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
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