CXML
        	    
LAPACK version 3.0
sstedc(3)

PURPOSE
  SSTEDC - compute all eigenvalues and, optionally, eigenvectors of a
  symmetric tridiagonal matrix using the divide and conquer method

SYNTAX
  SUBROUTINE SSTEDC( COMPZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO
		     )

      CHARACTER	     COMPZ

      INTEGER	     INFO, LDZ, LIWORK, LWORK, N

      INTEGER	     IWORK( * )

      REAL	     D( * ), E( * ), WORK( * ), Z( LDZ, * )

DESCRIPTION
  SSTEDC computes all eigenvalues and, optionally, eigenvectors of a
  symmetric tridiagonal matrix using the divide and conquer method. The
  eigenvectors of a full or band real symmetric matrix can also be found if
  SSYTRD or SSPTRD or SSBTRD has been used to reduce this matrix to
  tridiagonal form.

  This code makes very mild assumptions about floating point arithmetic. It
  will work on machines with a guard digit in add/subtract, or on those
  binary machines without guard digits which subtract like the Cray X-MP,
  Cray Y-MP, Cray C-90, or Cray-2.  It could conceivably fail on hexadecimal
  or decimal machines without guard digits, but we know of none.  See SLAED3
  for details.

ARGUMENTS
  COMPZ	  (input) CHARACTER*1
	  = 'N':  Compute eigenvalues only.
	  = 'I':  Compute eigenvectors of tridiagonal matrix also.
	  = 'V':  Compute eigenvectors of original dense symmetric matrix
	  also.	 On entry, Z contains the orthogonal matrix used to reduce
	  the original matrix to tridiagonal form.

  N	  (input) INTEGER
	  The dimension of the symmetric tridiagonal matrix.  N >= 0.

  D	  (input/output) REAL array, dimension (N)
	  On entry, the diagonal elements of the tridiagonal matrix.  On
	  exit, if INFO = 0, the eigenvalues in ascending order.

  E	  (input/output) REAL array, dimension (N-1)
	  On entry, the subdiagonal elements of the tridiagonal matrix.	 On
	  exit, E has been destroyed.

  Z	  (input/output) REAL array, dimension (LDZ,N)
	  On entry, if COMPZ = 'V', then Z contains the orthogonal matrix
	  used in the reduction to tridiagonal form.  On exit, if INFO = 0,
	  then if COMPZ = 'V', Z contains the orthonormal eigenvectors of the
	  original symmetric matrix, and if COMPZ = 'I', Z contains the
	  orthonormal eigenvectors of the symmetric tridiagonal matrix.	 If
	  COMPZ = 'N', then Z is not referenced.

  LDZ	  (input) INTEGER
	  The leading dimension of the array Z.	 LDZ >= 1.  If eigenvectors
	  are desired, then LDZ >= max(1,N).

  WORK	  (workspace/output) REAL array,
	  dimension (LWORK) On exit, if INFO = 0, WORK(1) returns the optimal
	  LWORK.

  LWORK	  (input) INTEGER
	  The dimension of the array WORK.  If COMPZ = 'N' or N <= 1 then
	  LWORK must be at least 1.  If COMPZ = 'V' and N > 1 then LWORK must
	  be at least ( 1 + 3*N + 2*N*lg N + 3*N**2 ), where lg( N ) =
	  smallest integer k such that 2**k >= N.  If COMPZ = 'I' and N > 1
	  then LWORK must be at least ( 1 + 4*N + N**2 ).

	  If LWORK = -1, then a workspace query is assumed; the routine only
	  calculates the optimal size of the WORK array, returns this value
	  as the first entry of the WORK array, and no error message related
	  to LWORK is issued by XERBLA.

  IWORK	  (workspace/output) INTEGER array, dimension (LIWORK)
	  On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.

  LIWORK  (input) INTEGER
	  The dimension of the array IWORK.  If COMPZ = 'N' or N <= 1 then
	  LIWORK must be at least 1.  If COMPZ = 'V' and N > 1 then LIWORK
	  must be at least ( 6 + 6*N + 5*N*lg N ).  If COMPZ = 'I' and N > 1
	  then LIWORK must be at least ( 3 + 5*N ).

	  If LIWORK = -1, then a workspace query is assumed; the routine only
	  calculates the optimal size of the IWORK array, returns this value
	  as the first entry of the IWORK array, and no error message related
	  to LIWORK is issued by XERBLA.

  INFO	  (output) INTEGER
	  = 0:	successful exit.
	  < 0:	if INFO = -i, the i-th argument had an illegal value.
	  > 0:	The algorithm failed to compute an eigenvalue while working
	  on the submatrix lying in rows and columns INFO/(N+1) through
	  mod(INFO,N+1).

FURTHER DETAILS
  Based on contributions by
     Jeff Rutter, Computer Science Division, University of California
     at Berkeley, USA
  Modified by Francoise Tisseur, University of Tennessee.