p?heevx

Computes selected eigenvalues and, optionally, eigenvectors of a Hermitian matrix.

Syntax

void pcheevx (char *jobz , char *range , char *uplo , MKL_INT *n , MKL_Complex8 *a , MKL_INT *ia , MKL_INT *ja , MKL_INT *desca , float *vl , float *vu , MKL_INT *il , MKL_INT *iu , float *abstol , MKL_INT *m , MKL_INT *nz , float *w , float *orfac , MKL_Complex8 *z , MKL_INT *iz , MKL_INT *jz , MKL_INT *descz , MKL_Complex8 *work , MKL_INT *lwork , float *rwork , MKL_INT *lrwork , MKL_INT *iwork , MKL_INT *liwork , MKL_INT *ifail , MKL_INT *iclustr , float *gap , MKL_INT *info );

void pzheevx (char *jobz , char *range , char *uplo , MKL_INT *n , MKL_Complex16 *a , MKL_INT *ia , MKL_INT *ja , MKL_INT *desca , double *vl , double *vu , MKL_INT *il , MKL_INT *iu , double *abstol , MKL_INT *m , MKL_INT *nz , double *w , double *orfac , MKL_Complex16 *z , MKL_INT *iz , MKL_INT *jz , MKL_INT *descz , MKL_Complex16 *work , MKL_INT *lwork , double *rwork , MKL_INT *lrwork , MKL_INT *iwork , MKL_INT *liwork , MKL_INT *ifail , MKL_INT *iclustr , double *gap , MKL_INT *info );

Include Files

  • mkl_scalapack.h

Description

The p?heevx function computes selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix A by calling the recommended sequence of ScaLAPACK functions. Eigenvalues and eigenvectors can be selected by specifying either a range of values or a range of indices for the desired eigenvalues.

Optimization Notice

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804

This notice covers the following instruction sets: SSE2, SSE4.2, AVX2, AVX-512.

Input Parameters

np = the number of rows local to a given process.

nq = the number of columns local to a given process.

jobz

(global) Must be 'N' or 'V'.

Specifies if it is necessary to compute the eigenvectors:

If jobz = 'N', then only eigenvalues are computed.

If jobz = 'V', then eigenvalues and eigenvectors are computed.

range

(global) Must be 'A', 'V', or 'I'.

If range = 'A', all eigenvalues will be found.

If range = 'V', all eigenvalues in the half-open interval [vl, vu] will be found.

If range = 'I', the eigenvalues with indices il through iu will be found.

uplo

(global) Must be 'U' or 'L'.

Specifies whether the upper or lower triangular part of the Hermitian matrix A is stored:

If uplo = 'U', a stores the upper triangular part of A.

If uplo = 'L', a stores the lower triangular part of A.

n

(global) The number of rows and columns of the matrix A(n 0).

a

(local).

Block cyclic array of global size n*n and local size lld_a*LOCc(ja+n-1). On entry, the Hermitian matrix A.

If uplo = 'U', only the upper triangular part of A is used to define the elements of the Hermitian matrix.

If uplo = 'L', only the lower triangular part of A is used to define the elements of the Hermitian matrix.

ia, ja

(global) The row and column indices in the global matrix A indicating the first row and the first column of the submatrix A, respectively.

desca

(global and local) array of size dlen_. The array descriptor for the distributed matrix A. If desca[ctxt_ - 1] is incorrect, p?heevx cannot guarantee correct error reporting.

vl, vu

(global)

If range = 'V', the lower and upper bounds of the interval to be searched for eigenvalues; not referenced if range = 'A' or 'I'.

il, iu

(global)

If range ='I', the indices of the smallest and largest eigenvalues to be returned.

Constraints:

il ≥ 1; min(il,n) ≤ iun.

Not referenced if range = 'A' or 'V'.

abstol

(global).

If jobz='V', setting abstol to p?lamch(context, 'U') yields the most orthogonal eigenvectors.

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 abstol+eps*max(|a|,|b|), where eps is the machine precision. If abstol is less than or equal to zero, then eps*norm(T) will be used in its place, where norm(T) is the 1-norm of the tridiagonal matrix obtained by reducing A to tridiagonal form.

Eigenvalues are computed most accurately when abstol is set to twice the underflow threshold 2*p?lamch('S'), not zero. If this function returns with ((mod(info,2)0).or.(mod(info/8,2)0)), indicating that some eigenvalues or eigenvectors did not converge, try setting abstol to 2*p?lamch('S').

Note

mod(x,y) is the integer remainder of x/y.

orfac

(global).

