/home/abui...r_2stage.f(3)
π /home/abui...r_2stage.f(3) π
From the Library Functions Manual, bestie. This is the cheevr_2stage.f page, and it's giving big LAPACK energy β part 1, with more coming. π«Ά
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/cheevr_2stage.f
β¨ SYNOPSIS β¨
Functions/Subroutines
Functions/Subroutines
subroutine CHEEVR_2STAGE (jobz, range, uplo, n, a, lda, vl, vu, il, iu,
abstol, m, w, z, ldz, isuppz, work, lwork, rwork, lrwork, iwork,
liwork, info)
CHEEVR_2STAGE computes the eigenvalues and, optionally, the left
and/or right eigenvectors for HE matrices
π Function/Subroutine Documentation π
subroutine CHEEVR_2STAGE (character jobz, character range, character uplo,
integer n, complex, dimension( lda, * ) a, integer lda, real vl, real
vu, integer il, integer iu, real abstol, integer m, real, dimension( * )
w, complex, dimension( ldz, * ) z, integer ldz, integer, dimension( * )
isuppz, complex, dimension( * ) work, integer lwork, real, dimension( *
) rwork, integer lrwork, integer, dimension( * ) iwork, integer liwork,
integer info)
CHEEVR_2STAGE computes the eigenvalues and, optionally, the left and/or right eigenvectors for HE matrices. π
π Purpose π
Okay so bestie, CHEEVR_2STAGE computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix A using the 2stage technique for the reduction to tridiagonal. Eigenvalues and eigenvectors can be selected by specifying either a range of values or a range of indices for the desired eigenvalues. β¨
CHEEVR_2STAGE first reduces the matrix A to tridiagonal form T with a call to CHETRD. Then, whenever possible, CHEEVR_2STAGE calls CSTEMR to compute eigenspectrum using Relatively Robust Representations. CSTEMR computes eigenvalues by the dqds algorithm, while orthogonal eigenvectors are computed from various L D L^T representations (also known as Relatively Robust Representations). Gram-Schmidt orthogonalization is avoided as far as possible. More specifically, the various steps of the algorithm are as follows. π§
For each unreduced block (submatrix) of T:
(a)ComputeT - sigma I = L D L^T, so thatLandDdefine all the wanted eigenvalues to high relative accuracy. This means that small relative changes in the entries ofDandLcause only small relative changes in the eigenvalues and eigenvectors. The standard (unfactored) representation of the tridiagonal matrixTdoes not have this property in general.(b)Compute the eigenvalues to suitable accuracy. If the eigenvectors are desired, the algorithm attains full accuracy of the computed eigenvalues only right before the corresponding vectors have to be computed, see steps c) and d).(c)For each cluster of close eigenvalues, select a new shift close to the cluster, find a new factorization, and refine the shifted eigenvalues to suitable accuracy.(d)For each eigenvalue with a large enough relative separation compute the corresponding eigenvector by forming a rank revealing twisted factorization. Go back to (c) for any clusters that remain.
The desired accuracy of the output can be specified by the input parameter ABSTOL. π―
For more details, see CSTEMR's documentation and:
- Inderjit S. Dhillon and Beresford N. Parlett: Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004.
- Inderjit Dhillon and Beresford Parlett: SIAM Journal on Matrix Analysis and Applications, Vol. 25, 2004. Also LAPACK Working Note 154.
- Inderjit Dhillon: , Computer Science Division Technical Report No. UCB/CSD-97-971, UC Berkeley, May 1997.
Note 1:CHEEVR_2STAGEcallsCSTEMRwhen the full spectrum is requested on machines which conform to the ieee-754 floating point standard.CHEEVR_2STAGEcallsSSTEBZandCSTEINon non-ieee machines and when partial spectrum requests are made. π«Ά
Warning, bestie: Normal execution of CSTEMR may create NaNs and infinities and hence may abort due to a floating point exception in environments which do not handle NaNs and infinities in the ieee standard default manner. π
π§Έ Parameters π§Έ
JOBZ
JOBZisCHARACTER*1'N': Compute eigenvalues only;'V': Compute eigenvalues and eigenvectors. Not available in this release.
