LAPACK  3.9.0
LAPACK: Linear Algebra PACKage

◆ sgelqt3()

recursive subroutine sgelqt3 ( integer  M,
integer  N,
real, dimension( lda, * )  A,
integer  LDA,
real, dimension( ldt, * )  T,
integer  LDT,
integer  INFO 
)

SGELQT3

Purpose:
 DGELQT3 recursively computes a LQ factorization of a real M-by-N
 matrix A, using the compact WY representation of Q.

 Based on the algorithm of Elmroth and Gustavson,
 IBM J. Res. Develop. Vol 44 No. 4 July 2000.
Parameters
[in]M
          M is INTEGER
          The number of rows of the matrix A.  M =< N.
[in]N
          N is INTEGER
          The number of columns of the matrix A.  N >= 0.
[in,out]A
          A is REAL array, dimension (LDA,N)
          On entry, the real M-by-N matrix A.  On exit, the elements on and
          below the diagonal contain the N-by-N lower triangular matrix L; the
          elements above the diagonal are the rows of V.  See below for
          further details.
[in]LDA
          LDA is INTEGER
          The leading dimension of the array A.  LDA >= max(1,M).
[out]T
          T is REAL array, dimension (LDT,N)
          The N-by-N upper triangular factor of the block reflector.
          The elements on and above the diagonal contain the block
          reflector T; the elements below the diagonal are not used.
          See below for further details.
[in]LDT
          LDT is INTEGER
          The leading dimension of the array T.  LDT >= max(1,N).
[out]INFO
          INFO is INTEGER
          = 0: successful exit
          < 0: if INFO = -i, the i-th argument had an illegal value
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date
November 2017
Further Details:
  The matrix V stores the elementary reflectors H(i) in the i-th row
  above the diagonal. For example, if M=5 and N=3, the matrix V is

               V = (  1  v1 v1 v1 v1 )
                   (     1  v2 v2 v2 )
                   (     1  v3 v3 v3 )


  where the vi's represent the vectors which define H(i), which are returned
  in the matrix A.  The 1's along the diagonal of V are not stored in A.  The
  block reflector H is then given by

               H = I - V * T * V**T

  where V**T is the transpose of V.

  For details of the algorithm, see Elmroth and Gustavson (cited above).

Definition at line 118 of file sgelqt3.f.

