并行分配算法在超立方体计算机上的实现与性能分析

BarryK. Carpenter, IV NathanielJ.Davis
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引用次数: 3

摘要

在军事交战中有效协调和控制资源的过程被称为战斗管理/指挥、控制和通信(BM/C3)。BM/C3的一项关键任务是分配武器摧毁目标。本研究的重点是发展并行计算方法,以实现快速和经济有效的武器分配目标。本文以求解分配问题的顺序匈牙利方法为基础,介绍了在Intel iPSC超立方体计算机上实现的四种并行分配方法的发展和相对性能比较。前三种方法是最优分配解的近似。这些方法的优点是计算速度快,并且已被证明可以生成在成本方面非常接近最佳分配的分配。第四种方法是匈牙利算法的并行实现,其中并行执行某些子任务。与前三种方法产生的次优分配相比,这种方法产生了最优分配。通过改变武器和目标的数量、使用的处理器数量和问题分区的大小来比较这四种方法的相对性能。
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Implementation and performance analysis of parallel assignment algorithms on a hypercube computer
The process of effectively coordinating and controlling resources during a military engagement is known as battle management/command, control, and communications (BM/C3). One key task of BM/C3 is allocating weapons to destroy targets. The focus of this research is on developing parallel computation methods to achieve fast and cost effective assignment of weapons to targets. Using the sequential Hungarian method for solving the assignment problem as a basis, this paper presents the development and the relative performance comparison of four parallel assignment methodologies that have been implemented on the Intel iPSC hypercube computer. The first three approaches are approximations to the optimal assignment solution. The advantage to these is that they are computationally fast and have proven to generate assignments that are very close the optimal assignment in terms of cost. The fourth approach is a parallel implementation of the Hungarian algorithm, where certain subtasks are performed in parallel. This approach produces an optimal assignment as compared to the sub-optimal assignments that result from the first three approaches. The relative performance of the four approaches is compared by varying the number of weapons and targets, the number of processors used, and the size of the problem partitions.
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