Energy-aware thread co-location in heterogeneous multicore processors

Given the wide variety of performance demands for various workloads, the trend in embedded systems is shifting from homogeneous to heterogeneous processors, which have been shown to yield performance and energy saving benefits. A typical heterogeneous processor has cores with different performance and power characteristics, that is, high performance and power hungry (“big”) cores, and low power and performance (“small”) cores. In order to satisfy the memory bandwidth and computation demands of various threads, it is important (albeit challenging) to map threads to cores. Such assignment should take into account that threads could potentially be harmful to each other in the usage of shared resources (e.g., cache, memory). We propose a scheme for dynamic energy-efficient assignment of threads to big/small cores, DIO-E (Distributed Intensity Online-Energy), which is an enhancement of the previously proposed DIO. In contrast to DIO, we take into account both CPU and memory demands of threads to characterize the performance of threads when co-running on the same core at run-time. Our results show that DIO-E improves the energy-delay-squared product (ED
²
) by 9% (average) over DIO, running on a performance-asymmetric multicore system. Both DIO and DIO-E show about 50% improvement in ED
²
over a state-of-the-art solution.