The current trend to move from homogeneous to heterogeneous multi-core systems promises further performance and energy-efficiency benefits. A typical future heterogeneous multi-core system includes two distinct types of cores, such as high performance sophisticated (``large'') cores and simple low-power (``small'') cores. In those heterogeneous platforms, execution phases of application threads that are CPU-intensive can take best advantage of large cores, whereas I/O or memory intensive execution phases are best suited and assigned to small cores. However, it is crucial that the assignment of threads to cores satisfy both the computational and memory bandwidth constraints of the threads. We propose an optimization approach to determine and apply the most energy efficient assignment of threads with soft real-time performance and memory bandwidth constraints in a multi-core system. Our approach includes an ILP (Integer Linear Programming) optimization model and a scheme to dynamically change thread-to-core assignment, since thread execution phases may change over time. In comparison to state-of-art dynamic thread assignment schemes, we show energy savings and performance gains for a variety of workloads, while respecting thread performance and memory bandwidth requirements.
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