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Cellular Computing and Least Squares for Partial Differential Problems Parallel Solving
被引:0
作者:
Fressengeas, Nicolas
[1
,3
]
Frezza-Buet, Herve
[2
,3
]
机构:
[1] Univ Lorraine, Lab Mat Opt Photon & Syst, EA 4423, F-57070 Metz, France
[2] Supelec, Team Informat Multimodal & Signal, F-57070 Metz, France
[3] Georgia Tech CNRS, Int Joint Res Lab, UMI 2958, F-57070 Metz, France
关键词:
Partial differential equations;
cellular automata;
distributed memory;
parallel architectures;
LSFEM;
finite elements;
AUTOMATA;
CNN;
EQUATIONS;
ENVIRONMENT;
MODELS;
D O I:
暂无
中图分类号:
TP301 [理论、方法];
学科分类号:
081202 ;
摘要:
This paper shows how partial differential problems can be numerically solved on a parallel cellular architecture through a completely automated procedure. This procedure leads from a discrete differential problem to a Cellular Algorithm that efficiently runs on parallel distributed memory architectures. This completely automated procedure is based on a adaptation of the Least Square Finite Elements Method that allows local only computations in a discrete mesh. These local computations are automatically derived from the discrete differential problem through formal computing and lead automatically to a Cellular Algorithm which is efficiently coded for parallel execution on a dedicated distributed interactive platform.
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页码:1 / 21
页数:21
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