Chapter Five - A runtime job scheduling algorithm for cluster architectures with dataflow accelerators.

This article discusses specialized computer cluster architectures for high performance computing that include both control-flow and DataFlow components, as well as their runtime scheduling algorithms. A novel optimal scheduling algorithm for such architectures is proposed. The proposed algorithm is general, but is limited in some cases due to its time complexity. From the base optimal algorithm, two additional heuristic algorithms are derived, and then compared to other schedulers. These heuristic algorithms produce near-optimal schedules for both DataFlow hardware jobs and control-flow jobs at large job counts, with negligible scheduling penalty. Compared to an optimal scheduler, the performance gain decreases slightly as job count increases. This research illustrates that the performance of existing cluster structures can be considerably improved by adding appropriate DataFlow accelerators and a proper scheduling algorithm, while at the same time decreasing the system transistor count and power consumption.