeah the title line cuts off there, but don't worry, she spills the whole menu down in PURPOSE, keep reading π)
πΈ SYNOPSIS πΈ
REAL FUNCTION PSLANGE( NORM, M, N, A, IA, JA, DESCA, WORK )
CHARACTER NORM
INTEGER IA, JA, M, N
INTEGER DESCA( * )
REAL A( * ), WORK( * )
π PURPOSE π
ok so PSLANGE returns the value of the one norm, or the Frobenius norm, or the infinity norm, or the element of largest absolute value of a distributed matrix sub( A ) = A(IA:IA+M-1, JA:JA+N-1). she does it all, no cap π
Here's exactly what PSLANGE hands back, depending on NORM:
max(abs(A(i,j)))β whenNORM = 'M'or'm', withIA <= i <= IA+M-1, andJA <= j <= JA+N-1norm1( sub( A ) )β whenNORM = '1','O'or'o'normI( sub( A ) )β whenNORM = 'I'or'i'normF( sub( A ) )β whenNORM = 'F','f','E'or'e'
where norm1 denotes the one norm of a matrix (maximum column sum), normI denotes the infinity norm of a matrix (maximum row sum) and normF denotes the Frobenius norm of a matrix (square root of sum of squares).
not me having to say this but: note that max(abs(A(i,j))) is not a matrix norm. she's a vibe, not a norm, iykyk π
π§ Notes π§
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 whole notation situation, laid out for you bestie:
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 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_ )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
NORMβ (global input)CHARACTER. Specifies the value to be returned inPSLANGEas described above. she's the vibe selector β¨Mβ (global input)INTEGER. The number of rows to be operated on i.e the number of rows of the distributed submatrixsub( A ). WhenM = 0,PSLANGEis set to zero.M >= 0.Nβ (global input)INTEGER. The number of columns to be operated on i.e the number of columns of the distributed submatrixsub( A ). WhenN = 0,PSLANGEis set to zero.N >= 0.Aβ (local input)REALpointer into the local memory to an array of dimension(LLD_A, LOCc(JA+N-1))containing the local pieces of the distributed matrixsub( A ).IAβ (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.WORKβ (local workspace)REALarray dimension(LWORK).
ok so for WORK, listen closely bestie:
LWORK >= 0 if NORM = 'M' or 'm' (not referenced), Nq0 if NORM = '1', 'O' or 'o', Mp0 if NORM = 'I' or 'i', 0 if NORM = 'F', 'f', 'E' or 'e' (not referenced), where
IROFFA = MOD( IA-1, MB_A ), ICOFFA = MOD( JA-1, NB_A ), IAROW =
INDXG2P( IA, MB_A, MYROW, RSRC_A, NPROW ), IACOL = INDXG2P( JA,
NB_A, MYCOL, CSRC_A, NPCOL ), Mp0 = NUMROC( M+IROFFA, MB_A,
MYROW, IAROW, NPROW ), Nq0 = NUMROC( N+ICOFFA, NB_A, MYCOL,
IACOL, NPCOL ),
INDXG2P and NUMROC are ScaLAPACK tool functions; MYROW, MYCOL, NPROW and NPCOL can be determined by calling the subroutine BLACS_GRIDINFO.
and that's the whole page, bestie π she's PSLANGE(l) from LAPACK version 1.5, dated 12 May 1997, and honestly? iconic behavior. go forth and compute your norms, you absolute main character πβ¨πΈ
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