LAPACK  3.9.0
LAPACK: Linear Algebra PACKage
cunhr_col.f
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1 *> \brief \b CUNHR_COL
2 *
3 * =========== DOCUMENTATION ===========
4 *
5 * Online html documentation available at
6 * http://www.netlib.org/lapack/explore-html/
7 *
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15 *> [TXT]</a>
16 *>
17 * Definition:
18 * ===========
19 *
20 * SUBROUTINE CUNHR_COL( M, N, NB, A, LDA, T, LDT, D, INFO )
21 *
22 * .. Scalar Arguments ..
23 * INTEGER INFO, LDA, LDT, M, N, NB
24 * ..
25 * .. Array Arguments ..
26 * COMPLEX A( LDA, * ), D( * ), T( LDT, * )
27 * ..
28 *
29 *> \par Purpose:
30 * =============
31 *>
32 *> \verbatim
33 *>
34 *> CUNHR_COL takes an M-by-N complex matrix Q_in with orthonormal columns
35 *> as input, stored in A, and performs Householder Reconstruction (HR),
36 *> i.e. reconstructs Householder vectors V(i) implicitly representing
37 *> another M-by-N matrix Q_out, with the property that Q_in = Q_out*S,
38 *> where S is an N-by-N diagonal matrix with diagonal entries
39 *> equal to +1 or -1. The Householder vectors (columns V(i) of V) are
40 *> stored in A on output, and the diagonal entries of S are stored in D.
41 *> Block reflectors are also returned in T
42 *> (same output format as CGEQRT).
43 *> \endverbatim
44 *
45 * Arguments:
46 * ==========
47 *
48 *> \param[in] M
49 *> \verbatim
50 *> M is INTEGER
51 *> The number of rows of the matrix A. M >= 0.
52 *> \endverbatim
53 *>
54 *> \param[in] N
55 *> \verbatim
56 *> N is INTEGER
57 *> The number of columns of the matrix A. M >= N >= 0.
58 *> \endverbatim
59 *>
60 *> \param[in] NB
61 *> \verbatim
62 *> NB is INTEGER
63 *> The column block size to be used in the reconstruction
64 *> of Householder column vector blocks in the array A and
65 *> corresponding block reflectors in the array T. NB >= 1.
66 *> (Note that if NB > N, then N is used instead of NB
67 *> as the column block size.)
68 *> \endverbatim
69 *>
70 *> \param[in,out] A
71 *> \verbatim
72 *> A is COMPLEX array, dimension (LDA,N)
73 *>
74 *> On entry:
75 *>
76 *> The array A contains an M-by-N orthonormal matrix Q_in,
77 *> i.e the columns of A are orthogonal unit vectors.
78 *>
79 *> On exit:
80 *>
81 *> The elements below the diagonal of A represent the unit
82 *> lower-trapezoidal matrix V of Householder column vectors
83 *> V(i). The unit diagonal entries of V are not stored
84 *> (same format as the output below the diagonal in A from
85 *> CGEQRT). The matrix T and the matrix V stored on output
86 *> in A implicitly define Q_out.
87 *>
88 *> The elements above the diagonal contain the factor U
89 *> of the "modified" LU-decomposition:
90 *> Q_in - ( S ) = V * U
91 *> ( 0 )
92 *> where 0 is a (M-N)-by-(M-N) zero matrix.
93 *> \endverbatim
94 *>
95 *> \param[in] LDA
96 *> \verbatim
97 *> LDA is INTEGER
98 *> The leading dimension of the array A. LDA >= max(1,M).
99 *> \endverbatim
100 *>
101 *> \param[out] T
102 *> \verbatim
103 *> T is COMPLEX array,
104 *> dimension (LDT, N)
105 *>
106 *> Let NOCB = Number_of_output_col_blocks
107 *> = CEIL(N/NB)
108 *>
109 *> On exit, T(1:NB, 1:N) contains NOCB upper-triangular
110 *> block reflectors used to define Q_out stored in compact
111 *> form as a sequence of upper-triangular NB-by-NB column
112 *> blocks (same format as the output T in CGEQRT).
113 *> The matrix T and the matrix V stored on output in A
114 *> implicitly define Q_out. NOTE: The lower triangles
115 *> below the upper-triangular blcoks will be filled with
116 *> zeros. See Further Details.
117 *> \endverbatim
118 *>
119 *> \param[in] LDT
120 *> \verbatim
121 *> LDT is INTEGER
122 *> The leading dimension of the array T.
123 *> LDT >= max(1,min(NB,N)).
