With the growing ubiquity of computer systems, the energy consumption of these systems is of increasing concern. Multicore architectures offer a potential opportunity for energy conservation by allowing cores to operate at lower frequencies when the processor demand low. Until recently, this has meant operating all cores at the same frequency, and research on analyzing power consumption of multicores has assumed that all cores run at the same frequency. However, emerging technologies such as fast voltage scaling and Turbo Boost promise to allow cores on a chip to operate at different frequencies. This paper presents an energy-aware resource management model, DREAM-MCP, which provides a flexible way to analyze energy consumption of multicores operating at non-uniform frequencies. This information can then be used to generate a fine-grained energy-efficient schedule for execution of the computations – as well as a schedule of frequency changes on a per-core basis – while satisfying performance requirements of computations. To evaluate our approach, we have carried out two case studies, one involving a problem with static workload (Gravitational N-Body Problem), and another involving a problem with dynamic workload (Adaptive Quadrature). Experimental results show that for both problems, the energy savings achieved using this approach far outweigh the energy consumed in the reasoning required for generating the schedules.
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