A task duplication based scheduling algorithm using partial schedules

We propose a novel replication-based two-phase scheduling algorithm designed to achieve DAG scheduling with small makespans and high efficiency. In the first phase, the schedule length of the application is minimized using a novel approach that utilizes partial schedules. In the second phase, the number of processors required is minimized by eliminating and merging these partial schedules. Experimental results on random DAGs show that the makespans generated by the proposed algorithm are slightly better than those generated by the well known CPFD algorithm whereas the number of processors used is less than half of what is needed by CPFD solutions.