Zweilous: A Decoupled and Flexible Memory Management Framework

被引:0
作者
Li, Guoxi [1 ]
Chen, Wenzhi [1 ]
Xiang, Yang [2 ]
机构
[1] Zhejiang Univ, Sch Comp Sci & Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Swinburne Univ Technol, Sch Software & Elect Engn, Hawthorn, Vic 3122, Australia
关键词
Memory management; Hardware; Linux; Cloud computing; Kernel; Operating systems; memory management; memory architecture; ARCHITECTURE;
D O I
10.1109/TC.2020.3009124
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Currently, with the booming growth of cloud computing, workloads from broad ranges of functions and demands are crammed into a single physical machine. They lay considerable stress on the need of evolution of the operating system underneath, especially the memory subsystem. Even enhancing large pages with main memory compression is not intuitively straightforward due to rigid rules imposed by the state-of-the-art manager Buddy System from the beginning of the design. To relieve the aforementioned problems and provide broader design space for system designers, we propose Zweilous, a clean slate physical memory management framework. It is self-contained, highly decoupled, and thus can co-exist with the vanilla memory manager. Separate self-contained metadata/functions guarantee a flexible extension with little modification to current frameworks. To show it is easy to add enhanced functions that accelerate the evolution of the memory management subsystem, we implement Hzmem, a new large page memory manager redesign enhanced with the function of main memory compression. Our method achieves competitive performance compared with native and virtualized large page support, effective memory size increased and fewer impacts on other parts of the operating system.
引用
收藏
页码:1350 / 1362
页数:13
相关论文
共 50 条
  • [21] HMC-SIM: A Simulation Framework for Hybrid Memory Cube Devices
    Leidel, John D.
    Chen, Yong
    PARALLEL PROCESSING LETTERS, 2014, 24 (04)
  • [22] Analysis of Memory Management Policies for Heterogeneous Cloud Computing
    Son, Dong Oh
    Choi, Hong Jun
    Park, Jae Hyung
    Hong, Cheol
    2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA 2013), 2013,
  • [23] A massive MPI parallel framework of smoothed particle hydrodynamics with optimized memory management for extreme mechanics problems
    Liu, Jiahao
    Yang, Xiufeng
    Zhang, Zhilang
    Liu, Moubin
    COMPUTER PHYSICS COMMUNICATIONS, 2024, 295
  • [24] Object memory management for constrained devices with heterogeneous memories
    Marquet, Kevin
    Grimaud, Gilles
    Lecture Notes in Electrical Engineering, 2009, 38 : 219 - 232
  • [25] Survey of Memory Management Techniques for HPC and Cloud Computing
    Pupykina, Anna
    Agosta, Giovanni
    IEEE ACCESS, 2019, 7 : 167351 - 167373
  • [26] ALMAS: An Application-Level Memory Management Service
    Salimi, Hadi
    Sayyah, Seyed Alimohammad
    Sharifi, Mohsen
    2008 3RD INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES: FROM THEORY TO APPLICATIONS, VOLS 1-5, 2008, : 2204 - 2207
  • [27] A SURVEY OF MEMORY MANAGEMENT
    VANWEZENBEEK, AM
    WITHAGEN, WJ
    MICROPROCESSING AND MICROPROGRAMMING, 1993, 36 (03): : 141 - 162
  • [28] Spark Memory Management
    Zhang, Wei
    Li, Jingmei
    ADVANCED HYBRID INFORMATION PROCESSING, 2018, 219 : 65 - 69
  • [29] Morpho: A decoupled MapReduce framework for elastic cloud computing
    Lu, Lu
    Shi, Xuanhua
    Jin, Hai
    Wang, Qiuyue
    Yuan, Daxing
    Wu, Song
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE, 2014, 36 : 80 - 90
  • [30] A Comprehensive Memory Management Framework for CPU-FPGA Heterogenous SoCs
    Du, Zelin
    Zhang, Qianling
    Lin, Mao
    Li, Shiqing
    Li, Xin
    Ju, Lei
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 42 (04) : 1058 - 1071