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.
引用
收藏
页码:1 / 21
页数:21
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