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A Monte Carlo boundary propagation method for the solution of Poisson's equation [electronic resource].

Published:
Washington, D.C. : United States. Dept. of Energy, 1990.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description:
Pages: (6 pages) : digital, PDF file
Additional Creators:
Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary:
To often the parallelism of a computational algorithm is used (or advertised) as a desirable measure of its performance. That is, the higher the computational parallelism the better the expected performance. With the current interest and emphasis on massively parallel computer systems, the notion of highly parallel algorithms is the subject of many conferences and funding proposals. Unfortunately, the revolution'' that this vision promises has served to further complicate the measure of parallel performance by the introduction of such notions as scaled speedup and scalable systems. As a counter example to the merits of highly parallel algorithms whose parallelism scales linearly with increasing problem size, we introduce a slight modification to a highly parallel Monte Carlo technique that is used to estimate the solution of Poisson's equation. This simple modification is shown to yield a much better estimate to the solution by incorporating a more efficient use of boundary data (Dirichlet boundary conditions). A by product of this new algorithm is a much more efficient sequential algorithm but at the expense of sacrificing parallelism. 3 refs.
Report Numbers:
E 1.99:la-ur-90-2577
E 1.99: conf-901101--22
conf-901101--22
la-ur-90-2577
Subject(s):
Other Subject(s):
Note:
Published through SciTech Connect.
01/01/1990.
"la-ur-90-2577"
" conf-901101--22"
"DE90015060"
American Nuclear Society winter meeting, Washington, DC (USA), 11-15 Nov 1990.
Brickner, R.G.; Hiromoto, R.
Funding Information:
W-7405-ENG-36
View MARC record | catkey: 14358151