Parameter estimation of complex mathematical models of human physiology using remote simulation distributed in scientific cloud

T. Kulhánek, M. Matejak, J. Šilar, J. Kofránek
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引用次数: 1

Abstract

A generic system for estimation of model parameters - calibrate models - is introduced. The proposed system architecture is built of several loosely coupled modules behaving as RESTful web services and allowing to integrate other parts of the system via HTTP protocol and data exchanged in JSON format. The system was designed in such a way that the most demanding computational part is computed in parallel and computation may be distributed to remote computational resources. A test deployment was done in scientific cloud provided by czech NGI CESNET. Parameter identification of complex models got significant speedup on cloud computing resources.
分布在科学云中的远程模拟人体生理复杂数学模型的参数估计
介绍了一种通用的模型参数估计系统——标定模型。提出的系统架构是由几个松散耦合的模块组成的,这些模块表现为RESTful web服务,并允许通过HTTP协议和以JSON格式交换的数据集成系统的其他部分。该系统的设计使要求最高的计算部分可以并行计算,并且计算可以分布到远程计算资源。在捷克NGI CESNET提供的科学云上进行了测试部署。在云计算资源上,复杂模型的参数识别速度显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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