124 *> \endverbatim
125 *>
126 *> \param[out] D
127 *> \verbatim
128 *> D is COMPLEX array, dimension min(M,N).
129 *> The elements can be only plus or minus one.
130 *>
131 *> D(i) is constructed as D(i) = -SIGN(Q_in_i(i,i)), where
132 *> 1 <= i <= min(M,N), and Q_in_i is Q_in after performing
133 *> i-1 steps of “modified” Gaussian elimination.
134 *> See Further Details.
135 *> \endverbatim
136 *>
137 *> \param[out] INFO
138 *> \verbatim
139 *> INFO is INTEGER
140 *> = 0: successful exit
141 *> < 0: if INFO = -i, the i-th argument had an illegal value
142 *> \endverbatim
143 *>
144 *> \par Further Details:
145 * =====================
146 *>
147 *> \verbatim
148 *>
149 *> The computed M-by-M unitary factor Q_out is defined implicitly as
150 *> a product of unitary matrices Q_out(i). Each Q_out(i) is stored in
151 *> the compact WY-representation format in the corresponding blocks of
152 *> matrices V (stored in A) and T.
153 *>
154 *> The M-by-N unit lower-trapezoidal matrix V stored in the M-by-N
155 *> matrix A contains the column vectors V(i) in NB-size column
156 *> blocks VB(j). For example, VB(1) contains the columns
157 *> V(1), V(2), ... V(NB). NOTE: The unit entries on
158 *> the diagonal of Y are not stored in A.
159 *>
160 *> The number of column blocks is
161 *>
162 *> NOCB = Number_of_output_col_blocks = CEIL(N/NB)
163 *>
164 *> where each block is of order NB except for the last block, which
165 *> is of order LAST_NB = N - (NOCB-1)*NB.
166 *>
167 *> For example, if M=6, N=5 and NB=2, the matrix V is
168 *>
169 *>
170 *> V = ( VB(1), VB(2), VB(3) ) =
171 *>
172 *> = ( 1 )
173 *> ( v21 1 )
174 *> ( v31 v32 1 )
175 *> ( v41 v42 v43 1 )
176 *> ( v51 v52 v53 v54 1 )
177 *> ( v61 v62 v63 v54 v65 )
178 *>
179 *>
180 *> For each of the column blocks VB(i), an upper-triangular block
181 *> reflector TB(i) is computed. These blocks are stored as
182 *> a sequence of upper-triangular column blocks in the NB-by-N
183 *> matrix T. The size of each TB(i) block is NB-by-NB, except
184 *> for the last block, whose size is LAST_NB-by-LAST_NB.
185 *>
186 *> For example, if M=6, N=5 and NB=2, the matrix T is
187 *>
188 *> T = ( TB(1), TB(2), TB(3) ) =
189 *>
190 *> = ( t11 t12 t13 t14 t15 )
191 *> ( t22 t24 )
192 *>
193 *>
194 *> The M-by-M factor Q_out is given as a product of NOCB
195 *> unitary M-by-M matrices Q_out(i).
196 *>
197 *> Q_out = Q_out(1) * Q_out(2) * ... * Q_out(NOCB),
198 *>
199 *> where each matrix Q_out(i) is given by the WY-representation
200 *> using corresponding blocks from the matrices V and T:
201 *>
202 *> Q_out(i) = I - VB(i) * TB(i) * (VB(i))**T,
203 *>
204 *> where I is the identity matrix. Here is the formula with matrix
205 *> dimensions:
206 *>
207 *> Q(i){M-by-M} = I{M-by-M} -
208 *> VB(i){M-by-INB} * TB(i){INB-by-INB} * (VB(i))**T {INB-by-M},
209 *>
210 *> where INB = NB, except for the last block NOCB
211 *> for which INB=LAST_NB.
212 *>
213 *> =====
214 *> NOTE:
215 *> =====
216 *>
217 *> If Q_in is the result of doing a QR factorization
218 *> B = Q_in * R_in, then:
219 *>
220 *> B = (Q_out*S) * R_in = Q_out * (S * R_in) = O_out * R_out.
221 *>
222 *> So if one wants to interpret Q_out as the result
223 *> of the QR factorization of B, then corresponding R_out
224 *> should be obtained by R_out = S * R_in, i.e. some rows of R_in
225 *> should be multiplied by -1.
226 *>
227 *> For the details of the algorithm, see [1].
228 *>
229 *> [1] "Reconstructing Householder vectors from tall-skinny QR",
230 *> G. Ballard, J. Demmel, L. Grigori, M. Jacquelin, H.D. Nguyen,
231 *> E. Solomonik, J. Parallel Distrib. Comput.,
232 *> vol. 85, pp. 3-31, 2015.
