LAPACK 3.12.0
LAPACK: Linear Algebra PACKage
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◆ cunhr_col()

subroutine cunhr_col ( integer  m,
integer  n,
integer  nb,
complex, dimension( lda, * )  a,
integer  lda,
complex, dimension( ldt, * )  t,
integer  ldt,
complex, dimension( * )  d,
integer  info 
)

CUNHR_COL

Download CUNHR_COL + dependencies [TGZ] [ZIP] [TXT]

Purpose:
  CUNHR_COL takes an M-by-N complex matrix Q_in with orthonormal columns
  as input, stored in A, and performs Householder Reconstruction (HR),
  i.e. reconstructs Householder vectors V(i) implicitly representing
  another M-by-N matrix Q_out, with the property that Q_in = Q_out*S,
  where S is an N-by-N diagonal matrix with diagonal entries
  equal to +1 or -1. The Householder vectors (columns V(i) of V) are
  stored in A on output, and the diagonal entries of S are stored in D.
  Block reflectors are also returned in T
  (same output format as CGEQRT).
Parameters
[in]M
          M is INTEGER
          The number of rows of the matrix A. M >= 0.
[in]N
          N is INTEGER
          The number of columns of the matrix A. M >= N >= 0.
[in]NB
          NB is INTEGER
          The column block size to be used in the reconstruction
          of Householder column vector blocks in the array A and
          corresponding block reflectors in the array T. NB >= 1.
          (Note that if NB > N, then N is used instead of NB
          as the column block size.)
[in,out]A
          A is COMPLEX array, dimension (LDA,N)

          On entry:

             The array A contains an M-by-N orthonormal matrix Q_in,
             i.e the columns of A are orthogonal unit vectors.

          On exit:

             The elements below the diagonal of A represent the unit
             lower-trapezoidal matrix V of Householder column vectors
             V(i). The unit diagonal entries of V are not stored
             (same format as the output below the diagonal in A from
             CGEQRT). The matrix T and the matrix V stored on output
             in A implicitly define Q_out.

             The elements above the diagonal contain the factor U
             of the "modified" LU-decomposition:
                Q_in - ( S ) = V * U
                       ( 0 )
             where 0 is a (M-N)-by-(M-N) zero matrix.
[in]LDA
          LDA is INTEGER
          The leading dimension of the array A.  LDA >= max(1,M).
[out]T
          T is COMPLEX array,
          dimension (LDT, N)

          Let NOCB = Number_of_output_col_blocks
                   = CEIL(N/NB)

          On exit, T(1:NB, 1:N) contains NOCB upper-triangular
          block reflectors used to define Q_out stored in compact
          form as a sequence of upper-triangular NB-by-NB column
          blocks (same format as the output T in CGEQRT).
          The matrix T and the matrix V stored on output in A
          implicitly define Q_out. NOTE: The lower triangles
          below the upper-triangular blocks will be filled with
          zeros. See Further Details.
[in]LDT
          LDT is INTEGER
          The leading dimension of the array T.
          LDT >= max(1,min(NB,N)).
[out]D
          D is COMPLEX array, dimension min(M,N).
          The elements can be only plus or minus one.

          D(i) is constructed as D(i) = -SIGN(Q_in_i(i,i)), where
          1 <= i <= min(M,N), and Q_in_i is Q_in after performing
          i-1 steps of “modified” Gaussian elimination.
          See Further Details.
[out]INFO
          INFO is INTEGER
          = 0:  successful exit
          < 0:  if INFO = -i, the i-th argument had an illegal value
Further Details:
 The computed M-by-M unitary factor Q_out is defined implicitly as
 a product of unitary matrices Q_out(i). Each Q_out(i) is stored in
 the compact WY-representation format in the corresponding blocks of
 matrices V (stored in A) and T.

 The M-by-N unit lower-trapezoidal matrix V stored in the M-by-N
 matrix A contains the column vectors V(i) in NB-size column
 blocks VB(j). For example, VB(1) contains the columns
 V(1), V(2), ... V(NB). NOTE: The unit entries on
 the diagonal of Y are not stored in A.

 The number of column blocks is

     NOCB = Number_of_output_col_blocks = CEIL(N/NB)

 where each block is of order NB except for the last block, which
 is of order LAST_NB = N - (NOCB-1)*NB.

 For example, if M=6,  N=5 and NB=2, the matrix V is


     V = (    VB(1),   VB(2), VB(3) ) =

       = (   1                      )
         ( v21    1                 )
         ( v31  v32    1            )
         ( v41  v42  v43   1        )
         ( v51  v52  v53  v54    1  )
         ( v61  v62  v63  v54   v65 )


 For each of the column blocks VB(i), an upper-triangular block
 reflector TB(i) is computed. These blocks are stored as
 a sequence of upper-triangular column blocks in the NB-by-N
 matrix T. The size of each TB(i) block is NB-by-NB, except
 for the last block, whose size is LAST_NB-by-LAST_NB.

