Using a divide and conquer approach, SLASD0 computes the singular
 value decomposition (SVD) of a real upper bidiagonal N-by-M
 matrix B with diagonal D and offdiagonal E, where M = N + SQRE.
 The algorithm computes orthogonal matrices U and VT such that
 B = U * S * VT. The singular values S are overwritten on D.

 A related subroutine, SLASDA, computes only the singular values,
 and optionally, the singular vectors in compact form.

          N is INTEGER
         On entry, the row dimension of the upper bidiagonal matrix.
         This is also the dimension of the main diagonal array D.

          SQRE is INTEGER
         Specifies the column dimension of the bidiagonal matrix.
         = 0: The bidiagonal matrix has column dimension M = N;
         = 1: The bidiagonal matrix has column dimension M = N+1;

          D is REAL array, dimension (N)
         On entry D contains the main diagonal of the bidiagonal
         matrix.
         On exit D, if INFO = 0, contains its singular values.

          E is REAL array, dimension (M-1)
         Contains the subdiagonal entries of the bidiagonal matrix.
         On exit, E has been destroyed.

          U is REAL array, dimension at least (LDQ, N)
         On exit, U contains the left singular vectors.

          LDU is INTEGER
         On entry, leading dimension of U.

          VT is REAL array, dimension at least (LDVT, M)
         On exit, VT**T contains the right singular vectors.

          LDVT is INTEGER
         On entry, leading dimension of VT.

          SMLSIZ is INTEGER
         On entry, maximum size of the subproblems at the
         bottom of the computation tree.

          IWORK is INTEGER array, dimension (8*N)

          WORK is REAL array, dimension (3*M**2+2*M)

          INFO is INTEGER
          = 0:  successful exit.
          < 0:  if INFO = -i, the i-th argument had an illegal value.
          > 0:  if INFO = 1, a singular value did not converge