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A task-based approach to parallel parametric linear programming solving, and application to polyhedral computations

机译:基于任务的并行参数线性编程解决方法以及应用于多面体计算的方法

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摘要

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications. Here, we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems. This type of parallel applications is challenging, because several tasks might be computing the same region. In this article, we are presenting the algorithm itself with a parallel redundancy elimination algorithm, and conducting a thorough performance analysis.
机译:参数线性编程是多面体计算的中央操作,以及某些控制应用。在这里,我们提出了一种基于任务的方案,用于并行化它,在大问题上具有准线性加速。这种类型的并行应用是具有挑战性的,因为若干任务可能是计算相同的区域。在本文中,我们通过并行冗余消除算法呈现算法本身,并进行彻底的性能分析。

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