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

来源：

JOURNAL OF CELLULAR AUTOMATA | 2014年 / 9卷 / 01期

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

页码：1 / 21

页数：21

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