 For example, if M=6,  N=5 and NB=2, the matrix T is

     T  = (    TB(1),    TB(2), TB(3) ) =

        = ( t11  t12  t13  t14   t15  )
          (      t22       t24        )


 The M-by-M factor Q_out is given as a product of NOCB
 unitary M-by-M matrices Q_out(i).

     Q_out = Q_out(1) * Q_out(2) * ... * Q_out(NOCB),

 where each matrix Q_out(i) is given by the WY-representation
 using corresponding blocks from the matrices V and T:

     Q_out(i) = I - VB(i) * TB(i) * (VB(i))**T,

 where I is the identity matrix. Here is the formula with matrix
 dimensions:

  Q(i){M-by-M} = I{M-by-M} -
    VB(i){M-by-INB} * TB(i){INB-by-INB} * (VB(i))**T {INB-by-M},

 where INB = NB, except for the last block NOCB
 for which INB=LAST_NB.

 =====
 NOTE:
 =====

 If Q_in is the result of doing a QR factorization
 B = Q_in * R_in, then:

 B = (Q_out*S) * R_in = Q_out * (S * R_in) = Q_out * R_out.

 So if one wants to interpret Q_out as the result
 of the QR factorization of B, then the corresponding R_out
 should be equal to R_out = S * R_in, i.e. some rows of R_in
 should be multiplied by -1.

 For the details of the algorithm, see [1].

 [1] "Reconstructing Householder vectors from tall-skinny QR",
     G. Ballard, J. Demmel, L. Grigori, M. Jacquelin, H.D. Nguyen,
     E. Solomonik, J. Parallel Distrib. Comput.,
     vol. 85, pp. 3-31, 2015.
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Contributors:
 November   2019, Igor Kozachenko,
            Computer Science Division,
            University of California, Berkeley

Definition at line 258 of file cunhr_col.f.

