Abstract
With the increasing diversity of demands, heterogeneous multi-core systems have become a popular architecture. One of the representative systems is the big.LITTLE technology, which combines high-performance big cores with the energy efficient little cores to achieve both high performance and low power. For such system, although people believe the most energy efficient way to execute tasks is scheduling them on little cores, the overlooked idle power consumption of big cores could overwhelm this simple energy saving strategy. In this thesis, we propose an efficient scheduling algorithm to minimize the energy consumption of the big.LITTLE heterogeneous multi-core systems. We first build an integer linear programming model that minimize the total energy, and solve it using Matlab. From the optimal solutions we observe their properties, base on which, we derive an algorithm using the longest time first heuristic and the local search approach. We implemented and tested our model and algorithm on an ODROID-XU3 development board, which consisting of four small in-order Cortex-A7 and four big out-of-order Cortex-A15 cores. The experimental results show that for the total energy consumption, the differences between the results obtained by our scheduling algorithm and the optimal solution are within 1\% on the average for various workloads. But our algorithm is much more efficient than solving the integer linear programming model.