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| launhr_col_getrfnp2(3) | LAPACK | launhr_col_getrfnp2(3) |
NAME¶
launhr_col_getrfnp2 - la{un,or}hr_col_getrfnp2: LU factor without pivoting, level 2
SYNOPSIS¶
Functions¶
recursive subroutine claunhr_col_getrfnp2 (m, n, a, lda, d,
info)
CLAUNHR_COL_GETRFNP2 recursive subroutine dlaorhr_col_getrfnp2
(m, n, a, lda, d, info)
DLAORHR_COL_GETRFNP2 recursive subroutine slaorhr_col_getrfnp2
(m, n, a, lda, d, info)
SLAORHR_COL_GETRFNP2 recursive subroutine zlaunhr_col_getrfnp2
(m, n, a, lda, d, info)
ZLAUNHR_COL_GETRFNP2
Detailed Description¶
Function Documentation¶
recursive subroutine claunhr_col_getrfnp2 (integer m, integer n, complex, dimension( lda, * ) a, integer lda, complex, dimension( * ) d, integer info)¶
CLAUNHR_COL_GETRFNP2
Purpose:
CLAUNHR_COL_GETRFNP2 computes the modified LU factorization without
pivoting of a complex general M-by-N matrix A. The factorization has
the form:
A - S = L * U,
where:
S is a m-by-n diagonal sign matrix with the diagonal D, so that
D(i) = S(i,i), 1 <= i <= min(M,N). The diagonal D is constructed
as D(i)=-SIGN(A(i,i)), where A(i,i) is the value after performing
i-1 steps of Gaussian elimination. This means that the diagonal
element at each step of 'modified' Gaussian elimination is at
least one in absolute value (so that division-by-zero not
possible during the division by the diagonal element);
L is a M-by-N lower triangular matrix with unit diagonal elements
(lower trapezoidal if M > N);
and U is a M-by-N upper triangular matrix
(upper trapezoidal if M < N).
This routine is an auxiliary routine used in the Householder
reconstruction routine CUNHR_COL. In CUNHR_COL, this routine is
applied to an M-by-N matrix A with orthonormal columns, where each
element is bounded by one in absolute value. With the choice of
the matrix S above, one can show that the diagonal element at each
step of Gaussian elimination is the largest (in absolute value) in
the column on or below the diagonal, so that no pivoting is required
for numerical stability [1].
For more details on the Householder reconstruction algorithm,
including the modified LU factorization, see [1].
This is the recursive version of the LU factorization algorithm.
Denote A - S by B. The algorithm divides the matrix B into four
submatrices:
[ B11 | B12 ] where B11 is n1 by n1,
B = [ -----|----- ] B21 is (m-n1) by n1,
[ B21 | B22 ] B12 is n1 by n2,
B22 is (m-n1) by n2,
with n1 = min(m,n)/2, n2 = n-n1.
The subroutine calls itself to factor B11, solves for B21,
solves for B12, updates B22, then calls itself to factor B22.
For more details on the recursive LU algorithm, see [2].
CLAUNHR_COL_GETRFNP2 is called to factorize a block by the blocked
routine CLAUNHR_COL_GETRFNP, which uses blocked code calling
Level 3 BLAS to update the submatrix. However, CLAUNHR_COL_GETRFNP2
is self-sufficient and can be used without CLAUNHR_COL_GETRFNP.
[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.
[2] 'Recursion leads to automatic variable blocking for dense linear
algebra algorithms', F. Gustavson, IBM J. of Res. and Dev.,
vol. 41, no. 6, pp. 737-755, 1997.
Parameters
M
M is INTEGER
The number of rows of the matrix A. M >= 0.
N
N is INTEGER
The number of columns of the matrix A. N >= 0.
A
A is COMPLEX array, dimension (LDA,N)
On entry, the M-by-N matrix to be factored.
On exit, the factors L and U from the factorization
A-S=L*U; the unit diagonal elements of L are not stored.
LDA
LDA is INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D
D is COMPLEX array, dimension min(M,N)
The diagonal elements of the diagonal M-by-N sign matrix S,
D(i) = S(i,i), where 1 <= i <= min(M,N). The elements can be
only ( +1.0, 0.0 ) or (-1.0, 0.0 ).
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.
Contributors:
November 2019, Igor Kozachenko,
Computer Science Division,
University of California, Berkeley
recursive subroutine dlaorhr_col_getrfnp2 (integer m, integer n, double precision, dimension( lda, * ) a, integer lda, double precision, dimension( * ) d, integer info)¶
DLAORHR_COL_GETRFNP2
Purpose:
DLAORHR_COL_GETRFNP2 computes the modified LU factorization without
pivoting of a real general M-by-N matrix A. The factorization has
the form:
A - S = L * U,
where:
S is a m-by-n diagonal sign matrix with the diagonal D, so that
D(i) = S(i,i), 1 <= i <= min(M,N). The diagonal D is constructed
as D(i)=-SIGN(A(i,i)), where A(i,i) is the value after performing
i-1 steps of Gaussian elimination. This means that the diagonal
element at each step of 'modified' Gaussian elimination is at
least one in absolute value (so that division-by-zero not
possible during the division by the diagonal element);
L is a M-by-N lower triangular matrix with unit diagonal elements
(lower trapezoidal if M > N);
and U is a M-by-N upper triangular matrix
(upper trapezoidal if M < N).
