Data Flow Graph Partitioning Schemes

The ordering of operations in a data flow program is not specified by the programmer, but is implied by the data dependencies. This advantage can be exploited further on multiprocessor architectures by grouping the nodes in the corresponding data flow graph and allocating these groups efficiently to processors. This paper presents and compares some of the numerous heuristic approaches that were proposed to partition data flow graphs and assign them to different processors. The processor allocation algorithms, which do not consider the communication cost between processors, are presented initially. A Region analysis algorithm that enables better load balancing but again does not consider communication cost is presented. Schauser et. al. developed an intermediate data structure “dual graph” to transition a data flow graph into threads which easily compiled and mapped on Threaded Abstract Machine. Lastly, algorithms, which consider these costs, are studied. We present a design pattern that can be summarized from these algorithms to efficiently partition data flow graphs. We also list the key issues that need to be addressed during data flow partitioning. Abstract: .................................................................................................................................................................. 1