Energy-aware Partial-Duplication Task Mapping under Real-Time and Reliability Constraints
Minyu Cui, Lei Mo, Angeliki Kritikakou and Emmanuel Casseau
An efficient task execution on multicore platforms can lead to low energy consumption. To achieve that, an Integer Non-Linear Programming (INLP) formulation is proposed that performs task mapping by jointly addressing task allocation, task frequency assignment, and task duplication. The goal is to minimize energy consumption under real-time and reliability constraints. To provide an optimal solution, the original INLP problem is safely transformed to an equivalent Mixed Integer Linear Programming (MILP) problem. The comparison of the proposed approach with existing energy-aware task mapping approaches shows that the proposed approach is able to find solutions when other approaches fail, achieving an overall lower energy consumption.