118 *
119 * -- LAPACK computational routine (version 3.8.0) --
120 * -- LAPACK is a software package provided by Univ. of Tennessee, --
121 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
122 * November 2017
123 *
124 * .. Scalar Arguments ..
125  INTEGER INFO, LDA, M, N, LDT
126 * ..
127 * .. Array Arguments ..
128  REAL A( LDA, * ), T( LDT, * )
129 * ..
130 *
131 * =====================================================================
132 *
133 * .. Parameters ..
134  REAL ONE
135  parameter( one = 1.0e+00 )
136 * ..
137 * .. Local Scalars ..
138  INTEGER I, I1, J, J1, M1, M2, IINFO
139 * ..
140 * .. External Subroutines ..
141  EXTERNAL slarfg, strmm, sgemm, xerbla
142 * ..
143 * .. Executable Statements ..
144 *
145  info = 0
146  IF( m .LT. 0 ) THEN
147  info = -1
148  ELSE IF( n .LT. m ) THEN
149  info = -2
150  ELSE IF( lda .LT. max( 1, m ) ) THEN
151  info = -4
152  ELSE IF( ldt .LT. max( 1, m ) ) THEN
153  info = -6
154  END IF
155  IF( info.NE.0 ) THEN
156  CALL xerbla( 'SGELQT3', -info )
157  RETURN
158  END IF
159 *
160  IF( m.EQ.1 ) THEN
161 *
162 * Compute Householder transform when N=1
163 *
164  CALL slarfg( n, a, a( 1, min( 2, n ) ), lda, t )
165 *
166  ELSE
167 *
168 * Otherwise, split A into blocks...
169 *
170  m1 = m/2
171  m2 = m-m1
172  i1 = min( m1+1, m )
173  j1 = min( m+1, n )
174 *
175 * Compute A(1:M1,1:N) <- (Y1,R1,T1), where Q1 = I - Y1 T1 Y1^H
176 *
177  CALL sgelqt3( m1, n, a, lda, t, ldt, iinfo )
178 *
179 * Compute A(J1:M,1:N) = Q1^H A(J1:M,1:N) [workspace: T(1:N1,J1:N)]
180 *
181  DO i=1,m2
182  DO j=1,m1
183  t( i+m1, j ) = a( i+m1, j )
184  END DO
185  END DO
186  CALL strmm( 'R', 'U', 'T', 'U', m2, m1, one,
187  & a, lda, t( i1, 1 ), ldt )
188 *
189  CALL sgemm( 'N', 'T', m2, m1, n-m1, one, a( i1, i1 ), lda,
190  & a( 1, i1 ), lda, one, t( i1, 1 ), ldt)
191 *
192  CALL strmm( 'R', 'U', 'N', 'N', m2, m1, one,
193  & t, ldt, t( i1, 1 ), ldt )
194 *
195  CALL sgemm( 'N', 'N', m2, n-m1, m1, -one, t( i1, 1 ), ldt,
196  & a( 1, i1 ), lda, one, a( i1, i1 ), lda )
197 *
198  CALL strmm( 'R', 'U', 'N', 'U', m2, m1 , one,
199  & a, lda, t( i1, 1 ), ldt )
200 *
201  DO i=1,m2
202  DO j=1,m1
203  a( i+m1, j ) = a( i+m1, j ) - t( i+m1, j )
204  t( i+m1, j )=0
205  END DO
206  END DO
207 *
208 * Compute A(J1:M,J1:N) <- (Y2,R2,T2) where Q2 = I - Y2 T2 Y2^H
209 *
210  CALL sgelqt3( m2, n-m1, a( i1, i1 ), lda,
211  & t( i1, i1 ), ldt, iinfo )
212 *
213 * Compute T3 = T(J1:N1,1:N) = -T1 Y1^H Y2 T2
214 *
215  DO i=1,m2
216  DO j=1,m1
217  t( j, i+m1 ) = (a( j, i+m1 ))
218  END DO
219  END DO
220 *
221  CALL strmm( 'R', 'U', 'T', 'U', m1, m2, one,
222  & a( i1, i1 ), lda, t( 1, i1 ), ldt )
223 *
224  CALL sgemm( 'N', 'T', m1, m2, n-m, one, a( 1, j1 ), lda,
225  & a( i1, j1 ), lda, one, t( 1, i1 ), ldt )
226 *
227  CALL strmm( 'L', 'U', 'N', 'N', m1, m2, -one, t, ldt,
228  & t( 1, i1 ), ldt )
229 *
230  CALL strmm( 'R', 'U', 'N', 'N', m1, m2, one,
231  & t( i1, i1 ), ldt, t( 1, i1 ), ldt )
232 *
233 *
234 *
235 * Y = (Y1,Y2); L = [ L1 0 ]; T = [T1 T3]
236 * [ A(1:N1,J1:N) L2 ] [ 0 T2]
237 *
238  END IF
239 *
240  RETURN
241 *
242 * End of SGELQT3
243 *
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strmm
subroutine strmm(SIDE, UPLO, TRANSA, DIAG, M, N, ALPHA, A, LDA, B, LDB)
STRMM
Definition: strmm.f:179
sgelqt3
recursive subroutine sgelqt3(M, N, A, LDA, T, LDT, INFO)
SGELQT3
Definition: sgelqt3.f:118
sgemm
subroutine sgemm(TRANSA, TRANSB, M, N, K, ALPHA, A, LDA, B, LDB, BETA, C, LDC)
SGEMM
Definition: sgemm.f:189
slarfg
subroutine slarfg(N, ALPHA, X, INCX, TAU)
SLARFG generates an elementary reflector (Householder matrix).
Definition: slarfg.f:108
xerbla
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62