Abstract:
Duplication and dynamic voltage/frequency scaling (DVFS) creates an interesting trade-off for scheduling task
graphs on multiprocessors to improve energy consumption and
schedule length (or makespan). With DVFS, tasks are made to
run on low voltages, which decreases their computation power.
However, it also increases their execution costs and hence, may
increase the schedule length. Furthermore, applying DVFS on
processors does not impact the communication delay/energy
consumption. Duplicating a task on multiple processors reduces
the communication delay among them, which further reduces
the schedule length. Although duplication reduces the communication energy among processors, it also increases the overall
computation energy. In this paper, we explore this trade-off
between duplication and DVFS, and propose a polynomial time
heuristic to schedule task graphs on heterogeneous multiprocessors. The tasks are carefully duplicated with DVFS to reduce
its impact on the computation energy. The results demonstrate
that the proposed algorithm is able to effectively balance the
makespan and energy consumption over other algorithms in
various scenarios
