Send mail to: mgnet@cs.yale.edu for the digests mgnet-requests@cs.yale.edu for comments or help 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" } ------------------------------ End of MGNet Digest **************************