Power Management for Mobile Games on Asymmetric Multi-Cores

被引:0
|
作者
Pathania, Anuj [1 ]
Pagani, Santiago [1 ]
Shafique, Muhammad [1 ]
Henkel, Joerg [1 ]
机构
[1] Karlsruhe Inst Technol, Chair Embedded Syst, Karlsruhe, Germany
关键词
Power Management; Mobile Games; Asymmetric or Heterogeneous Multi-Cores; PERFORMANCE;
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
Gaming on mobile platforms is highly power hungry and rapidly drains the limited-capacity battery. In multi-threaded gaming, each thread has different processing requirements and even a single slow thread may lead to Quality of Service (QoS) violations. Further, modern mobile platforms are equipped with asymmetric multi-core processors, so that different cores exhibit diverse power and performance properties. These asymmetric cores along with different Dynamic Power Management (DPM) techniques enable a high degree of power efficiency in mobile gaming. The default Linux power manager (i.e. "Governor") of asymmetric multi-cores performs power-wise inefficient for mobile games as it over allocates resources for processing threads by being oblivious to the QoS. The state-of-the-art Governor for mobile gaming does not account for multi-threaded gaming workloads, which are mainstream in mobile gaming. In this work, we present a power-performance characterization of multi-threaded mobile games by executing them on a real-world mobile platform with an asymmetric multi-core. This analysis is leveraged to propose a QoS-aware Governor running a lightweight online heuristic that holistically accounts for thread-to-core mapping and DPM. This solution, when integrated into the platform's Operating System (OS), provides 12% improved power efficiency on average.
引用
收藏
页码:243 / 248
页数:6
相关论文
共 50 条
  • [1] Price Theory Based Power Management for Heterogeneous Multi-Cores
    Muthukaruppan, Thannirmalai Somu
    Pathania, Anuj
    Mitra, Tulika
    [J]. ACM SIGPLAN NOTICES, 2014, 49 (04) : 161 - 176
  • [2] Online Power Management for Multi-Cores: A Reinforcement Learning Based Approach
    Wang, Yiming
    Zhang, Weizhe
    Hao, Meng
    Wang, Zheng
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2022, 33 (04) : 751 - 764
  • [3] Approximation-Aware Coordinated Power/Performance Management for Heterogeneous Multi-cores
    Kanduri, Anil
    Miele, Antonio
    Rahmani, Amir M.
    Liljeberg, Pasi
    Bolchini, Cristiana
    Dutt, Nikil
    [J]. 2018 55TH ACM/ESDA/IEEE DESIGN AUTOMATION CONFERENCE (DAC), 2018,
  • [4] Seamless Parallelism Management for Video Stream Processing on Multi-Cores
    Vogel, Adriano
    Griebler, Dalvan
    Fernandes, Luiz Gustavo
    Danelutto, Marco
    [J]. PARALLEL COMPUTING: TECHNOLOGY TRENDS, 2020, 36 : 533 - 542
  • [5] Accelerating Code on Multi-cores with FastFlow
    Aldinucci, Marco
    Danelutto, Marco
    Kilpatrick, Peter
    Meneghin, Massimiliano
    Torquati, Massimo
    [J]. EURO-PAR 2011 PARALLEL PROCESSING, PT 2, 2011, 6853 : 170 - 181
  • [6] Software Coherence Management on Non-Coherent Cache Multi-cores
    Cai, Jian
    Shrivastava, Aviral
    [J]. 2016 29TH INTERNATIONAL CONFERENCE ON VLSI DESIGN AND 2016 15TH INTERNATIONAL CONFERENCE ON EMBEDDED SYSTEMS (VLSID), 2016, : 397 - 402
  • [7] Multi-cores, posets, and lattice paths
    Amdeberhan, Tewodros
    Leven, Emily Sergel
    [J]. ADVANCES IN APPLIED MATHEMATICS, 2015, 71 : 1 - 13
  • [8] A novel thermal management scheme for 3D-IC chips with multi-cores and high power density
    Ding, Bin
    Zhang, Zhi-Hao
    Gong, Liang
    Xu, Ming-Hai
    Huang, Zhao-Qin
    [J]. APPLIED THERMAL ENGINEERING, 2020, 168
  • [9] Adaptive Cache Management for a combined SRAM and DRAM Cache Hierarchy for Multi-Cores
    Hameed, Fazal
    Bauer, Lars
    Henkel, Joerg
    [J]. DESIGN, AUTOMATION & TEST IN EUROPE, 2013, : 77 - 82
  • [10] Parallelization of an XML Data Compressor on Multi-cores
    Mueldner, Tomasz
    Fry, Christopher
    Corbin, Tyler
    Miziolek, Jan Krzysztof
    [J]. PARALLEL PROCESSING AND APPLIED MATHEMATICS, PT II, 2012, 7204 : 101 - 110