Abstract
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.
Highlights
With growing concerns about the carbon footprint of computers – computers currently produce 2–3% of greenhouse gas emissions related to human activities – there is ever greater interest in power conservation and efficient use of computational resources
We review related work in Section 2; to better motivate our work, in Section 3, we take two frequency scaling technologies as examples to illustrate the effect of these technologies on energy consumption; Section 4 presents our DREAMMCP model for multicore resource management and energy analysis; results from our experimental involving two problems with different characteristics are presented in Section 5; Section 6 concludes the paper
5 Experimental results A prototype of DREAM-MCP has been implemented for multicore processor resource management and energy consumption analysis
Summary
With growing concerns about the carbon footprint of computers – computers currently produce 2–3% of greenhouse gas emissions related to human activities – there is ever greater interest in power conservation and efficient use of computational resources. The relationship between a processor’s speed and its power requirement emerged as a significant concern: the dynamic power required by a CMOS-based processor is proportional to the product of its operating voltage and clock frequency; and for these processors, the operating voltage is proportional to its clock frequency. The dynamic power consumed by a CMOS processor is (typically) proportional to the cube of its frequency [1]. This motivated the general shift away from faster processors to multicore processors for delivering the more processor cycles to applications with ever increasing demands. Dynamic voltage and frequency scaling (DVFS) can be used to deliver only the required amount of speed for such computations
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