From na-net@na-net.stanford.edu Sun Apr 2 12:47:06 1989 Received: from beauty.stanford.edu by antares.mcs.anl.gov (4.0/SMI-DDN) id AA02627; Sun, 2 Apr 89 12:46:43 CDT Received: from patience.stanford.edu by beauty.stanford.edu (4.0/inc-1.5) id AA05096; Sun, 2 Apr 89 10:52:25 PDT Received: from bravery.stanford.edu by patience.stanford.edu (4.0/inc-1.5) id AA12356; Sun, 2 Apr 89 10:43:57 PDT Received: by bravery.stanford.edu (4.0/inc-1.5) id AA12049; Sun, 2 Apr 89 10:55:49 PDT Date: Sun, 2 Apr 89 10:55:49 PDT From: na-net@na-net.stanford.edu Message-Id: <8904021755.AA12049@bravery.stanford.edu> Return-Path: Subject: NA-NET distribution message Errors-To: nanet@na-net.stanford.edu Maint-Path: maintainer@na-net.stanford.edu To: na-net@na-net.stanford.edu Reply-To: na-net@na-net.stanford.edu Comment: requests, comments or problems to nanet@na-net.stanford.edu Comment: submissions to na@na-net.stanford.edu Comment: alternate address: na%na-net@score.stanford.edu Status: RO NA Digest Sunday, April 2, 1989 Volume 89 : Issue 13 Today's Editor: Cleve Moler Today's Topics: Random Algorithms for Elliptic PDE Position at Cornell Perfect Universal Numerical Kernel ------------------------------------------------------- From: Art Werschulz Date: 30 Mar 89 15:00:45 GMT Subject: Random Algorithms for Elliptic PDE Does anybody out there have pointers to information on random algorithms for *elliptic* partial differential equations? This would include (but not necessarily be limited to) random walk algorithms, Monte Carlo algorithms, etc. Thanks. Art Werschulz Columbia University Computer Science Department InterNet: agw@cs.columbia.edu BITnet: agw%cs.columbia.edu@cunyvm CSnet: agw%cs.columbia.edu@csnet-relay USEnet: ...!rutgers!columbia!cs!agw ATTnet: Columbia University (212) 854-8642 854-2736 Fordham University (212) 841-5323 841-5396 ------------------------------ From: Tom Coleman Date: Fri, 31 Mar 89 13:59:17 -0500 Subject: Position at Cornell Cornell University Computer Science Department Research Associate: Entry-level. Conduct research in the Cornell Computational Optimization Project (CCOP) with particular emphasis on large-scale continuous (and piece-wise continuous) problems. Ph.D. in computer science with specialization in numerical optimization. Post-doctoral experience (minimum of six months). Expert knowledge of methods for piece-wise continuous minimization, with a solid research tract record in this area. Working knowledge of MATLAB, Fortran and some parallel computing experience. Proven ability to analyze and establish mathematical convergence properties of minimization algorithms. Salary: $30,000 - $35,000 annually. Send curriculum vitae with three references to Thomas Coleman, Department of Computer Science, Cornell University, Ithaca, NY 14853-7501. Cornell University is an equal opportunity employer and welcomes applications from women and ethnic minorities. ------------------------------ From: Ed Plum Date: Sat, Apr 1 1989 20:09:64 Subject: Perfect Universal Numerical Kernel News Release April 1, 1989 Palo Alto, California Mathematicians at Palo Alto's Universal Numerical Techniques Studio (NUTS) today announced an unprecedented breakthrough in mathematical software. Their Perfect Universal Numerical Kernel (PUNK) is expected to replace all previously developed mathematical software. The new algorithm solves all possible numerical problems and achieves all the goals of quality mathematical software: * Perfectly Portable -- runs on all computers. * Perfectly Stable -- introduces no roundoff error. * Perfectly Parallel -- linear speedup for any number of processors. * Perfectly Patentable -- of course. The foundation of the technique is a data base of important, useful and frequently occurring numbers. The PUNK Preprocessor expands this into a list of all the floating point numbers for any particular computer. The user of the system specifies a problem by providing a function F(X) which evaluates the problem specific residual. PUNK then generates a sequence of approximate solutions, X, until one is found for which F(X) = 0. Separate processors on a parallel computer are assigned to individual components of the solution vector, and so perfect parallel efficiency is obtained on large problems. Since all possible floating point numbers are tried until an exact solution is found, no additional rounding errors are introduced by PUNK. The system is now in beta test, and will be available by the end of the quarter. ------------------------------ End of NA Digest ************************** -------