Abstract
In massively parallel systems, the performance gains are often significantly diminished by the inherent communication overhead. This overhead is caused by the required message passing resulting from the task allocation scheme. In this paper, techniques to reduce this communication overhead by both scheduling the communication and determining the routing that the messages should take within a tightly-coupled processor network are presented. Using the recently developed Collision Graph model, static scheduling algorithms are derived which work at compile-time to determine the ordering and routing of the individual message transmissions. Since a priori knowledge about the network traffic required by static scheduling may not be available or accurate, this work also considers dynamic scheduling. A novel hybrid technique is presented which operates in a dynamic environment yet uses known information obtained by analyzing the communication patterns. Experiments performed show significant improvement over baseline techniques.
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