259 IMPLICIT NONE
260*
261* -- LAPACK computational routine --
262* -- LAPACK is a software package provided by Univ. of Tennessee, --
263* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
264*
265* .. Scalar Arguments ..
266 INTEGER INFO, LDA, LDT, M, N, NB
267* ..
268* .. Array Arguments ..
269 COMPLEX A( LDA, * ), D( * ), T( LDT, * )
270* ..
271*
272* =====================================================================
273*
274* .. Parameters ..
275 COMPLEX CONE, CZERO
276 parameter( cone = ( 1.0e+0, 0.0e+0 ),
277 $ czero = ( 0.0e+0, 0.0e+0 ) )
278* ..
279* .. Local Scalars ..
280 INTEGER I, IINFO, J, JB, JBTEMP1, JBTEMP2, JNB,
281 $ NPLUSONE
282* ..
283* .. External Subroutines ..
285 $ xerbla
286* ..
287* .. Intrinsic Functions ..
288 INTRINSIC max, min
289* ..
290* .. Executable Statements ..
291*
292* Test the input parameters
293*
294 info = 0
295 IF( m.LT.0 ) THEN
296 info = -1
297 ELSE IF( n.LT.0 .OR. n.GT.m ) THEN
298 info = -2
299 ELSE IF( nb.LT.1 ) THEN
300 info = -3
301 ELSE IF( lda.LT.max( 1, m ) ) THEN
302 info = -5
303 ELSE IF( ldt.LT.max( 1, min( nb, n ) ) ) THEN
304 info = -7
305 END IF
306*
307* Handle error in the input parameters.
308*
309 IF( info.NE.0 ) THEN
310 CALL xerbla( 'CUNHR_COL', -info )
311 RETURN
312 END IF
313*
314* Quick return if possible
315*
316 IF( min( m, n ).EQ.0 ) THEN
317 RETURN
318 END IF
319*
320* On input, the M-by-N matrix A contains the unitary
321* M-by-N matrix Q_in.
322*
323* (1) Compute the unit lower-trapezoidal V (ones on the diagonal
324* are not stored) by performing the "modified" LU-decomposition.
325*
326* Q_in - ( S ) = V * U = ( V1 ) * U,
327* ( 0 ) ( V2 )
328*
329* where 0 is an (M-N)-by-N zero matrix.
330*
331* (1-1) Factor V1 and U.
332
333 CALL claunhr_col_getrfnp( n, n, a, lda, d, iinfo )
334*
335* (1-2) Solve for V2.
336*
337 IF( m.GT.n ) THEN
338 CALL ctrsm( 'R', 'U', 'N', 'N', m-n, n, cone, a, lda,
339 $ a( n+1, 1 ), lda )
340 END IF
341*
342* (2) Reconstruct the block reflector T stored in T(1:NB, 1:N)
343* as a sequence of upper-triangular blocks with NB-size column
344* blocking.
345*
346* Loop over the column blocks of size NB of the array A(1:M,1:N)
347* and the array T(1:NB,1:N), JB is the column index of a column
348* block, JNB is the column block size at each step JB.
349*
350 nplusone = n + 1
351 DO jb = 1, n, nb
352*
353* (2-0) Determine the column block size JNB.
354*
355 jnb = min( nplusone-jb, nb )
356*
357* (2-1) Copy the upper-triangular part of the current JNB-by-JNB
358* diagonal block U(JB) (of the N-by-N matrix U) stored
359* in A(JB:JB+JNB-1,JB:JB+JNB-1) into the upper-triangular part
360* of the current JNB-by-JNB block T(1:JNB,JB:JB+JNB-1)
361* column-by-column, total JNB*(JNB+1)/2 elements.
362*
363 jbtemp1 = jb - 1
364 DO j = jb, jb+jnb-1
365 CALL ccopy( j-jbtemp1, a( jb, j ), 1, t( 1, j ), 1 )
366 END DO
367*
368* (2-2) Perform on the upper-triangular part of the current
369* JNB-by-JNB diagonal block U(JB) (of the N-by-N matrix U) stored
370* in T(1:JNB,JB:JB+JNB-1) the following operation in place:
371* (-1)*U(JB)*S(JB), i.e the result will be stored in the upper-
372* triangular part of T(1:JNB,JB:JB+JNB-1). This multiplication
373* of the JNB-by-JNB diagonal block U(JB) by the JNB-by-JNB
374* diagonal block S(JB) of the N-by-N sign matrix S from the
375* right means changing the sign of each J-th column of the block
376* U(JB) according to the sign of the diagonal element of the block
377* S(JB), i.e. S(J,J) that is stored in the array element D(J).
378*
379 DO j = jb, jb+jnb-1
380 IF( d( j ).EQ.cone ) THEN
381 CALL cscal( j-jbtemp1, -cone, t( 1, j ), 1 )
382 END IF
383 END DO
384*
385* (2-3) Perform the triangular solve for the current block
386* matrix X(JB):
387*
388* X(JB) * (A(JB)**T) = B(JB), where:
389*
390* A(JB)**T is a JNB-by-JNB unit upper-triangular
391* coefficient block, and A(JB)=V1(JB), which
392* is a JNB-by-JNB unit lower-triangular block
393* stored in A(JB:JB+JNB-1,JB:JB+JNB-1).
394* The N-by-N matrix V1 is the upper part
395* of the M-by-N lower-trapezoidal matrix V
396* stored in A(1:M,1:N);
397*
398* B(JB) is a JNB-by-JNB upper-triangular right-hand
399* side block, B(JB) = (-1)*U(JB)*S(JB), and
400* B(JB) is stored in T(1:JNB,JB:JB+JNB-1);
401*
402* X(JB) is a JNB-by-JNB upper-triangular solution
403* block, X(JB) is the upper-triangular block
404* reflector T(JB), and X(JB) is stored
405* in T(1:JNB,JB:JB+JNB-1).
406*
407* In other words, we perform the triangular solve for the
408* upper-triangular block T(JB):
409*
410* T(JB) * (V1(JB)**T) = (-1)*U(JB)*S(JB).
411*
412* Even though the blocks X(JB) and B(JB) are upper-
413* triangular, the routine CTRSM will access all JNB**2
414* elements of the square T(1:JNB,JB:JB+JNB-1). Therefore,
415* we need to set to zero the elements of the block
416* T(1:JNB,JB:JB+JNB-1) below the diagonal before the call
417* to CTRSM.
418*
419* (2-3a) Set the elements to zero.
420*
421 jbtemp2 = jb - 2
422 DO j = jb, jb+jnb-2
423 DO i = j-jbtemp2, nb
424 t( i, j ) = czero
425 END DO
426 END DO
427*
428* (2-3b) Perform the triangular solve.
429*
430 CALL ctrsm( 'R', 'L', 'C', 'U', jnb, jnb, cone,
431 $ a( jb, jb ), lda, t( 1, jb ), ldt )
432*
433 END DO
434*
435 RETURN
436*
437* End of CUNHR_COL
438*
subroutine xerbla(srname, info)
Definition cblat2.f:3285
subroutine ccopy(n, cx, incx, cy, incy)
CCOPY
Definition ccopy.f:81
subroutine claunhr_col_getrfnp(m, n, a, lda, d, info)
CLAUNHR_COL_GETRFNP
subroutine cscal(n, ca, cx, incx)
CSCAL
Definition cscal.f:78
subroutine ctrsm(side, uplo, transa, diag, m, n, alpha, a, lda, b, ldb)
CTRSM
Definition ctrsm.f:180
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