一种优化的前瞻处理器,用于精简搜索空间

J. Gu
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引用次数: 3

摘要

离散松弛算法(DRA)是一种有效的求解一致标注问题(CLP)中弧一致性(AC)的计算方法。对于n个对象和m个标签的问题,原始的顺序AC-1算法的时间复杂度为O(n/sup 3/m/sup 3/)。运行的示例问题表明,所有这些顺序算法都太慢,无法满足任何有用的实时CLP应用程序的需要。给出了并行AC算法(其中处理器数量是问题大小的多项式)的最优下界O(nm)的最优并行DRA5算法。该算法已在一个细粒度、大规模并行的硬件计算机体系结构上实现。对于实际问题,在这种硬件架构上可以达到4到10个数量级的效率改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An optimal lookahead processor to prune search space
The discrete relaxation algorithm (DRA) is an efficient computational technique for enforcing arc consistency (AC) in a consistent labeling problem (CLP). The original sequential AC-1 algorithm suffers from O(n/sup 3/m/sup 3/) time complexity for an n-object and m-label problem. Sample problem runs show that all these sequential algorithms are too slow to meet the need for any useful real-time CLP applications. An optimal parallel DRA5 algorithm that reaches the optimal lower bound, O(nm), for parallel AC algorithms (where the number of processors is polynomial in the problem size) is given. The algorithm has been implemented on a fine-grained, massively parallel hardware computer architecture. For problems of practical interest, 4 to 10 orders of magnitude of efficiency improvement can be reached on this hardware architecture.<>
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