Send mail to: mgnet@cs.yale.edu for the digests or bakeoff
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Current editor: Craig Douglas douglas-craig@cs.yale.edu
Anonymous ftp repository: casper.cs.yale.edu (128.36.12.1)
Today's editor: Craig Douglas (douglas-craig@cs.yale.edu)
Volume 2, Number 6 (June 19, 1992)
Today's topics:
C++/OOP and (F)WEB question about multigrid
Paper on effective field theories
p method domain decomposition paper
Parallel multigrid codes?
Journal of Parallel Algorithms and Applications Call for Papers
References
-------------------------------------------------------
From: Marcus Speh
Subject: C++/OOP and (F)WEB question about multigrid
I would like to know about references and/or people designing
MG algorithms in C++; I received U. Ruede's paper (thanks a lot !)
and he promised another one in the near future (following the SIAM workshop
on scientific C++ computing), but I would need something more basic and
cut to a question like: does it pay/ and why to code in an OOP language ?
Does anybody know about .web versions, either with
Levy's CWEB, Knuth's type-it-in-by-hand WEB or Krommes' multilingual
FWEB (ratfor, C, C++, fortran) of multigrid algorithms or - packages ?
I am just starting to use J. Krommes' FWEB for this purpose:
I find it exceptionally well suited for (scientific) visualization of
algorithms. I would appreciate any hint or information.
Marcus Speh
Editor's Note: I know that Joe Pasciak (pasciak@bnl.gov) and
------------- Parashkevov Rossen (rossen@ledaig.uwyo.edu) both write
their codes using fweb.
-------------------------------------------------------
Date: Thu, 14 May 92 16:16:11 +0200
From: Marcus Speh
Subject: Paper on multigrid methods for effective field theories
EFFECTIVE FIELD THEORIES
by G. Mack, T. Kalkreuter, G. Palma, M. Speh(*),
Univ. Hamburg, Germany
(with 7 PS figures included, 2 figures missing)
To appear in Springer Lecture Notes of Physics,
Proc. of the 31. IUKT Schladming on Computational Physics
eds. C.B. Lang, H. Gausterer
(*)comments, questions, please to: marcus@apollo.desy.de
ABSTRACT
Effective field theories encode the predictions of a quantum field theory at
low energy. The effective theory has a fairly low ultraviolet cutoff. As a
result, loop corrections are small, at least if the effective action contains
a term which is quadratic in the fields, and physical predictions can be read
straight from the effective Lagrangean.
Methods will be discussed how to compute an effective low energy action from a
given fundamental action, either analytically or numerically, or by a
combination of both methods. Basically, the idea is to integrate out the high
frequency components of fields. This requires the choice of a "blockspin,"
i.e., the specification of a low frequency field as a function of the
fundamental fields. These blockspins will be the fields of the effective
field theory. The blockspin need not be a field of the same type as one of
the fundamental fields, and it may be composite. Special features of
blockspins in nonabelian gauge theories will be discussed in some detail.
In analytical work and in multigrid updating schemes one needs interpolation
kernels A from coarse to fine grid in addition to the averaging kernels C
which determines the blockspin. A neural net strategy for finding optimal
kernels is presented.
Numerical methods are applicable to obtain actions of effective theories on
lattices of finite volume. The special case of a "lattice" with a single
site (the constraint effective potential) is of particular interest. In a
Higgs model, the effective action reduces in this case to the free energy,
considered as a function of a gauge covariant magnetization. Its shape
determines the phase structure of the theory. Its loop expansion with and
without gauge fields can be used to determine finite size corrections to
numerical data.
Keywords: Effective action,
lattice gauge theory,
blockspin methods,
multigrid updating schemes,
neural multilevel algorithm.
Comments, questions, suggestions are very welcome.
Please contact me.
Marcus Speh (marcus@apollo.desy.de)
-------------------------------------------------------
Date: Fri, 15 May 92
From: Jonathan M. Smith (j.m.smith@durham.ac.uk)
Subject: p method domain decomposition paper
Efficient Domain Decomposition Preconditioning for the p-version Finite Element
Method - The mass matrix.
Jonathan M. Smith
University of Durham
Department of Mathematical Sciences
Durham DH1 3LE
England
j.m.smith@durham.ac.uk
In recent years we have observed both the increased popularity of the
_p_-version finite element method and domain decomposition preconditioning
techniques. Current work has given us theoretical and numerical results,
showing that we can reduce the condition number of the stiffness matrix from
polynomial to polynomial logarithmic in the number of degrees of freedom.