This routine is an auxiliary routine used in the Householder
reconstruction routine DORHR_COL. In DORHR_COL, this routine is
applied to an M-by-N matrix A with orthonormal columns, where each
element is bounded by one in absolute value. With the choice of
the matrix S above, one can show that the diagonal element at each
step of Gaussian elimination is the largest (in absolute value) in
the column on or below the diagonal, so that no pivoting is required
for numerical stability [1].
For more details on the Householder reconstruction algorithm,
including the modified LU factorization, see [1].
This is the recursive version of the LU factorization algorithm.
Denote A - S by B. The algorithm divides the matrix B into four
submatrices:
[ B11 | B12 ] where B11 is n1 by n1,
B = [ -----|----- ] B21 is (m-n1) by n1,
[ B21 | B22 ] B12 is n1 by n2,
B22 is (m-n1) by n2,
with n1 = min(m,n)/2, n2 = n-n1.
The subroutine calls itself to factor B11, solves for B21,
solves for B12, updates B22, then calls itself to factor B22.
For more details on the recursive LU algorithm, see [2].
DLAORHR_COL_GETRFNP2 is called to factorize a block by the blocked
routine DLAORHR_COL_GETRFNP, which uses blocked code calling
Level 3 BLAS to update the submatrix. However, DLAORHR_COL_GETRFNP2
is self-sufficient and can be used without DLAORHR_COL_GETRFNP.
[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.
[2] 'Recursion leads to automatic variable blocking for dense linear
algebra algorithms', F. Gustavson, IBM J. of Res. and Dev.,
vol. 41, no. 6, pp. 737-755, 1997.
Parameters
M
M is INTEGER
The number of rows of the matrix A. M >= 0.
N
N is INTEGER
The number of columns of the matrix A. N >= 0.
A
A is DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix to be factored.
On exit, the factors L and U from the factorization
A-S=L*U; the unit diagonal elements of L are not stored.
LDA
LDA is INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D
D is DOUBLE PRECISION array, dimension min(M,N)
The diagonal elements of the diagonal M-by-N sign matrix S,
D(i) = S(i,i), where 1 <= i <= min(M,N). The elements can
be only plus or minus one.
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.
Contributors:
November 2019, Igor Kozachenko,
Computer Science Division,
University of California, Berkeley
recursive subroutine slaorhr_col_getrfnp2 (integer m, integer n, real, dimension( lda, * ) a, integer lda, real, dimension( * ) d, integer info)¶
SLAORHR_COL_GETRFNP2
Purpose:
SLAORHR_COL_GETRFNP2 computes the modified LU factorization without
pivoting of a real general M-by-N matrix A. The factorization has
the form:
A - S = L * U,
where:
S is a m-by-n diagonal sign matrix with the diagonal D, so that
D(i) = S(i,i), 1 <= i <= min(M,N). The diagonal D is constructed
as D(i)=-SIGN(A(i,i)), where A(i,i) is the value after performing
i-1 steps of Gaussian elimination. This means that the diagonal
element at each step of 'modified' Gaussian elimination is at
least one in absolute value (so that division-by-zero not
possible during the division by the diagonal element);
L is a M-by-N lower triangular matrix with unit diagonal elements
(lower trapezoidal if M > N);
and U is a M-by-N upper triangular matrix
(upper trapezoidal if M < N).
This routine is an auxiliary routine used in the Householder
reconstruction routine SORHR_COL. In SORHR_COL, this routine is
applied to an M-by-N matrix A with orthonormal columns, where each
element is bounded by one in absolute value. With the choice of
the matrix S above, one can show that the diagonal element at each
step of Gaussian elimination is the largest (in absolute value) in
the column on or below the diagonal, so that no pivoting is required
for numerical stability [1].
For more details on the Householder reconstruction algorithm,
including the modified LU factorization, see [1].
This is the recursive version of the LU factorization algorithm.
Denote A - S by B. The algorithm divides the matrix B into four
submatrices:
[ B11 | B12 ] where B11 is n1 by n1,
B = [ -----|----- ] B21 is (m-n1) by n1,
[ B21 | B22 ] B12 is n1 by n2,
B22 is (m-n1) by n2,
with n1 = min(m,n)/2, n2 = n-n1.
