Managing GPU Buffers for Caching More Apps in Mobile Systems

被引:0
|
作者
Kwon, Sejun [1 ]
Kim, Sang-Hoon [2 ]
Kim, Jin-Soo [1 ]
Jeong, Jinkyu [1 ]
机构
[1] Sungkyunkwan Univ, Seoul, South Korea
[2] Korea Adv Inst Sci & Technol, Daejeon, South Korea
关键词
MEMORY;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Modern mobile systems cache apps actively to quickly respond to a user's call to launch apps. Since the amount of usable memory is critical to the number of cacheable apps, it is important to maximize memory utilization. Meanwhile, modern mobile apps make use of graphics processing units (GPUs) to accelerate their graphic operations and to provide better user experience. In resource-constrained mobile systems, GPU cannot afford its private memory but shares the main memory with CPU. It leads to a considerable amount of main memory to be allocated for GPU buffers which are used for processing GPU operations. These GPU buffers are, however, not managed effectively so that inactive GPU buffers occupy a large fraction of the memory and decrease memory utilization. This paper proposes a scheme to manage GPU buffers to increase the memory utilization in mobile systems. Our scheme identifies inactive GPU buffers by exploiting the state of an app from a user's perspective, and reduces their memory footprint by compressing them. Our sophisticated design approach prevents GPU-specific issues from causing an unpleasant overhead. Our evaluation on a running prototype with realistic workloads shows that the proposed scheme can secure up to 215.9 MB of extra memory from 1.5 GB of main memory and increase the average number of cached apps by up to 31.3%.
引用
收藏
页码:207 / 216
页数:10
相关论文
共 50 条
  • [41] Devils in Your Apps: Vulnerabilities and User Privacy Exposure in Mobile Notification Systems
    Lou, Jiadong
    Zhang, Xiaohan
    Zhang, Yihe
    Li, Xinghua
    Yuan, Xu
    Zhang, Ning
    2023 53RD ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, DSN, 2023, : 28 - 41
  • [42] More Haste, Less Speed: How Update Frequency of Mobile Apps Influences Consumer Interest
    Gong, Xuan
    Razzaq, Amar
    Wang, Wei
    JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH, 2021, 16 (07): : 2922 - 2942
  • [43] Living a Lie: Security Analysis of Facial Liveness Detection Systems in Mobile Apps
    Wang, Xianbo
    Luo, Kaixuan
    Lau, Wing Cheong
    APPLIED CRYPTOGRAPHY AND NETWORK SECURITY, ACNS 2024, PT III, 2024, 14585 : 432 - 459
  • [44] Apps-Usage Driven Energy Management for Multicore Mobile Computing Systems
    Rex, Hou Zhao Qi
    Chuen, Jong Ching
    Herkersdorf, Andreas
    2014 14TH INTERNATIONAL SYMPOSIUM ON INTEGRATED CIRCUITS (ISIC), 2014, : 472 - 475
  • [45] Designing Hospital Wayfinding Systems, Touchscreen Kiosks, Environmental Cues and Mobile Apps: An Evaluation of a Mobile Wayfinding Application
    Harper, Christy
    Duke, Tyler
    Crosser, Andrea
    Avera, Angie
    Jefferies, Spencer
    ADVANCES IN HUMAN FACTORS AND ERGONOMICS IN HEALTHCARE AND MEDICAL DEVICES, 2020, 957 : 89 - 96
  • [46] How effective are mobile apps in managing people with type 2 diabetes mellitus? A systematic literature review protocol
    Taramasco, Carla
    Rimassa, Carla
    Garrido, Maria Elena Lagos
    Figueroa, Rosa L.
    PLOS ONE, 2024, 19 (04):
  • [47] Managing Ubiquitous Connectivity: Mobile Media Flow Service Systems
    Kolb, Darl
    Ivaturi, Koteswara
    Henderson, Sarah
    Srinivasan, Ananth
    2015 IEEE World Congress on Services, 2015, : 113 - 120
  • [48] Managing Safety and Adaptability in Mobile Multi-Robot Systems
    Bozhinoski, Darko
    QOSA'15 PROCEEDINGS OF THE 11TH INTERNATIONAL ACM SIGSOFT CONFERENCE ON QUALITY OF SOFTWARE ARCHITECTURES, 2015, : 135 - 140
  • [49] Managing Depth Information Uncertainty in Inland Mobile Navigation Systems
    Wawrzyniak, Natalia
    Hyla, Tomasz
    ROUGH SETS AND INTELLIGENT SYSTEMS PARADIGMS, RSEISP 2014, 2014, 8537 : 343 - 350
  • [50] Energy-Efficient Task Caching and Offloading Strategy in Mobile Edge Computing Systems
    Chen, Qian
    Liu, Zhoubin
    Ruan, Linna
    Wang, Zixiang
    Shao, Sujie
    Qi, Feng
    SECURITY WITH INTELLIGENT COMPUTING AND BIG-DATA SERVICES, 2020, 895 : 824 - 837