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DEVELOPMENT OF DISTRIBUTED COMPUTING FRAMEWORK FOR PARALLEL MULTI-DISCIPLINARY OPTIMIZATION

机译:并行多学科优化的分布式计算框架开发

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This paper discusses the detailed design and development of a web based parallel multi-disciplinary optimization (PMDO) framework in the distributed computing environment. This system consists of the HTTP server, the XML parser and the communication module based on TCP/IP, and is built around a computational kernel called the ACES kernel, which provides powerful computation and evaluation capabilities as well as optimization routines specifically designed for engineering purposes. We formulate and subdivide an optimization problem into several sub-problems such that one node is designated as a master which solves the overall problem and the others are distributed to client nodes each of which handles each independent sub-optimization problem. In the iteration to solve the overall optimization problem, the master forwards necessary data to each client for updated values which are the solutions of sub-optimization problems and collects the results from all the client nodes. The master continues the iteration until the optimum is reached. All optimization problems are represented in XML form and provided as input to the master and each client node.
机译:本文讨论了分布式计算环境中基于Web的并行多学科优化(PMDO)框架的详细设计和开发。该系统由HTTP服务器,XML解析器和基于TCP / IP的通信模块组成,并围绕称为ACES内核的计算内核构建,该内核提供强大的计算和评估功能以及专为工程目的设计的优化例程。 。我们将优化问题表述并细分为几个子问题,以便将一个节点指定为解决总体问题的主节点,将其他节点分配给客户端节点,每个节点分别处理每个独立的子优化问题。在解决整体优化问题的迭代中,主服务器将必要的数据转发给每个客户端以获取更新值,这些值是子优化问题的解决方案,并从所有客户端节点收集结果。主机继续迭代,直到达到最佳。所有优化问题均以XML形式表示,并作为输入提供给主节点和每个客户端节点。

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