PZLACON(l)
π PZLACON π β LAPACK auxiliary routine (version 1.5)
okay so bestie, gather round, because this one is a whole vibe and also genuinely useful π«Ά. It lives in LAPACK, it's an auxiliary routine, and it is iconic.
πΈ NAME πΈ
PZLACON β estimate the 1-norm of a square, complex distributed matrix A. That's it, that's the whole job, and it does it beautifully. π
β¨ SYNOPSIS β¨
SUBROUTINE PZLACON( N, V, IV, JV, DESCV, X, IX, JX, DESCX, EST, KASE )
INTEGER IV, IX, JV, JX, KASE, N
DOUBLE PRECISION EST
INTEGER DESCV( * ), DESCX( * )
COMPLEX*16 V( * ), X( * )
look at her. she's literally perfect. π
π¦ PURPOSE π¦
PZLACON estimates the 1-norm of a square, complex distributed matrix A.
Reverse communication is used for evaluating matrix-vector products. X and V are aligned with the distributed matrix A, this information is implicitly contained within IV, IX, DESCV, and DESCX.
not me explaining reverse communication like it's a situationship: you keep handing control back and forth until somebody finally commits. 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".
so here's the whole lore drop, one entry per line because we do not do tables in this house π:
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 (the whole cast, no skips, no cuts)
Nβ (global input) INTEGER β The length of the distributed vectorsVandX.N >= 0.Vβ (local workspace)COMPLEX*16pointer into the local memory to an array of dimensionLOCr(N+MOD(IV-1,MB_V)). On the final return,V = A*W, whereEST = norm(V)/norm(W)(Wis not returned).IVβ (global input) INTEGER β The row index in the global arrayVindicating the first row ofsub( V ).JVβ (global input) INTEGER β The column index in the global arrayVindicating the first column ofsub( V ).DESCVβ (global and local input) INTEGER array of dimensionDLEN_. The array descriptor for the distributed matrixV.Xβ (local input/local output)COMPLEX*16pointer into the local memory to an array of dimensionLOCr(N+MOD(IX-1,MB_X)). On an intermediate return,Xshould be overwritten byA * X, ifKASE=1,A' * X, ifKASE=2, whereA'is the conjugate transpose ofA, andPZLACONmust be re-called with all the other parameters unchanged.IXβ (global input) INTEGER β The row index in the global arrayXindicating the first row ofsub( X ).JXβ (global input) INTEGER β The column index in the global arrayXindicating the first column ofsub( X ).DESCXβ (global and local input) INTEGER array of dimensionDLEN_. The array descriptor for the distributed matrixX.ESTβ (global output) DOUBLE PRECISION β An estimate (a lower bound) fornorm(A).KASEβ (local input/local output) INTEGER β On the initial call toPZLACON,KASEshould be0. On an intermediate return,KASEwill be1or2, indicating whetherXshould be overwritten byA * XorA' * X. On the final return fromPZLACON,KASEwill again be0.
bestie, theKASEloop is the whole plot.0β you're starting.1or2β she's handing it back to you and you owe her a matvec.0again β we're done, she's home, she's safe, she's EST. π₯
π FURTHER DETAILS π
The serial version ZLACON has been contributed by Nick Higham, University of Manchester. It was originally named SONEST, dated March 16, 1988.
Reference: N.J. Higham, "FORTRAN codes for estimating the one-norm of a real or complex matrix, with applications to condition estimation", ACM Trans. Math. Soft., vol. 14, no. 4, pp. 381-396, December 1988.
and that's the whole page, no cap. this was LAPACK version 1.5, dated 12 May 1997 β shoutout to the archive, shoutout to Nick Higham, and shoutout to you for reading all the way down here. you're the main character now. go estimate some norms. πβ¨ππ¦πΈπ π«Ά
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