RANGE
RANGEisCHARACTER*1'A': all eigenvalues will be found.'V': all eigenvalues in the half-open interval(VL,VU]will be found.'I': theIL-th throughIU-th eigenvalues will be found.
For RANGE = 'V' or 'I' and IU - IL < N - 1, SSTEBZ and CSTEIN are called. π
UPLO
UPLOisCHARACTER*1'U': Upper triangle ofAis stored;'L': Lower triangle ofAis stored.
N
NisINTEGER- The order of the matrix
A.N >= 0.
- The order of the matrix
A
AisCOMPLEXarray, dimension(LDA, N)- On entry, the Hermitian matrix
A. IfUPLO = 'U', the leadingN-by-Nupper triangular part ofAcontains the upper triangular part of the matrixA. IfUPLO = 'L', the leadingN-by-Nlower triangular part ofAcontains the lower triangular part of the matrixA. - On exit, the lower triangle (if
UPLO='L') or the upper triangle (ifUPLO='U') ofA, including the diagonal, is destroyed. π
- On entry, the Hermitian matrix
LDA
LDAisINTEGER- The leading dimension of the array
A.LDA >= max(1,N).
- The leading dimension of the array
VL
VLisREAL- If
RANGE='V', the lower bound of the interval to be searched for eigenvalues.VL < VU. - Not referenced if
RANGE = 'A'or'I'.
- If
VU
VUisREAL- If
RANGE='V', the upper bound of the interval to be searched for eigenvalues.VL < VU. - Not referenced if
RANGE = 'A'or'I'.
- If
IL
ILisINTEGER- If
RANGE='I', the index of the smallest eigenvalue to be returned. 1 <= IL <= IU <= N, ifN > 0;IL = 1andIU = 0ifN = 0.- Not referenced if
RANGE = 'A'or'V'.
- If
IU
IUisINTEGER- If
RANGE='I', the index of the largest eigenvalue to be returned. 1 <= IL <= IU <= N, ifN > 0;IL = 1andIU = 0ifN = 0.- Not referenced if
RANGE = 'A'or'V'.
- If
ABSTOL
ABSTOLisREAL- The absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval
[a,b]of width less than or equal to
- The absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval
ABSTOL + EPS * max( |a|,|b| ) ,
where EPS is the machine precision. If ABSTOL is less than or equal to zero, then EPS*|T| will be used in its place, where |T| is the 1-norm of the tridiagonal matrix obtained by reducing A to tridiagonal form.
See by Demmel and Kahan, LAPACK Working Note #3.
If high relative accuracy is important, set ABSTOL to SLAMCH( 'Safe minimum' ). Doing so will guarantee that eigenvalues are computed to high relative accuracy when possible in future releases. The current code does not make any guarantees about high relative accuracy, but future releases will. See J. Barlow and J. Demmel, , LAPACK Working Note #7, for a discussion of which matrices define their eigenvalues to high relative accuracy. π
M
MisINTEGER- The total number of eigenvalues found.
0 <= M <= N. - If
RANGE = 'A',M = N, and ifRANGE = 'I',M = IU-IL+1.
- The total number of eigenvalues found.
W
WisREALarray, dimension(N)- The first
Melements contain the selected eigenvalues in ascending order. β
- The first
Z
ZisCOMPLEXarray, dimension(LDZ, max(1,M))- If
JOBZ = 'V', then ifINFO = 0, the firstMcolumns ofZcontain the orthonormal eigenvectors of the matrixAcorresponding to the selected eigenvalues, with the i-th column ofZholding the eigenvector associated withW(i). - If
JOBZ = 'N', thenZis not referenced. - Note: the user must ensure that at least
max(1,M)columns are supplied in the arrayZ; ifRANGE = 'V', the exact value ofMis not known in advance and an upper bound must be used. π
- If
LDZ
LDZisINTEGER- The leading dimension of the array
Z.LDZ >= 1, and ifJOBZ = 'V',LDZ >= max(1,N).
