PSGELS(l)

📦 version 1.5, in ubuntu jammy

🦋 PSGELS(l) — bestie, we're solving linear systems 🦋

okay so this is the manpage for PSGELS, a LAPACK routine, version 1.5, and honestly? it's giving ✨math✨ but the parallel/distributed kind, so grab a boba and let's go 🧋💖

🌸 NAME 🌸

PSGELS — solve overdetermined or underdetermined real linear systems involving an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1), periodt 💅

🎀 SYNOPSIS 🎀

SUBROUTINE PSGELS( TRANS, M, N, NRHS, A, IA, JA, DESCA, B, IB, JB,
                   DESCB, WORK, LWORK, INFO )

    CHARACTER      TRANS

    INTEGER        IA, IB, INFO, JA, JB, LWORK, M, N, NRHS

    INTEGER        DESCA( * ), DESCB( * )

    REAL           A( * ), B( * ), WORK( * )

👑 PURPOSE 👑

PSGELS solves overdetermined or underdetermined real linear systems involving an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1), or its transpose, using a QR or LQ factorization of sub( A ). It is assumed that sub( A ) has full rank. (read that again bestie, FULL RANK, no cap)

The following options are provided:

If TRANS = 'N' and m >= n: find the least squares solution of an overdetermined system, i.e., solve the least squares problem

minimize || sub( B ) - sub( A )*X ||.

If TRANS = 'N' and m < n: find the minimum norm solution of an underdetermined system sub( A ) * X = sub( B ).
If TRANS = 'T' and m >= n: find the minimum norm solution of an undetermined system sub( A )**T * X = sub( B ).
If TRANS = 'T' and m < n: find the least squares solution of an overdetermined system, i.e., solve the least squares problem

minimize || sub( B ) - sub( A )**T * X ||.

where sub( B ) denotes B( IB:IB+M-1, JB:JB+NRHS-1 ) when TRANS = 'N' and B( IB:IB+N-1, JB:JB+NRHS-1 ) otherwise. Several right hand side vectors b and solution vectors x can be handled in a single call; When TRANS = 'N', the solution vectors are stored as the columns of the N-by-NRHS right hand side matrix sub( B ) and the M-by-NRHS right hand side matrix sub( B ) otherwise. 🫶 multiple rhs in one call? she's efficient, she's iconic, she's everything

📝 Notes 📝

mini lore drop before the main event:

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".

Here's the whole roster, bestie, every single one 🌈:

DTYPE_A (global) — stored in DESCA( DTYPE_ ) — The descriptor type. In this case, DTYPE_A = 1.
CTXT_A (global) — stored in DESCA( 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) — stored in DESCA( M_ ) — The number of rows in the global array A.
N_A (global) — stored in DESCA( N_ ) — The number of columns in the global array A.
MB_A (global) — stored in DESCA( MB_ ) — The blocking factor used to distribute the rows of the array.
NB_A (global) — stored in DESCA( NB_ ) — The blocking factor used to distribute the columns of the array.
RSRC_A (global) — stored in DESCA( RSRC_ ) — The process row over which the first row of the array A is distributed.
CSRC_A (global) — stored in DESCA( CSRC_ ) — The process column over which the first column of the array A is distributed.
LLD_A (local) — stored in DESCA( LLD_ ) — 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