However in the _p_-version, we have an additional problem. We observe that
heirachical bases, which while being very natural bases for the _p_-version
finite element method, are very unnatural bases for the mass matrix. This can
be seen by noting the growth in the condition number is exponential in _p_,
the degree of the polynomial on each element.
Using methods based on those for the stiffness matrix, derived by Babuska,
Craig, Mandel and Pitkaranta in 1988-89, it is possible to control this
ill-conditioning; resulting in a bound on the relative condition independent
of _p_, for relatively little work. In this paper we shall present present
empirical results for both triangular and quadrilateral quasi-uniform meshes,
and analytical bounds for quadrilateral meshes.
-------------------------------------------------------
Date: Mon, 15 Jun 92 06:05:57 PDT
From: lamb@research.CS.ORST.EDU (Ben Lam)
To: douglas@CS.YALE.EDU
Subject: MADPACK
hi,
I am using your MADPACK and wonder whether there is a parallel version
of it. Do you know of other parallel multigrid and conjugate gradient
programs?
Thanks.
--Ben Lam
lamb@research.cs.orst.edu
Editor's Note: The parallel version of version 2 of madpack is something
------------- I would not want to perpetrate on the world since it is
just too hard to use. There is a new version of madpack,
which contains an abstract solver (DAMG) and a 2D/3D
Poisson solver (DPMG). DAMG has 4 multigrid schemes, 11
solvers and 5 preconditioners (and can be different per
level), handles non PDE problems, any PDE that can be
discretized, and optionally will call back your own change
level, smoother, or preconditioner subroutines, can be
restarted after adding levels (coarser or finer), and will
feed your cat when you are on vacation. DPMG is tailored
for 3 different machine architectures, has a variety of
projection and interpolation operators, handles uniform or
tensor product grids and not completely trivial boundary
conditions.
I am talking to some people about doing a parallel version
of DPMG and possibly DAMG that is usable. Anyone
interested in this should contact me directly through Yale
(douglas-craig@cs.yale.edu).
FURTHER, I would be very interested in adding parallel
multigrid and/or domain decomposition solvers to the code
repository, so if you have something, please contribute
it. Research codes are welcome; they do not have to be
product quality.
-------------------------------------------------------
From: PAA Editorial Board
Subject: Journal of Parallel Algorithms and Applications Call for Papers
Journal of
Parallel
Algorithms and
Applications
Editor in Chief:
Professor David J. Evans, Director, Parallel Algorithms Research Centre,
Loughborough University of Technology, Loughborough, Leics. LE11 3TU, U.K.
Editorial Review Board:
Akl, S.G. (Canada) Loizou, G. (UK)
Boglaev, Y.P. (Russia) Margaritis, K.G. (Greece)
Clint, M. (UK) Petkov, N. (Netherlands)
Das, S.K. (USA) Quinn, M.J. (USA)
Dehne, F. (Canada) Raymond-Smith, V. (UK)
Douglas, C.C. (USA) Thune, M. (Sweden)
Jeong, C.S. (Korea) Tollenaire, T. (Belguim)
Lee, R.C.T. (R.O. China) Vajtersic, M. (Czechoslavakia)
Zenos, S.A. (USA)
Editorial Policy:
Parallel Algorithms and Applications will publish papers which relate to
Parallel and Multiprocessor computer systems covering the following
areas:
Parallel Algorithms: Design, Analysis and Usage in Numerical Analysis,
Discrete Mathematics, Non-numerical, Geometric, Graphics, Genetic,
Optimisation, Pattern Recognition, Simulation, Signal/Image Processing
and Systolic Algorithms.
Parallel Applications: Usage in the areas of Artificial Intelligence,
Systems Software and Compilers, CAD/CAM, Databases, Expert Systems,
Information Retrieval, Neural Networks, Industrial, Scientific and
Commercial Applications for Pipelined, Vector, Array, Parallel, and
Distributed Computers.
-------------------------------------------------------
Date: Mon, 1 Jun 1992 10:42:10 GMT
From: Paul.de.Zeeuw@cwi.nl
Subject: bib directory
@article{PMDeZeeuw_90,
author = "P. M. De{~Z}eeuw",
title = "Matrix--dependent prolongations and restrictions
in a blackbox multigrid solver",
journal = "J. Comput. Appl. Math.",
volume = "33",
year = "1990",
pages = "1--27"
}
@article{PMDeZeeuw_92,
author = "P. M. De{~Z}eeuw",
title = "Nonlinear multigrid applied to a one--dimensional
stationary semiconductor model",
journal = "SIAM J. Sci. Stat. Comput.",
volume = "13",
year = "1992",
pages = "512--530"
}
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End of MGNet Digest
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