Authors: Sanjeev Baskiyar Rabab AbdelKader
Publish Date: 2010/01/29
Volume: 13, Issue: 4, Pages: 373-383
Abstract
We address the problem of scheduling directed acyclic task graph DAG on a heterogeneous distributed processor system with the twin objectives of minimizing finish time and energy consumption Previous scheduling heuristics have assigned DAGs to processors to minimize overall runtime of the application But applications on embedded systems such as high performance DSP in image processing multimedia and wireless security need schedules which use low energy tooWe develop a new scheduling algorithm called Energy Aware DAG Scheduling EADAGS on heterogeneous processors that can run on discrete operating voltages Such processors can scale down their voltages and slow down to reduce energy whenever they idle due to task dependencies EADAGS combines dynamic voltage scaling DVS with Decisive Path Scheduling DPS to achieve the twin objectives Using simulations we show average energy consumption reduction over DPS by 40 Energy savings increased with increasing number of nodes or increasing Communication to Computation Ratios and decreased with increasing parallelism or increasing number of available processors These results were based on a software simulation study over a large set of randomly generated graphs as well as graphs for realworld problems with various characteristics
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