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Imprecise computations provide an avenue for scheduling algorithms developedfor energy-constrained computing devices by trading off output quality with theutilization of system resources. This work proposes a method for schedulingtask graphs with potentially imprecise computations, with the goal ofmaximizing the quality of service subject to a hard deadline and an energybound. Furthermore, for evaluating the efficacy of the proposed method, a mixedinteger linear program formulation of the problem, which provides the optimalreference scheduling solutions, is also presented. The effect of potentiallyimprecise inputs of tasks on their output quality is taken into account in theproposed method. Both the proposed method and MILP formulation targetmultiprocessor platforms. Experiments are run on 10 randomly generated taskgraphs. Based on the obtained results, for some cases, a feasible schedule of atask graph can be achieved with the energy consumption less than 50% of theminimum energy required for scheduling all tasks in that task graph completelyprecisely.

Energy-Aware Scheduling of Task Graphs with Imprecise Computations and End-to-End Deadlines