The subroutine calls itself to factor B11, solves for B21,
solves for B12, updates B22, then calls itself to factor B22.
For more details on the recursive LU algorithm, see [2].
SLAORHR_COL_GETRFNP2 is called to factorize a block by the blocked
routine SLAORHR_COL_GETRFNP, which uses blocked code calling
Level 3 BLAS to update the submatrix. However, SLAORHR_COL_GETRFNP2
is self-sufficient and can be used without SLAORHR_COL_GETRFNP.
[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.
[2] 'Recursion leads to automatic variable blocking for dense linear
algebra algorithms', F. Gustavson, IBM J. of Res. and Dev.,
vol. 41, no. 6, pp. 737-755, 1997.
Parameters
M
M is INTEGER
The number of rows of the matrix A. M >= 0.
N
N is INTEGER
The number of columns of the matrix A. N >= 0.
A
A is REAL array, dimension (LDA,N)
On entry, the M-by-N matrix to be factored.
On exit, the factors L and U from the factorization
A-S=L*U; the unit diagonal elements of L are not stored.
LDA
LDA is INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D
D is REAL array, dimension min(M,N)
The diagonal elements of the diagonal M-by-N sign matrix S,
D(i) = S(i,i), where 1 <= i <= min(M,N). The elements can
be only plus or minus one.
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.
Contributors:
November 2019, Igor Kozachenko,
Computer Science Division,
University of California, Berkeley
recursive subroutine zlaunhr_col_getrfnp2 (integer m, integer n, complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension( * ) d, integer info)¶
ZLAUNHR_COL_GETRFNP2
Purpose:
ZLAUNHR_COL_GETRFNP2 computes the modified LU factorization without
pivoting of a complex general M-by-N matrix A. The factorization has
the form:
A - S = L * U,
where:
S is a m-by-n diagonal sign matrix with the diagonal D, so that
D(i) = S(i,i), 1 <= i <= min(M,N). The diagonal D is constructed
as D(i)=-SIGN(A(i,i)), where A(i,i) is the value after performing
i-1 steps of Gaussian elimination. This means that the diagonal
element at each step of 'modified' Gaussian elimination is at
least one in absolute value (so that division-by-zero not
possible during the division by the diagonal element);
L is a M-by-N lower triangular matrix with unit diagonal elements
(lower trapezoidal if M > N);
and U is a M-by-N upper triangular matrix
(upper trapezoidal if M < N).
This routine is an auxiliary routine used in the Householder
reconstruction routine ZUNHR_COL. In ZUNHR_COL, this routine is
applied to an M-by-N matrix A with orthonormal columns, where each
element is bounded by one in absolute value. With the choice of
the matrix S above, one can show that the diagonal element at each
step of Gaussian elimination is the largest (in absolute value) in
the column on or below the diagonal, so that no pivoting is required
for numerical stability [1].
For more details on the Householder reconstruction algorithm,
including the modified LU factorization, see [1].
This is the recursive version of the LU factorization algorithm.
Denote A - S by B. The algorithm divides the matrix B into four
submatrices:
[ B11 | B12 ] where B11 is n1 by n1,
B = [ -----|----- ] B21 is (m-n1) by n1,
[ B21 | B22 ] B12 is n1 by n2,
B22 is (m-n1) by n2,
with n1 = min(m,n)/2, n2 = n-n1.
The subroutine calls itself to factor B11, solves for B21,
solves for B12, updates B22, then calls itself to factor B22.
For more details on the recursive LU algorithm, see [2].
ZLAUNHR_COL_GETRFNP2 is called to factorize a block by the blocked
routine ZLAUNHR_COL_GETRFNP, which uses blocked code calling
Level 3 BLAS to update the submatrix. However, ZLAUNHR_COL_GETRFNP2
is self-sufficient and can be used without ZLAUNHR_COL_GETRFNP.
[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.
[2] 'Recursion leads to automatic variable blocking for dense linear
algebra algorithms', F. Gustavson, IBM J. of Res. and Dev.,
vol. 41, no. 6, pp. 737-755, 1997.
Parameters
M
M is INTEGER
The number of rows of the matrix A. M >= 0.
N
N is INTEGER
The number of columns of the matrix A. N >= 0.
A
A is COMPLEX*16 array, dimension (LDA,N)
On entry, the M-by-N matrix to be factored.
On exit, the factors L and U from the factorization
A-S=L*U; the unit diagonal elements of L are not stored.
LDA
LDA is INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D
D is COMPLEX*16 array, dimension min(M,N)
The diagonal elements of the diagonal M-by-N sign matrix S,
D(i) = S(i,i), where 1 <= i <= min(M,N). The elements can be
only ( +1.0, 0.0 ) or (-1.0, 0.0 ).
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.
Contributors:
November 2019, Igor Kozachenko,
Computer Science Division,
University of California, Berkeley
Author¶
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