Abstract-Power-aware execution of parallel programs is now a primary concern in large-scale HPC environments. Prior research in this area has explored models and algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic concurrency throttling (DCT) to achieve power-aware execution of programs written in a single programming model, typically MPI or OpenMP. However, hybrid programming models combining MPI and OpenMP are growing in popularity as emerging large-scale systems have many nodes with several processors per node and multiple cores per processor. In this paper we present and evaluate solutions for power-efficient execution of programs written in this hybrid model targeting large-scale distributed systems with multicore nodes. We use a new power-aware performance prediction model of hybrid MPI/OpenMP applications to derive a novel algorithm for power-efficient execution of realistic applications from the ASC Sequoia and NPB MZ benchmarks. Our new algorithm yields substantial energy savings (4.18% on average and up to 13.8%) with either negligible performance loss or performance gain (up to 7.2%).

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Chinese government promotes ecological civilization in the-13 th five year planning‖ (2016-2020) period. As a result, ecological impacts become highlight in the national circular economy practices. To apply the eco-industrial development strategy to address the intertwined industrial and regional economic development, as well as related environmental and ecological challenges is key point. Urban industrial symbiosis provides a novel approach to realize the above expectation. Traditional evaluation on circular economy provided critical environmental insights, while to date, trade-offs of circular economy practices, and critical insights on regional eco-industrial development. It will shed a light on ecological civilization construction in China in the new national planning period.