✨ ARGUMENTS ✨

the main characters, one by one, no skips, we don't do skips here 💅

TRANS (global input) CHARACTER — = 'N': the linear system involves sub( A ); = 'T': the linear system involves sub( A )**T.
M (global input) INTEGER — The number of rows to be operated on, i.e. the number of rows of the distributed submatrix sub( A ). M >= 0.
N (global input) INTEGER — The number of columns to be operated on, i.e. the number of columns of the distributed submatrix sub( A ). N >= 0.
NRHS (global input) INTEGER — The number of right hand sides, i.e. the number of columns of the distributed submatrices sub( B ) and X. NRHS >= 0.
A (local input/local output) REAL pointer into the local memory to an array of local dimension ( LLD_A, LOCc(JA+N-1) ). On entry, the M-by-N matrix A. If M >= N, sub( A ) is overwritten by details of its QR factorization as returned by PSGEQRF; if M < N, sub( A ) is overwritten by details of its LQ factorization as returned by PSGELQF.
IA (global input) INTEGER — The row index in the global array A indicating the first row of sub( A ).
JA (global input) INTEGER — The column index in the global array A indicating the first column of sub( A ).
DESCA (global and local input) INTEGER array of dimension DLEN_. The array descriptor for the distributed matrix A.
B (local input/local output) REAL pointer into the local memory to an array of local dimension (LLD_B, LOCc(JB+NRHS-1)). On entry, this array contains the local pieces of the distributed matrix B of right hand side vectors, stored columnwise; sub( B ) is M-by-NRHS if TRANS='N', and N-by-NRHS otherwise. On exit, sub( B ) is overwritten by the solution vectors, stored columnwise: if TRANS = 'N' and M >= N, rows 1 to N of sub( B ) contain the least squares solution vectors; the residual sum of squares for the solution in each column is given by the sum of squares of elements N+1 to M in that column; if TRANS = 'N' and M < N, rows 1 to N of sub( B ) contain the minimum norm solution vectors; if TRANS = 'T' and M >= N, rows 1 to M of sub( B ) contain the minimum norm solution vectors; if TRANS = 'T' and M < N, rows 1 to M of sub( B ) contain the least squares solution vectors; the residual sum of squares for the solution in each column is given by the sum of squares of elements M+1 to N in that column. (yes that's four whole cases, she contains multitudes)
IB (global input) INTEGER — The row index in the global array B indicating the first row of sub( B ).
JB (global input) INTEGER — The column index in the global array B indicating the first column of sub( B ).
DESCB (global and local input) INTEGER array of dimension DLEN_. The array descriptor for the distributed matrix B.
WORK (local workspace/local output) REAL array, dimension (LWORK) — On exit, WORK(1) returns the minimal and optimal LWORK.
LWORK (local or global input) INTEGER — The dimension of the array WORK. LWORK is local input and must be at least

LWORK >= LTAU + MAX( LWF, LWS )

where if M >= N, then

LTAU = NUMROC( JA+MIN(M,N)-1, NB_A, MYCOL, CSRC_A, NPCOL ),
LWF  = NB_A * ( MpA0 + NqA0 + NB_A )
LWS  = MAX( (NB_A*(NB_A-1))/2, (NRHSqB0 + MpB0)*NB_A ) + NB_A * NB_A

Else

LTAU = NUMROC( IA+MIN(M,N)-1, MB_A, MYROW, RSRC_A, NPROW ),
LWF  = MB_A * ( MpA0 + NqA0 + MB_A )
LWS  = MAX( (MB_A*(MB_A-1))/2, ( NpB0 + MAX( NqA0 + NUMROC( NUMROC( N+IROFFB, MB_A, 0, 0, NPROW ), MB_A, 0, 0, LCMP ), NRHSqB0 ) )*MB_A ) + MB_A * MB_A

End if

where LCMP = LCM / NPROW with LCM = ILCM( NPROW, NPCOL ),

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 ), MpA0 = NUMROC( M+IROFFA, MB_A, MYROW, IAROW, NPROW ), NqA0 = NUMROC( N+ICOFFA, NB_A, MYCOL, IACOL, NPCOL ),

IROFFB = MOD( IB-1, MB_B ), ICOFFB = MOD( JB-1, NB_B ), IBROW = INDXG2P( IB, MB_B, MYROW, RSRC_B, NPROW ), IBCOL = INDXG2P( JB, NB_B, MYCOL, CSRC_B, NPCOL ), MpB0 = NUMROC( M+IROFFB, MB_B, MYROW, IBROW, NPROW ), NpB0 = NUMROC( N+IROFFB, MB_B, MYROW, IBROW, NPROW ), NRHSqB0 = NUMROC( NRHS+ICOFFB, NB_B, MYCOL, IBCOL, NPCOL ),

ILCM, INDXG2P and NUMROC are ScaLAPACK tool functions; MYROW, MYCOL, NPROW and NPCOL can be determined by calling the subroutine BLACS_GRIDINFO. (iykyk 🧚)

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. ✨ the little peek-behind-the-curtain trick ✨

INFO (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.

bestie please — check your LWORK, check your descriptors, check your INFO, because a negative INFO is not the vibe. 💀

and that's the whole thing, no crumbs left 🍓 This little love letter comes to you from LAPACK version 1.5, dated 12 May 1997 — so yes she's vintage, she's classic, she's the blueprint 👑✨ Go solve something iconic, bestie, and may your INFO always be 0 🫶💖🌸

📦 where this page comes from

ubuntu jammy: scalapack-doc 1.5-11
💖 girlified by deepseek-ai/DeepSeek-V4.1-Flash on 2026-10-14: a language model's rewrite of the original, under its terms