233 *> \endverbatim
234 *>
235 * Authors:
236 * ========
237 *
238 *> \author Univ. of Tennessee
239 *> \author Univ. of California Berkeley
240 *> \author Univ. of Colorado Denver
241 *> \author NAG Ltd.
242 *
243 *> \date November 2019
244 *
245 *> \ingroup complexOTHERcomputational
246 *
247 *> \par Contributors:
248 * ==================
249 *>
250 *> \verbatim
251 *>
252 *> November 2019, Igor Kozachenko,
253 *> Computer Science Division,
254 *> University of California, Berkeley
255 *>
256 *> \endverbatim
257 *
258 * =====================================================================
259  SUBROUTINE cunhr_col( M, N, NB, A, LDA, T, LDT, D, INFO )
260  IMPLICIT NONE
261 *
262 * -- LAPACK computational routine (version 3.9.0) --
263 * -- LAPACK is a software package provided by Univ. of Tennessee, --
264 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
265 * November 2019
266 *
267 * .. Scalar Arguments ..
268  INTEGER INFO, LDA, LDT, M, N, NB
269 * ..
270 * .. Array Arguments ..
271  COMPLEX A( LDA, * ), D( * ), T( LDT, * )
272 * ..
273 *
274 * =====================================================================
275 *
276 * .. Parameters ..
277  COMPLEX CONE, CZERO
278  parameter( cone = ( 1.0e+0, 0.0e+0 ),
279  $ czero = ( 0.0e+0, 0.0e+0 ) )
280 * ..
281 * .. Local Scalars ..
282  INTEGER I, IINFO, J, JB, JBTEMP1, JBTEMP2, JNB,
283  $ NPLUSONE
284 * ..
285 * .. External Subroutines ..
286  EXTERNAL ccopy, claunhr_col_getrfnp, cscal, ctrsm,
287  $ xerbla
288 * ..
289 * .. Intrinsic Functions ..
290  INTRINSIC max, min
291 * ..
292 * .. Executable Statements ..
293 *
294 * Test the input parameters
295 *
296  info = 0
297  IF( m.LT.0 ) THEN
298  info = -1
299  ELSE IF( n.LT.0 .OR. n.GT.m ) THEN
300  info = -2
301  ELSE IF( nb.LT.1 ) THEN
302  info = -3
303  ELSE IF( lda.LT.max( 1, m ) ) THEN
304  info = -5
305  ELSE IF( ldt.LT.max( 1, min( nb, n ) ) ) THEN
306  info = -7
307  END IF
308 *
309 * Handle error in the input parameters.
310 *
311  IF( info.NE.0 ) THEN
312  CALL xerbla( 'CUNHR_COL', -info )
313  RETURN
314  END IF
315 *
316 * Quick return if possible
317 *
318  IF( min( m, n ).EQ.0 ) THEN
319  RETURN
320  END IF
321 *
322 * On input, the M-by-N matrix A contains the unitary
323 * M-by-N matrix Q_in.
324 *
325 * (1) Compute the unit lower-trapezoidal V (ones on the diagonal
326 * are not stored) by performing the "modified" LU-decomposition.
327 *
328 * Q_in - ( S ) = V * U = ( V1 ) * U,
329 * ( 0 ) ( V2 )
330 *
331 * where 0 is an (M-N)-by-N zero matrix.
332 *
333 * (1-1) Factor V1 and U.
334 
335  CALL claunhr_col_getrfnp( n, n, a, lda, d, iinfo )
336 *
337 * (1-2) Solve for V2.
338 *
339  IF( m.GT.n ) THEN
340  CALL ctrsm( 'R', 'U', 'N', 'N', m-n, n, cone, a, lda,
341  $ a( n+1, 1 ), lda )
342  END IF
343 *
344 * (2) Reconstruct the block reflector T stored in T(1:NB, 1:N)
345 * as a sequence of upper-triangular blocks with NB-size column
346 * blocking.
347 *
348 * Loop over the column blocks of size NB of the array A(1:M,1:N)
349 * and the array T(1:NB,1:N), JB is the column index of a column
350 * block, JNB is the column block size at each step JB.
351 *
352  nplusone = n + 1
353  DO jb = 1, n, nb
354 *
355 * (2-0) Determine the column block size JNB.
356 *
357  jnb = min( nplusone-jb, nb )
358 *
359 * (2-1) Copy the upper-triangular part of the current JNB-by-JNB
360 * diagonal block U(JB) (of the N-by-N matrix U) stored
361 * in A(JB:JB+JNB-1,JB:JB+JNB-1) into the upper-triangular part
362 * of the current JNB-by-JNB block T(1:JNB,JB:JB+JNB-1)
363 * column-by-column, total JNB*(JNB+1)/2 elements.
