Optimal communication scheduling based on collision graph model

While research on the static scheduling of computational tasks for parallel systems has been ongoing for years, most work does not consider the communication costs nor does it consider the network congestion. A new static scheduling technique is presented which focuses on the communication overhead inherent in parallel processing systems. This paper builds a framework based on a newly developed graph model called a collision graph to study this problem. Using this model, algorithms are developed which can be embedded into existing static scheduling methods to improve their performance. The scheduling of cyclic data flow graphs was shown to be improved significantly as this technique was applied to the cyclo-compaction scheduling algorithm.