Analysis of macro-dataflow dynamic scheduling on nonuniform memory access architectures

The author studies dynamic scheduling of computational tasks with communication costs using nonuniform memory access architecture. The computing model assumes that data transfer can be partitioned into parallel and sequential parts with respect to the task execution. A scheduling heuristic, called least-communication (LC), together with a two-level scheduler is proposed in an attempt to minimize the finish time. The LC selects the task that removes the largest amount of remaining data transfer, if no such tasks are available the task that has been ready to run at the earliest is selected first. The time complexity of LC is O(n₂). Testing the finish time of LC and first-come first-served scheduling (FCFS) shows that LC is useful for tasks having moderate granularity and whose computation and communication requirements vary widely for different data sets