期刊
IEEE TRANSACTIONS ON COMPUTERS
卷 70, 期 9, 页码 1472-1483出版社
IEEE COMPUTER SOC
DOI: 10.1109/TC.2020.3012987
关键词
Games; Graphics processing units; Central Processing Unit; Smart phones; Computer architecture; Hardware; Rendering (computer graphics); Mobile games; smartphone; big; LITTLE architecture; power management; DVFS
资金
- Shenzhen Science and Technology Innovation Committee (SZSTI) [JCYJ20170818090006804]
Mobile games are increasingly demanding in computational complexity, leading to rapid battery drain of integrated CPUs and GPUs, hindering user experience improvement. By introducing a CPU-GPU governing framework that recognizes performance demand and selects the most energy-efficient hardware configuration for different game scenes, significant power savings can be achieved without compromising user experience.
Games have been one of the most popular applications on smartphones. In order to meet the increasing computational complexity of mobile games, smartphones are now equipped with heterogeneous CPU multi-core architectures like big.LITTLE as well as high-performance GPUs. However, the integrated CPUs and GPUs drain the battery quickly, which has become a bottleneck for improving user experience. In addition to traditional Dynamic Voltage and Frequency Scaling (DVFS) technique for CPUs and GPUs power reduction, heterogeneous multi-core processors, such as the big.LITTLE architecture, have been designed to offer more opportunity for performance-energy tradeoffs. But current processor governors in smartphones can not exploit these power-saving mechanisms wisely, causing considerable energy waste. In this article, we propose a CPU-GPU governing framework that recognizes the performance demand for different game scenes, and select the most energy-efficient hardware configuration for the corresponding scenes. We implement our framework on an ODROID-XU4 mobile platform, and the experiments show that our framework can achieve 26.7, 16.6, and 10.5 percent power saving on average without compromising user experience when compared to the default governor used in our platform and two governors proposed by other researchers, respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据