The rapidly growing computing systems, such as AI server cluster, IoT devices etc. are facing increasing energy expenditure pressure and the warning of carbon footprint. Designing eco-friendly computing systems which integrated renewable energy sources have attracted considerable attentions recently. Existing schemes either incur green energy efficiency degradation or sacrifice workload performance. This paper proposes REcache (Renewable Energy cache), a sustainable energy management scheme to efficiently utilize green energy for computing systems. Compared to previous proposals, we present a dedicated circuit and energy-aware management policies to coordinate energy harvesting, power management and workload scheduling. We evaluate our scheme through both prototyping and simulation. The experimental results show that the REcache could effectively improve the energy availability 10%, workload performance 5% for different workloads on average.
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REcache: Efficient Sustainable Energy Management Circuits and Policies for Computing Systems
Semantic Scholar · Computer Science · 2019
Abstract
The rapidly growing computing systems, such as AI server cluster, IoT devices etc. are facing increasing energy expenditure pressure and the warning of carbon footprint. Designing eco-friendly computing systems which integrated renewable energy sources have attracted considerable attentions recently. Existing schemes either incur green energy efficiency degradation or sacrifice workload performance. This paper proposes REcache (Renewable Energy cache), a sustainable energy management scheme to efficiently utilize green energy for computing systems. Compared to previous proposals, we present a dedicated circuit and energy-aware management policies to coordinate energy harvesting, power management and workload scheduling. We evaluate our scheme through both prototyping and simulation. The experimental results show that the REcache could effectively improve the energy availability 10%, workload performance 5% for different workloads on average.