Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

By scheduling multiple applications with complementary resource requirements on a smaller number of compute nodes, we aim to improve performance, resource utilization, energy consumption, and energy efficiency simultaneously. In addition to our naive consolidation approach, which already achieves the aforementioned goals, we propose a new energy efficiency-aware (EEA) scheduling policy and compare its performance with current state-of-the-art policies, namely round-robin (RR), resource utilization-aware (RUA), adaptive shortest-job first (ASJF) in order to support the consolidation of applications in heterogeneous computing systems, and in turn, simultaneously improve performance, resource utilization, energy consumption, and energy efficiency, as measured by the energy-delay product. Of particular note, our experimental results on a real heterogeneous computing system demonstrate the efficacy of our scheduling policies by improving overall energy efficiency by an order of magnitude.