DSYTRD_SY2SB(3)
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/dsytrd_sy2sb.f
Bestie, this is the DSYTRD_SY2SB(3) page from the Library Functions Manual, and it comes straight out of that file path. π
β¨ SYNOPSIS β¨
π Functions/Subroutines
subroutine DSYTRD_SY2SB (uplo, n, kd, a, lda, ab, ldab, tau, work, lwork, info)
DSYTRD_SY2SB β yup, that's the subroutine we're talking about. π«Ά
π FUNCTION/SUBROUTINE DOCUMENTATION π
subroutine DSYTRD_SY2SB (character uplo, integer n, integer kd, double
precision, dimension( lda, * ) a, integer lda, double precision,
dimension( ldab, * ) ab, integer ldab, double precision, dimension( * )
tau, double precision, dimension( * ) work, integer lwork, integer info)
DSYTRD_SY2SB
π Purpose
DSYTRD_SY2SB reduces a real symmetric matrix A to real symmetric band-diagonal form AB by an orthogonal similarity transformation:
Q**T * A * Q = AB.
Lowkey iconic. β¨
π Parameters
UPLOβUPLO is CHARACTER*1= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
NβN is INTEGER. The order of the matrixA.N >= 0.KDβKD is INTEGER. The number of superdiagonals of the reduced matrix ifUPLO = 'U', or the number of subdiagonals ifUPLO = 'L'.KD >= 0. The reduced matrix is stored in the arrayAB.AβA is DOUBLE PRECISION array, dimension (LDA,N).- On entry, the symmetric matrix
A. IfUPLO = 'U', the leadingN-by-Nupper triangular part ofAcontains the upper triangular part of the matrixA, and the strictly lower triangular part ofAis not referenced. IfUPLO = 'L', the leadingN-by-Nlower triangular part ofAcontains the lower triangular part of the matrixA, and the strictly upper triangular part ofAis not referenced. - On exit, if
UPLO = 'U', the diagonal and first superdiagonal ofAare overwritten by the corresponding elements of the tridiagonal matrixT, and the elements above the first superdiagonal, with the arrayTAU, represent the orthogonal matrixQas a product of elementary reflectors; ifUPLO = 'L', the diagonal and first subdiagonal ofAare over-written by the corresponding elements of the tridiagonal matrixT, and the elements below the first subdiagonal, with the arrayTAU, represent the orthogonal matrixQas a product of elementary reflectors. See Further Details.
- On entry, the symmetric matrix
LDAβLDA is INTEGER. The leading dimension of the arrayA.LDA >= max(1,N).ABβAB is DOUBLE PRECISION array, dimension (LDAB,N). On exit, the upper or lower triangle of the symmetric band matrixA, stored in the firstKD+1rows of the array. Thej-th column ofAis stored in thej-th column of the arrayABas follows:
if UPLO = 'U', AB(kd+1+i-j,j) = A(i,j) for max(1,j-kd)<=i<=j;
if UPLO = 'L', AB(1+i-j,j) = A(i,j) for j<=i<=min(n,j+kd).
LDABβLDAB is INTEGER. The leading dimension of the arrayAB.LDAB >= KD+1.TAUβTAU is DOUBLE PRECISION array, dimension (N-KD). The scalar factors of the elementary reflectors (see Further Details).WORKβWORK is DOUBLE PRECISION array, dimension (LWORK). On exit, ifINFO = 0, or ifLWORK=-1,WORK(1)returns the size ofLWORK.LWORKβLWORK is INTEGER. The dimension of the arrayWORKwhich should be calculated by a workspace query.LWORK = MAX(1, LWORK_QUERY). IfLWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of theWORKarray, returns this value as the first entry of theWORKarray, and no error message related toLWORKis issued byXERBLA.LWORK_QUERY = N*KD + N*max(KD,FACTOPTNB) + 2*KD*KD- where
FACTOPTNBis the blocking used by the QR or LQ algorithm, usuallyFACTOPTNB=128is a good choice otherwise puttingLWORK=-1will provide the size ofWORK.
INFOβINFO is INTEGER= 0: successful exit< 0: ifINFO = -i, thei-th argument had an illegal value
π«Ά AUTHOR π«Ά
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π§ FURTHER DETAILS π§
Implemented by Azzam Haidar.
All details are available on technical report, SC11, SC13 papers.
- Azzam Haidar, Hatem Ltaief, and Jack Dongarra. Parallel reduction to condensed forms for symmetric eigenvalue problems using aggregated fine-grained and memory-aware kernels. In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC '11), New York, NY, USA, Article 8 , 11 pages.
http://doi.acm.org/10.1145/2063384.2063394 - A. Haidar, J. Kurzak, P. Luszczek, 2013. An improved parallel singular value algorithm and its implementation for multicore hardware, In Proceedings of 2013 International Conference for High Performance Computing, Networking, Storage and Analysis (SC '13). Denver, Colorado, USA, 2013. Article 90, 12 pages.
http://doi.acm.org/10.1145/2503210.2503292 - A. Haidar, R. Solca, S. Tomov, T. Schulthess and J. Dongarra. A novel hybrid CPU-GPU generalized eigensolver for electronic structure calculations based on fine-grained memory aware tasks. International Journal of High Performance Computing Applications. Volume 28 Issue 2, Pages 196-209, May 2014.
http://hpc.sagepub.com/content/28/2/196
If UPLO = 'U', the matrix Q is represented as a product of elementary reflectors:
Q = H(k)**T . . . H(2)**T H(1)**T, where k = n-kd.
Each H(i) has the form:
H(i) = I - tau * v * v**T
where tau is a real scalar, and v is a real vector with v(1:i+kd-1) = 0 and v(i+kd) = 1; conjg(v(i+kd+1:n)) is stored on exit in A(i,i+kd+1:n), and tau in TAU(i).
If UPLO = 'L', the matrix Q is represented as a product of elementary reflectors:
Q = H(1) H(2) . . . H(k), where k = n-kd.
Each H(i) has the form:
H(i) = I - tau * v * v**T
where tau is a real scalar, and v is a real vector with v(kd+1:i) = 0 and v(i+kd+1) = 1; v(i+kd+2:n) is stored on exit in A(i+kd+2:n,i), and tau in TAU(i).
The contents of A on exit are illustrated by the following examples with n = 5:
if UPLO = 'U': if UPLO = 'L':
( ab ab/v1 v1 v1 v1 ) ( ab )
( ab ab/v2 v2 v2 ) ( ab/v1 ab )
( ab ab/v3 v3 ) ( v1 ab/v2 ab )
( ab ab/v4 ) ( v1 v2 ab/v3 ab )
( ab ) ( v1 v2 v3 ab/v4 ab )
where d and e denote diagonal and off-diagonal elements of T, and vi denotes an element of the vector defining H(i).
.fi
Definition at line 241 of file dsytrd_sy2sb.f.
π AUTHOR (the auto-generated one) π
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