Benchmarking RenderScript: Potential for Energy Efficient Multi-Core Mobile Devices

被引:0
|
作者
Ju, Qianao [1 ]
Chen, Shang-Tse [1 ]
Zhang, Ying [1 ]
机构
[1] Georgia Inst Technol Atlanta, Atlanta, GA 30332 USA
关键词
smart city; mobile heterogeneous computing; RenderScript; energy efficiency;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multi-core System On Chips (SoCs) are playing a predominating role in smart phones and tablets. Unlike traditional multi-core desktops, mobile devices are restricted by the limited energy the batteries can buffer. It remains unclear whether it is energy efficient to adopt heterogeneous computing in multi-core mobile devices. In this paper, we evaluate mobile heterogeneous computing by benchmarking RenderScript, a high performance computing framework in Android system, using 6 selected benchmarks in the area of linear algebra, machine learning and image processing. For each benchmark, both the original version and the RenderScript heterogeneous version are implemented for the performance comparison. We make a thorough study of the performance in terms of computation speedup and power consumption on two smart phone platforms. Our results demonstrate that, compared with original implementation, the increase of computation speed ranges from 2 to 18 by using RenderScript while the power consumption overhead is capped by 75%. By adopting heterogeneous computing, the total energy required for executing the applications can be significantly reduced. Based on the benchmarking results, the potential for improving energy efficiency of multi-core mobile devices is discussed.
引用
收藏
页码:25 / 30
页数:6
相关论文
共 50 条
  • [21] An Extensible Infrastructure for Benchmarking Multi-Core Processors based Systems
    Jamal, M. Hasan
    Mustafa, Ghulam
    Waheed, Abdul
    Mahmood, Waqar
    PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON PERFORMANCE EVALUATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS, 2009, 41 (04): : 13 - 20
  • [22] Enhancing Energy Efficiency of Multimedia Applications in Heterogeneous Mobile Multi-Core Processors
    Kim, Young Geun
    Kim, Minyong
    Chung, Sung Woo
    IEEE TRANSACTIONS ON COMPUTERS, 2017, 66 (11) : 1878 - 1889
  • [23] An Energy-efficient Frame-based Task Scheduling Algorithm for Heterogeneous Multi-core SoC in IoT Devices
    Yang, Yi
    Diao, Weimin
    2020 16TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC, 2020, : 1404 - 1409
  • [24] Energy-efficient task scheduling for multi-core platforms with per-core DVFS
    Lin, Ching-Chi
    Syu, You-Cheng
    Chang, Chao-Jui
    Wu, Jan-Jan
    Liu, Pangfeng
    Cheng, Po-Wen
    Hsu, Wei-Te
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2015, 86 : 71 - 81
  • [25] Special issue on energy efficient multi-core and many-core systems, Part I
    Rahmani, Amir M.
    Liljeberg, Pasi
    Ayala, Jose L.
    Tenhunen, Hannu
    Veidenbaum, Alexander V.
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2016, 95 : 1 - 2
  • [26] Special issue on energy efficient multi-core and many-core systems, Part II
    Rahmani, Amir M.
    Liljeberg, Pasi
    Ayala, Jose L.
    Tenhunen, Hannu
    Veidenbaum, Alexander V.
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2017, 100 : 128 - 129
  • [27] Hybridization of Metaheuristics Based Energy Efficient Scheduling Algorithm for Multi-Core Systems
    Justus, J. Jean
    Sakthi, U.
    Priyadarshini, K.
    Thiyaneswaran, B.
    Alajmi, Masoud
    Obayya, Marwa
    Hamza, Manar Ahmed
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2023, 44 (01): : 205 - 219
  • [28] Fairness-Aware Energy Efficient Scheduling on Heterogeneous Multi-Core Processors
    Salami, Bagher
    Noori, Hamid
    Naghibzadeh, Mahmoud
    IEEE TRANSACTIONS ON COMPUTERS, 2021, 70 (01) : 72 - 82
  • [29] PEPS: predictive energy-efficient parallel scheduler for multi-core processors
    Maghsoud, Zeinab
    Noori, Hamid
    Pour Mozaffari, Saadat
    JOURNAL OF SUPERCOMPUTING, 2021, 77 (07): : 6566 - 6585
  • [30] Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors
    Lee, Sungju
    Kim, Heegon
    Chung, Yongwha
    Park, Daihee
    SENSORS, 2012, 12 (11) : 14647 - 14670