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An external-memory depth-first search algorithm for general grid graphs

机译:通用网格图的外部存储器深度优先搜索算法

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摘要

Graph data in modern scientific and engineering applications are often too large to fit in the computer’s main memory. Input/output (I/O) complexity is a major research issue in this context. Minimization of the number of I/O operations (in external memory graph algorithms) is the main focus of current research while classical (internal memory) graph algorithms were designed to minimize temporal complexity.In this paper, we propose an external memory depth first search algorithm for general grid graphs. The I/O-complexity of the algorithm isO(sort(N)log_2N/M) , where N=|V|+|E|,sort(N)=θ(N/B long_M/B M/B) is the sorting I/O-complexity, M is the memory size, and B is the block size. The best known algorithm for this class of graph is the standard (internal memory) DFS algorithm with appropriate block (sub-grid) I/O-access. Its I/O-complexity is O(N/B). Recently, the authors proposed an (sort(N))Oalgorithm for solid grid graphs
机译:现代科学和工程应用中的图形数据通常太大而无法容纳在计算机的主存储器中。在这种情况下,输入/输出(I / O)的复杂性是一个主要的研究问题。 I / O操作数量的减少(在外部存储器图算法中)是当前研究的重点,而经典(内部存储器)图算法的设计是为了最大限度地减少时间复杂度。本文提出了外部存储器深度优先搜索一般网格图的算法。算法的I / O复杂度为O(sort(N)log_2N / M),其中N = | V | + | E |,sort(N)=θ(N / B long_M / BM / B)是排序I / O复杂度,M是内存大小,B是块大小。此类图形的最著名算法是具有适当块(子网格)I / O访问的标准(内部存储器)DFS算法。其I / O复杂度为O(N / B)。最近,作者提出了用于固体网格图的(sort(N))算法

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