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Data flow graph partitioning to reduce communication cost

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Published:01 December 1986Publication History
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Abstract

This paper presents a cost-effective scheme for partitioning large data flow graphs. Standard data flow machine architectures are assumed in this work. The objective is to reduce the overhead due to token transfers through the communication network of the machine. When this scheme is employed on large graphs, the load distribution on the rings of the data flow machine is also improved. A canonical form of a data flow graph is introduced to establish the relationship between the communication overhead and the size reduction of the partition cut-set. General lower estimates on the overhead are derived in terms of processing and transmission delay parameters of the machine. The method uses heuristics and an evaluation function to guide the partition algorithm. Some implications of the proposed method on the organization of the data flow machines are discussed.

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                  cover image ACM SIGMICRO Newsletter
                  ACM SIGMICRO Newsletter  Volume 17, Issue 4
                  Dec. 1986
                  163 pages
                  ISSN:1050-916X
                  DOI:10.1145/19530
                  Issue’s Table of Contents
                  • cover image ACM Conferences
                    MICRO 19: Proceedings of the 19th annual workshop on Microprogramming
                    December 1986
                    179 pages
                    ISBN:081860736X
                    DOI:10.1145/19551

                  Copyright © 1986 Authors

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                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 1 December 1986

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