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A cellular array is a two-dimensional, checkerboard type interconnection of identical modules (or cells), where each cell contains a few hits of memory and a small amount of combinational logic, and communicates mainly with its immediate neighbors In the array. The chief computational advantage offered by cellular arrays is the improvement in speed achieved by virtue of the possibilities for parallel processing. In this paper it is shown that cellular arrays are inherently well suited for the solution of many graph problems. For example, the adjacency matrix of a graph is easily mapped onto an array; each matrix element is stored in one cell of the array, and typical row and column operations are readily implemented by simple cell logic. A major challenge in the effective use of cellular arrays for the solution of graph problems is the determination of algorithms that exploit the possibilities for parallelism, especially for problems whose solutions appear to be inherently serial. In particular, several parallelized algorithms are presented for the solution of certain spanning tree, distance, and path problems, with direct applications to wire routing, PERT chart analysis, and the analysis of many types of networks. These algorithms exhibit a computation time that in many cases grows at a rate not exceeding log2, n, where n is the number of nodes in the graph. Straight. forward cellular implementations of the well-known serial algorithms for these problems require about n steps, and noncellular implementations require from n2 to n3 steps. [ABSTRACT FROM AUTHOR]

Presents an algorithm for finding blocks and cutnodes of an arbitrary undirected graph. Representation of the graph as an ordered list of edges or as a packed adjacency matrix; Development of a spanning tree with labeled edges with two edges bearing different labels if and only if they belong to different blocks; Derivation of values of gamma for each test graphs generated by an extension of the web grammar approach.