On the energy-aware partitioning of real-time tasks on homogeneous multi-processor systems

In high-performance computing systems, efficient energy management is a key feature for keeping energy bills low and avoiding thermal dissipation problems, as well as for controlling the application performance. This paper considers the problem of partitioning and scheduling a set of real-time tasks on a realistic hardware platform consisting of a number of homogeneous processors. Several well-known heuristics are compared to identify the approach that better reduces the overall energy consumption of the entire system. Despite the actual state of art, the approach which minimizes the number of active cores is the most energy efficient.