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Computing Network Flow on a Multiple Processor Pipeline
June 1994 (vol. 5 no. 6)
pp. 653-658

We demonstrate the feasibility of a distributed implementation of the Goldberg-Tarjan algorithm for finding the maximum flow in a network. Unlike other parallel implementations of this algorithm, where the network graph is partitioned among many processors, we partition the algorithm among processors arranged in a pipeline. The network graph data are distributed among the processors according to local requirements. The partitioned algorithm is implemented on six processors within a 15-processor pipelined message-passing multicomputer operating at 5 MHz. We used randomly generated networks with integer capacities as examples. Performance estimates based upon a six-processor pipelined implementation indicated a speedup between 3.8 and 5.9 over a single processor.

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Index Terms:
Index Termspipeline processing; distributed algorithms; graph theory; network flow; multiple processor pipeline; maximum flow; Goldberg-Tarjan algorithm; parallel implementations; network graph; partitioned algorithm; six processors; message-passing multicomputer; performance estimates
Citation:
P. Agrawal, A. Ng, "Computing Network Flow on a Multiple Processor Pipeline," IEEE Transactions on Parallel and Distributed Systems, vol. 5, no. 6, pp. 653-658, June 1994, doi:10.1109/71.285611
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