- The leading dimension of the array
ISUPPZ
ISUPPZisINTEGERarray, dimension( 2*max(1,M) )- The support of the eigenvectors in
Z, i.e., the indices indicating the nonzero elements inZ. The i-th eigenvector is nonzero only in elementsISUPPZ( 2*i-1 )throughISUPPZ( 2*i ). This is an output ofCSTEMR(tridiagonal matrix). The support of the eigenvectors ofAis typically1:Nbecause of the unitary transformations applied byCUNMTR. - Implemented only for
RANGE = 'A'or'I'andIU - IL = N - 1. π¦
- The support of the eigenvectors in
WORK
WORKisCOMPLEXarray, dimension(MAX(1,LWORK))- On exit, if
INFO = 0,WORK(1)returns the optimalLWORK. β¨
- On exit, if
LWORK
πΎ LWORK (continued, because sheβs a main character)
okay so LWORK is INTEGER β itβs the dimension of the array WORK. and bestie, this part is a whole journey:
- If
JOBZ = 'N'andN > 1,LWORKmust be queried. no cap, you literally have to query it. LWORK = MAX(1, 26*N, dimension) where
LWORK = MAX(1, 26*N, dimension) where
dimension = max(stage1,stage2) + (KD+1)*N + N
= N*KD + N*max(KD+1,FACTOPTNB)
+ max(2*KD*KD, KD*NTHREADS)
+ (KD+1)*N + N
where KD is the blocking size of the reduction, FACTOPTNB is the blocking used by the QR or LQ algorithm, usually FACTOPTNB=128 is a good choice, NTHREADS is the number of threads used when openMP compilation is enabled, otherwise =1.
- If
JOBZ = 'V'andN > 1,LWORKmust be queried. Not yet available π - If
LWORK = -1, then a workspace query is assumed; the routine only calculates the optimal sizes of theWORK,RWORKandIWORKarrays, returns these values as the first entries of theWORK,RWORKandIWORKarrays, and no error message related toLWORKorLRWORKorLIWORKis issued byXERBLA.
πΈ RWORK
RWORK is REAL array, dimension (MAX(1,LRWORK)). On exit, if INFO = 0, RWORK(1) returns the optimal (and minimal) LRWORK. slay β¨
π LRWORK
LRWORK is INTEGER. The length of the array RWORK. LRWORK >= max(1,24*N).
If LRWORK = -1, then a workspace query is assumed; the routine only calculates the optimal sizes of the WORK, RWORK and IWORK arrays, returns these values as the first entries of the WORK, RWORK and IWORK arrays, and no error message related to LWORK or LRWORK or LIWORK is issued by XERBLA.
π¦ IWORK
IWORK is INTEGER array, dimension (MAX(1,LIWORK)). On exit, if INFO = 0, IWORK(1) returns the optimal (and minimal) LIWORK.
π LIWORK
LIWORK is INTEGER. The dimension of the array IWORK. LIWORK >= max(1,10*N).
If LIWORK = -1, then a workspace query is assumed; the routine only calculates the optimal sizes of the WORK, RWORK and IWORK arrays, returns these values as the first entries of the WORK, RWORK and IWORK arrays, and no error message related to LWORK or LRWORK or LIWORK is issued by XERBLA.
π INFO
INFO is INTEGER
= 0: successful exit< 0: ifINFO = -i, the i-th argument had an illegal value> 0: Internal error
π Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π«Ά Contributors:
- Inderjit Dhillon, IBM Almaden, USA
- Osni Marques, LBNL/NERSC, USA
- Ken Stanley, Computer Science Division, University of California at Berkeley, USA
- Jason Riedy, Computer Science Division, University of California at Berkeley, USA
π Further Details:
All details about the 2stage techniques are available in:
- 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
Definition at line 402 of file cheevr_2stage.f.
π€ Author
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