Scheduling directed task graphs on multiprocessors using simulated annealing

Two algorithms based on simulated annealing for minimizing the schedule length of a directed task graph on a multiprocessor system are presented. The first algorithm uses the schedule length itself as the cost function to be minimized. The second algorithm uses an indirect cost function that minimizes the total communication overhead and the total loss of parallelism simultaneously. Implementation results indicate that the first algorithm is superior to the second one in terms of the schedule length it gives, but the second algorithm is superior to the first in terms of algorithm run time