**Today's Topics:**

From: Art Werschulz <agw@columbia.edu>

Date: 30 Mar 89 15:00:45 GMT

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

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From: Tom Coleman <coleman@gvax.cs.cornell.edu>

Date: Fri, 31 Mar 89 13:59:17 -0500

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.

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From: Ed Plum <plum@nuts.com>

Date: Sat, Apr 1 1989 20:09:64

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.

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End of NA Digest

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