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Asynchronous Optimization Techniques for Distributed Computing Applications

机译:分布式计算应用的异步优化技术

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Simulation-based optimization of manufacturing systems has emerged into a widely accepted decision support technique for industrial applications. Due to the computational complexity of these applications, simulation-based optimization is typically implemented in software systems that make use of distributed computing-units in order to reach an acceptable performance. However, even then dynamical methods, i.e. methods that are not bound to a fixed number of iterations are desired in order to further increase the performance of the optimization process. This paper addresses possibilities for employing population-based optimization techniques in an asynchronous way in order to react to computational node failures, limited computing resources and unbalanced simulation times. We demonstrate our approach by applying it to the optimization of set-up parameters for virtual tooling machines within an underlying research project of the leading edge cluster 'ITS OWL - intelligent technical systems'.
机译:基于仿真的制造系统优化已出现为工业应用的广泛接受的决策支持技术。由于这些应用的计算复杂性,基于仿真的优化通常在利用分布式计算单元的软件系统中实现,以达到可接受的性能。然而,即使是动态方法,即不得绑定到固定数量的迭代的方法,以进一步提高优化过程的性能。本文解决了以异步方式使用基于人口的优化技术的可能性,以便对计算节点故障,有限的计算资源和不平衡模拟时间作出反应。我们通过将虚拟工具机的优化优化在领先的边缘集群“其猫头鹰 - 智能技术系统”的基础研究项目中优化虚拟工具机的设置参数来展示我们的方法。

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