364 *
365  jbtemp1 = jb - 1
366  DO j = jb, jb+jnb-1
367  CALL ccopy( j-jbtemp1, a( jb, j ), 1, t( 1, j ), 1 )
368  END DO
369 *
370 * (2-2) Perform on the upper-triangular part of the current
371 * JNB-by-JNB diagonal block U(JB) (of the N-by-N matrix U) stored
372 * in T(1:JNB,JB:JB+JNB-1) the following operation in place:
373 * (-1)*U(JB)*S(JB), i.e the result will be stored in the upper-
374 * triangular part of T(1:JNB,JB:JB+JNB-1). This multiplication
375 * of the JNB-by-JNB diagonal block U(JB) by the JNB-by-JNB
376 * diagonal block S(JB) of the N-by-N sign matrix S from the
377 * right means changing the sign of each J-th column of the block
378 * U(JB) according to the sign of the diagonal element of the block
379 * S(JB), i.e. S(J,J) that is stored in the array element D(J).
380 *
381  DO j = jb, jb+jnb-1
382  IF( d( j ).EQ.cone ) THEN
383  CALL cscal( j-jbtemp1, -cone, t( 1, j ), 1 )
384  END IF
385  END DO
386 *
387 * (2-3) Perform the triangular solve for the current block
388 * matrix X(JB):
389 *
390 * X(JB) * (A(JB)**T) = B(JB), where:
391 *
392 * A(JB)**T is a JNB-by-JNB unit upper-triangular
393 * coefficient block, and A(JB)=V1(JB), which
394 * is a JNB-by-JNB unit lower-triangular block
395 * stored in A(JB:JB+JNB-1,JB:JB+JNB-1).
396 * The N-by-N matrix V1 is the upper part
397 * of the M-by-N lower-trapezoidal matrix V
398 * stored in A(1:M,1:N);
399 *
400 * B(JB) is a JNB-by-JNB upper-triangular right-hand
401 * side block, B(JB) = (-1)*U(JB)*S(JB), and
402 * B(JB) is stored in T(1:JNB,JB:JB+JNB-1);
403 *
404 * X(JB) is a JNB-by-JNB upper-triangular solution
405 * block, X(JB) is the upper-triangular block
406 * reflector T(JB), and X(JB) is stored
407 * in T(1:JNB,JB:JB+JNB-1).
408 *
409 * In other words, we perform the triangular solve for the
410 * upper-triangular block T(JB):
411 *
412 * T(JB) * (V1(JB)**T) = (-1)*U(JB)*S(JB).
413 *
414 * Even though the blocks X(JB) and B(JB) are upper-
415 * triangular, the routine CTRSM will access all JNB**2
416 * elements of the square T(1:JNB,JB:JB+JNB-1). Therefore,
417 * we need to set to zero the elements of the block
418 * T(1:JNB,JB:JB+JNB-1) below the diagonal before the call
419 * to CTRSM.
420 *
421 * (2-3a) Set the elements to zero.
422 *
423  jbtemp2 = jb - 2
424  DO j = jb, jb+jnb-2
425  DO i = j-jbtemp2, nb
426  t( i, j ) = czero
427  END DO
428  END DO
429 *
430 * (2-3b) Perform the triangular solve.
431 *
432  CALL ctrsm( 'R', 'L', 'C', 'U', jnb, jnb, cone,
433  $ a( jb, jb ), lda, t( 1, jb ), ldt )
434 *
435  END DO
436 *
437  RETURN
438 *
439 * End of CUNHR_COL
440 *
441  END
claunhr_col_getrfnp
subroutine claunhr_col_getrfnp(M, N, A, LDA, D, INFO)
CLAUNHR_COL_GETRFNP
Definition: claunhr_col_getrfnp.f:148
ctrsm
subroutine ctrsm(SIDE, UPLO, TRANSA, DIAG, M, N, ALPHA, A, LDA, B, LDB)
CTRSM
Definition: ctrsm.f:182
cscal
subroutine cscal(N, CA, CX, INCX)
CSCAL
Definition: cscal.f:80
xerbla
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62
cunhr_col
subroutine cunhr_col(M, N, NB, A, LDA, T, LDT, D, INFO)
CUNHR_COL
Definition: cunhr_col.f:260
ccopy
subroutine ccopy(N, CX, INCX, CY, INCY)
CCOPY
Definition: ccopy.f:83