Specifies which eigenvectors should be reorthogonalized. Eigenvectors that correspond to eigenvalues which are within tol=orfac*norm(A) of each other are to be reorthogonalized. However, if the workspace is insufficient (see lwork), tol may be decreased until all eigenvectors to be reorthogonalized can be stored in one process. No reorthogonalization will be done if orfac equals zero. A default value of 1.0e-3 is used if orfac is negative.

orfac should be identical on all processes.

iz, jz

(global) The row and column indices in the global matrix Z indicating the first row and the first column of the submatrix Z, respectively.

descz

(global and local) array of size dlen_. The array descriptor for the distributed matrix Z. descz[ctxt_ - 1] must equal desca[ctxt_ - 1].

work

(local).

Array of size lwork.

lwork

(local) The size of the array work.

If only eigenvalues are requested:

lworkn + max(nb*(np0 + 1), 3)

If eigenvectors are requested:

lworkn + (np0+mq0+nb)*nb

with nq0 = numroc(nn, nb, 0, 0, NPCOL).

lwork 5*n + max(5*nn, np0*mq0+2*nb*nb) + iceil(neig, NPROW*NPCOL)*nn

For optimal performance, greater workspace is needed, that is

lworkmax(lwork, nhetrd_lwork)

where lwork is as defined above, and nhetrd_lwork = n + 2*(anb+1)*(4*nps+2) + (nps+1)*nps

ictxt = desca[ctxt_ - 1]

anb = pjlaenv(ictxt, 3, 'pchettrd', 'L', 0, 0, 0, 0)

sqnpc = sqrt(dble(NPROW * NPCOL))

nps = max(numroc(n, 1, 0, 0, sqnpc), 2*anb)

If lwork = -1, then lwork is global input and a workspace query is assumed; the function only calculates the size required for optimal performance for all work arrays. Each of these values is returned in the first entry of the corresponding work arrays, and no error message is issued by pxerbla.

rwork

(local)

Workspace array of size lrwork.

lrwork

(local) The size of the array work.

See below for definitions of variables used to define lwork.

If no eigenvectors are requested (jobz = 'N'), then lrwork 5*nn+4*n.

If eigenvectors are requested (jobz = 'V'), then the amount of workspace required to guarantee that all eigenvectors are computed is:

lrwork 4*n + max(5*nn, np0*mq0+2*nb*nb) + iceil(neig, NPROW*NPCOL)*nn

The computed eigenvectors may not be orthogonal if the minimal workspace is supplied and orfac is too small. If you want to guarantee orthogonality (at the cost of potentially poor performance) you should add the following values to lrwork:

(clustersize-1)*n,

where clustersize is the number of eigenvalues in the largest cluster, where a cluster is defined as a set of close eigenvalues:

{w[k - 1],..., w[k+clustersize-2]|w[j] ≤ w[j-1]+orfac*2*norm(A)}.

Variable definitions:

neig = number of eigenvectors requested;

nb = desca[mb_ - 1] = desca[nb_ - 1] = descz[mb_ - 1] = descz[nb_ - 1];

nn = max(n, NB, 2);

desca[rsrc_ - 1] = desca[nb_ - 1] = descz[rsrc_ - 1] = descz[csrc_ - 1] = 0;

np0 = numroc(nn, nb, 0, 0, NPROW);

mq0 = numroc(max(neig, nb, 2), nb, 0, 0, NPCOL);

iceil(x, y) is a ScaLAPACK function returning ceiling(x/y)

When lrwork is too small:

If lwork is too small to guarantee orthogonality, p?heevx attempts to maintain orthogonality in the clusters with the smallest spacing between the eigenvalues. If lwork is too small to compute all the eigenvectors requested, no computation is performed and info= -23 is returned. Note that when range='V', p?heevx does not know how many eigenvectors are requested until the eigenvalues are computed. Therefore, when range='V' and as long as lwork is large enough to allow p?heevx to compute the eigenvalues, p?heevx will compute the eigenvalues and as many eigenvectors as it can.

Relationship between workspace, orthogonality and performance:

If clustersizen/sqrt(NPROW*NPCOL), then providing enough space to compute all the eigenvectors orthogonally will cause serious degradation in performance. In the limit (that is, clustersize = n-1)p?stein will perform no better than ?stein on 1 processor.

For clustersize = n/sqrt(NPROW*NPCOL) reorthogonalizing all eigenvectors will increase the total execution time by a factor of 2 or more.

For clustersize>n/sqrt(NPROW*NPCOL) execution time will grow as the square of the cluster size, all other factors remaining equal and assuming enough workspace. Less workspace means less reorthogonalization but faster execution.

