Associative Processing of Network Flow Problems

Application of associative processors to the solution of the maximal flow problem is investigated. To take maximum advantage of the capability of associative processors, a new algorithm based on matrix representation is developed. The new algorithm is then compared with the associative version of the Ford and Fulkerson labeling method. The comparison is made on the total associative memory access time required for problem solution by each algorithm running on an associate processor. Results show that the ratio of the labeling algorithm to the new algorithm is about 3 for a dense network with 5 nodes. This ratio increases as the number of nodes increases, and decreases as the density of the network decreases.