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Non-Linear Constrained GRG Optimisation under Parallel-Distributed Computing Environments

机译:并行分布式计算环境下的非线性约束GRG优化

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摘要

We have designed and implemented a parallel version of the Generalised Reduced Gradient optimisation method (GRG), especially devised for efficient processing on heterogeneous NOWs. The core parallel routines deal with simultaneous constraint evaluation and the calculation of gradients for both the objective function and the constraints. A hybrid model for task scheduling that minimises idle time and considers the heterogeneous nature of the processors was proposed. As to performance comparisons, a modified speed-up metric that takes into account heterogeneity was employed. Significant time improvements were obtained for both academic and industrial examples corresponding to process-plant units. The best results were attained for large-scale problems or when the functions to be evaluated were costly.
机译:我们已经设计并实现了广义缩减梯度优化方法(GRG)的并行版本,特别设计用于对异构NOW进行有效处理。核心并行例程处理同时的约束评估以及目标函数和约束的梯度计算。提出了一种用于任务调度的混合模型,该模型可最大程度地减少空闲时间并考虑处理器的异构性质。关于性能比较,采用了考虑异质性的改进的加速指标。对于与过程工厂单元相对应的学术和工业实例,均获得了显着的时间改进。对于大规模问题或要评估的功能成本高昂时,可获得最佳结果。

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