If lwork = -1, then lwork is global input and a workspace query is assumed; the function only calculates the size required for optimal performance for all work arrays. Each of these values is returned in the first entry of the corresponding work arrays, and no error message is issued by pxerbla.

iwork

(local) Workspace array.

liwork

(local), size of iwork.

liwork ≥ 6*nnp

Where: nnp = max(n, NPROW*NPCOL+1, 4)

If liwork = -1, then liwork is global input and a workspace query is assumed; the function only calculates the minimum and optimal size for all work arrays. Each of these values is returned in the first entry of the corresponding work array, and no error message is issued by pxerbla.

Output Parameters

a

On exit, the lower triangle (if uplo = 'L'), or the upper triangle (if uplo = 'U') of A, including the diagonal, is overwritten.

m

(global) The total number of eigenvalues found; 0 ≤ mn.

nz

(global) Total number of eigenvectors computed. 0 ≤ nzm.

The number of columns of z that are filled.

If jobz'V', nz is not referenced.

If jobz = 'V', nz = m unless the user supplies insufficient space and p?heevx is not able to detect this before beginning computation. To get all the eigenvectors requested, the user must supply both sufficient space to hold the eigenvectors in z (mdescz[n_ - 1]) and sufficient workspace to compute them. (See lwork). p?heevx is always able to detect insufficient space without computation unless range='V'.

w

(global).

Array of size n. The first m elements contain the selected eigenvalues in ascending order.

z

(local).

Array, global size n*n, local size lld_z*LOCc(jz+n-1).

If jobz ='V', then on normal exit the first m columns of z contain the orthonormal eigenvectors of the matrix corresponding to the selected eigenvalues. If an eigenvector fails to converge, then that column of z contains the latest approximation to the eigenvector, and the index of the eigenvector is returned in ifail.

If jobz = 'N', then z is not referenced.

work[0]

On exit, returns adequate workspace to allow optimal performance.

rwork

(local).

Array of size lrwork. On return, rwork[0] contains the optimal amount of workspace required for efficient execution.

If jobz='N'rwork[0] = optimal amount of workspace required to compute eigenvalues efficiently.

If jobz='V'rwork[0] = optimal amount of workspace required to compute eigenvalues and eigenvectors efficiently with no guarantee on orthogonality.

If range='V', it is assumed that all eigenvectors may be required.

iwork[0]

(local)

On return, iwork[0] contains the amount of integer workspace required.

ifail

(global)

Array of size n.

If jobz ='V', then on normal exit, the first m elements of ifail are zero. If (mod(info,2)0) on exit, then ifail contains the indices of the eigenvectors that failed to converge.

If jobz = 'N', then ifail is not referenced.

iclustr

(global)

Array of size 2*NPROW*NPCOL.

This array contains indices of eigenvectors corresponding to a cluster of eigenvalues that could not be reorthogonalized due to insufficient workspace (see lwork, orfac and info). Eigenvectors corresponding to clusters of eigenvalues indexed iclustr[2*i - 2]) to iclustr[2*i - 1], could not be reorthogonalized due to lack of workspace. Hence the eigenvectors corresponding to these clusters may not be orthogonal. iclustr is a zero terminated array. (iclustr[2*k - 1]0 and iclustr[2*k]=0) if and only if k is the number of clusters. iclustr is not referenced if jobz = 'N'.

gap

(global)

Array of size (NPROW*NPCOL)

This array contains the gap between eigenvalues whose eigenvectors could not be reorthogonalized. The output values in this array correspond to the clusters indicated by the array iclustr. As a result, the dot product between eigenvectors corresponding to the i-th cluster may be as high as (C*n)/gap(i) where C is a small constant.

info

(global)

If info = 0, the execution is successful.

If info < 0:

If the i-th argument is an array and the j-entry had an illegal value, then info = -(i*100+j). If the i-th argument is a scalar and had an illegal value, then info = -i.

If info> 0:

If (mod(info,2)0), then one or more eigenvectors failed to converge. Their indices are stored in ifail. Ensure abstol=2.0*p?lamch('U')

If (mod(info/2,2)0), then eigenvectors corresponding to one or more clusters of eigenvalues could not be reorthogonalized because of insufficient workspace.The indices of the clusters are stored in the array iclustr.

If (mod(info/4,2)0), then space limit prevented p?syevx from computing all of the eigenvectors between vl and vu. The number of eigenvectors computed is returned in nz.

If (mod(info/8,2)0), then p?stebz failed to compute eigenvalues. Ensure abstol=2.0*p?lamch('U').

See Also

For more complete information about compiler optimizations, see our Optimization Notice.
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