Energy consumption constraints on computing systems are more important than ever. Maintenance costs for high performance systems are limiting the applicability of processing devices with large dissipation power. New solutions are needed to increase both the computation capability and the power efficiency. Moreover, energy efficient applications should balance performance vs. consumption. Therefore power data of components are important. This work presents the most remarkable alternatives to measure the power consumption of different types of computing systems, describing the advantages and limitations of available power measurement systems. Finally, a methodology is proposed to select the right power consumption measurement system taking into account precision of the measure, scalability and controllability of the acquisition system.
This paper analyses the power consumption of hybrid computation on embedded architectures with an available GPU. Novel efficiency metrics are obtained using a well-known benchmark process based on the Fourier transform as computing work load. The measurement process is arranged in order to obtain specific power data for each hardware configuration, varying the data size and number of computation threads, disabling the GPU, mixing the power computation of CPU/GPU, etc. The resulting data may be of interest for new applications and cluster development (i.e. Beowulf clusters) based on low power devices, such as the Beobot project.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.