Holistic and Opportunistic Scheduling of Background I/Os in Flash-Based SSDs

被引:0
|
作者
Wang, Yu [1 ]
Zhou, You [2 ]
Wu, Fei [1 ]
Zhong, Yu [1 ,3 ]
Zhou, Jian [1 ]
Lu, Zhonghai [4 ]
Li, Shu [5 ]
Wang, Zhengyong [5 ]
Xie, Changsheng [1 ]
机构
[1] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
[3] DapuStor Corp, Prod Dev, Shenzhen 518100, Peoples R China
[4] KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, S-16440 Stockholm, Sweden
[5] Alibaba Grp, Hangzhou 310052, Peoples R China
基金
中国国家自然科学基金;
关键词
NAND flash; storage systems; I/O scheduling; background tasks; foreground performance;
D O I
10.1109/TC.2023.3288748
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Background (BG) tasks are maintained indispensably in multiple layers of storage systems, from applications to flash-based SSDs. They launch a large amount of I/Os, causing significant interference with foreground (FG) I/O performance. Our key insight is that, to mitigate such interference, holistic scheduling of system-wide, multi-source BG I/Os is required and can only be realized at the underlying SSD layer. Only the SSD has a global view of all FG and BG I/Os as well as direct information and control about flash storage resources. We are thus inspired to propose a novel I/O scheduling architecture, called HuFu. It provides a framework for host software to register BG tasks and offload their I/O scheduling into the SSD. Then, the SSD-internal I/O scheduler prioritizes FG I/O processing, while BG I/Os are scheduled opportunistically by utilizing flash parallelism and idleness. To verify HuFu, we perform case studies on RocksDB and compares it with several state-of-the-art host-side I/O scheduling schemes. Experimental results show that HuFu can significantly alleviate performance interference caused by BG I/Os and improve SSD bandwidth utilization, thus improving the FG throughput, average and tail latencies (e.g., by about 18% in a write-heavy workload).
引用
收藏
页码:3127 / 3139
页数:13
相关论文
共 50 条
  • [1] I/O Scheduling Schemes for Better I/O Proportionality on Flash-based SSDs
    Kim, Jaeho
    Lee, Eunjae
    Noh, Sam H.
    2016 IEEE 24TH INTERNATIONAL SYMPOSIUM ON MODELING, ANALYSIS AND SIMULATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS (MASCOTS), 2016, : 221 - 230
  • [2] A Performance Evaluation of Scientific I/O Workloads on Flash-Based SSDs
    Park, Stan
    Shen, Kai
    2009 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING AND WORKSHOPS, 2009, : 501 - 505
  • [3] Exploiting Internal Parallelism of Flash-based SSDs
    Park, Seon-yeong
    Seo, Euiseong
    Shin, Ji-Yong
    Maeng, Seungryoul
    Lee, Joonwon
    IEEE COMPUTER ARCHITECTURE LETTERS, 2010, 9 (01) : 9 - 12
  • [4] Integrating Flash-based SSDs into the Storage Stack
    Appuswamy, Raja
    van Moolenbroek, David C.
    Tanenbaum, Andrew S.
    2012 IEEE 28TH SYMPOSIUM ON MASS STORAGE SYSTEMS AND TECHNOLOGIES (MSST), 2012,
  • [5] Layer-Aware Request Scheduling for 3D Flash-Based SSDs
    Xu, Jinming
    Du, Yajuan
    Ding, Cong
    IEEE ACCESS, 2021, 9 : 72025 - 72032
  • [6] An Integrated Approach for Managing the Lifetime of Flash-Based SSDs
    Lee, Sungjin
    Kim, Taejin
    Park, Ji-Sung
    Kim, Jihong
    DESIGN, AUTOMATION & TEST IN EUROPE, 2013, : 1522 - 1525
  • [7] NVM-accelerated Metadata Management for Flash-based SSDs
    Xue, Mingdi
    Wang, Chundong
    Wei, Qingsong
    Yang, Jun
    Chen, Cheng
    2016 INTERNATIONAL CONFERENCE ON CLOUD COMPUTING RESEARCH AND INNOVATION - ICCCRI 2016, 2016, : 134 - 139
  • [8] Supporting System Consistency with Differential Transactions in Flash-Based SSDs
    Lu, Youyou
    Shu, Jiwu
    Guo, Jia
    Zhu, Peng
    IEEE TRANSACTIONS ON COMPUTERS, 2016, 65 (02) : 627 - 639
  • [9] An Adaptive Write Buffer Management Scheme for Flash-Based SSDs
    Wu, Guanying
    He, Xubin
    Eckart, Ben
    ACM TRANSACTIONS ON STORAGE, 2012, 8 (01)
  • [10] An Efficient and Parallel File Defragmentation Scheme for Flash-based SSDs
    Zhu, Guangyu
    Lee, Jeongeun
    Son, Yongseok
    37TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, 2022, : 1208 - 1211