Footnotes
 - ...\title 
- 
This work was supported in part by 
DARPA and ARO under contract number DAAL03-91-C-0047, 
the National Science Foundation Science and Technology Center Cooperative
Agreement No. CCR-8809615, 
the Applied Mathematical Sciences subprogram of the Office of 
Energy Research, U.S.  Department of Energy, under Contract
DE-AC05-84OR21400, 
and 
the Stichting Nationale Computer Faciliteit (NCF) by Grant CRG 92.03.
- ...\author 
- Los Alamos National Laboratory,
     Los Alamos, NM 87544.
- ...\author 
- Department of Computer Science, University of
     Tennessee, Knoxville, TN 37996-1301.
- ...\author 
- Applied Mathematics Department,
              University of California, Los Angeles, CA 90024-1555.
- ...\author 
- Computer Science Division and Mathematics 
              Department, University of California, Berkeley, CA 94720.
- ...\author 
- Mathematical Sciences Section, 
     Oak Ridge National Laboratory, Oak Ridge, TN 37831-6367.
- ...\author 
- National Institute of Standards and Technology,
        Gaithersburg, MD, 20899
- ...\author 
- Department of Mathematics, Utrecht University, Utrecht, the
      Netherlands.
- ... 
- For a discussion of BLAS as building
    blocks, see [144][71][70][69] and
    LAPACK routines [3].  Also, see
    Appendix  . .
- ... 
- For a more detailed account of the early
  history of CG methods, we refer the reader to Golub and
  O'Leary [108] and
  Hestenes [123].
- ... 
- Under certain conditions, one can show
  that the point Jacobi algorithm is optimal, or close to optimal, in
  the sense of reducing the condition number, among all
  preconditioners of diagonal form.  This was shown by Forsythe and
  Strauss for matrices with Property A [99], and by van der
  Sluis [198] for general sparse matrices.  For
  extensions to block Jacobi preconditioners, see
  Demmel [66] and Elsner [95].
- ... 
- The SOR and Gauss-Seidel matrices are never used as preconditioners,
for a rather technical reason.
SOR-preconditioning with optimal  maps the eigenvalues of the
coefficient matrix to a circle in the complex plane;
see Hageman and Young [.3]HaYo:applied. In this case no
polynomial acceleration is possible, i.e., the accelerating polynomial
reduces to the trivial polynomial maps the eigenvalues of the
coefficient matrix to a circle in the complex plane;
see Hageman and Young [.3]HaYo:applied. In this case no
polynomial acceleration is possible, i.e., the accelerating polynomial
reduces to the trivial polynomial , and the resulting
method is simply the stationary SOR method.
Recent research by Eiermann and Varga [84] has shown
that polynomial
acceleration of SOR with suboptimal , and the resulting
method is simply the stationary SOR method.
Recent research by Eiermann and Varga [84] has shown
that polynomial
acceleration of SOR with suboptimal will yield no improvement
over simple SOR with optimal will yield no improvement
over simple SOR with optimal . .
- ... 
- To be precise, if we make an incomplete factorization  , we
refer to positions in , we
refer to positions in and and when we talk of positions in the
factorization. The matrix when we talk of positions in the
factorization. The matrix will have more nonzeros than will have more nonzeros than and and combined. combined.
- ... 
- The zero refers to the fact that only ``level zero'' fill is
permitted, that is, nonzero elements of the original matrix. Fill
levels are defined by calling an element of level  if it is
caused by elements at least one of which is of level if it is
caused by elements at least one of which is of level .
The first fill level is that caused by the original matrix elements. .
The first fill level is that caused by the original matrix elements.
- ... 
- In graph theoretical terms,  and and - - coincide if the matrix graph contains no triangles. coincide if the matrix graph contains no triangles.
- ... 
- Writing  is equally valid, but in practice
harder to implement. is equally valid, but in practice
harder to implement.
- ... 
-  On a machine with IEEE Standard
    Floating Point Arithmetic,  in single precision, and in single precision, and in double precision. in double precision.
- ... 
- IEEE standard
floating point arithmetic permits computations with  and
NaN, or Not-a-Number, symbols. and
NaN, or Not-a-Number, symbols.
- ... 
 
Jack Dongarra
Mon Nov 20 08:52:54 EST 1995