SRC/cunhr_col.f(3)
πΈ NAME πΈ
SRC/cunhr_col.f β okay bestie, this is the Library Functions Manual page for SRC/cunhr_col.f(3). It's the source-file glow-up for the cunhr_col routine. π
β¨ SYNOPSIS β¨
π§© Functions/Subroutines π§©
subroutine cunhr_col (m, n, nb, a, lda, t, ldt, d, info)
CUNHR_COL
π Function/Subroutine Documentation π
π subroutine cunhr_col π
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)
π CUNHR_COL π
π Purpose π
okay so CUNHR_COL takes an M-by-N complex matrix Q_in with orthonormal columns as input, stored in A, and performs Householder Reconstruction (HR). That means it reconstructs Householder vectors V(i) that implicitly represent 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). π«Ά
π Parameters π
MβMisINTEGER. The number of rows of the matrixA.M >= 0.NβNisINTEGER. The number of columns of the matrixA.M >= N >= 0.NBβNBisINTEGER. The column block size to be used in the reconstruction of Householder column vector blocks in the arrayAand corresponding block reflectors in the arrayT.NB >= 1. (Note that ifNB > N, thenNis used instead ofNBas the column block size.) πAβAisCOMPLEX array, dimension (LDA,N).- On entry: the array
Acontains anM-by-Northonormal matrixQ_in, i.e. the columns ofAare orthogonal unit vectors. - On exit: the elements below the diagonal of
Arepresent the unit lower-trapezoidal matrixVof Householder column vectorsV(i). The unit diagonal entries ofVare not stored (same format as the output below the diagonal inAfromCGEQRT). The matrixTand the matrixVstored on output inAimplicitly defineQ_out. - The elements above the diagonal contain the factor
Uof the LU-decomposition:
- On entry: the array
Q_in - ( S ) = V * U
( 0 )
where 0 is a (M-N)-by-(M-N) zero matrix.
LDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,M).TβTisCOMPLEX array, dimension (LDT, N).- Let
NOCB = Number_of_output_col_blocks = CEIL(N/NB). - On exit,
T(1:NB, 1:N)containsNOCBupper-triangular block reflectors used to defineQ_out, stored in compact form as a sequence of upper-triangularNB-by-NBcolumn blocks (same format as the outputTinCGEQRT). The matrixTand the matrixVstored on output inAimplicitly defineQ_out. - NOTE: the lower triangles below the upper-triangular blocks will be filled with zeros. See Further Details. π
- Let
LDTβLDTisINTEGER. The leading dimension of the arrayT.LDT >= max(1,min(NB,N)).DβDisCOMPLEX array, dimension min(M,N). The elements can be only plus or minus one.D(i)is constructed asD(i) = -SIGN(Q_in_i(i,i)), where1 <= i <= min(M,N), andQ_in_iisQ_inafter performingi-1steps of βmodifiedβ Gaussian elimination. See Further Details.
INFOβINFOisINTEGER.= 0: successful exit< 0: ifINFO = -i, thei-th argument had an illegal value
π¦ Further Details π¦
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. (yes, the source literally says Y there β I'm not editing it, bestie π)
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] ,
G. Ballard, J. Demmel, L. Grigori, M. Jacquelin, H.D. Nguyen,
E. Solomonik, J. Parallel Distrib. Comput.,
vol. 85, pp. 3-31, 2015.
π Author π
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π Contributors π
November 2019, Igor Kozachenko, Computer Science Division, University of California, Berkeley. π
Definition at line 258 of file cunhr_col.f.
πͺ Author πͺ
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