Efficient hybrid polling for ultra-low latency storage devices

Gyusun Lee, Seokha Shin, Jinkyu Jeong

    Research output: Contribution to journalArticlepeer-review


    With the introduction of ultra-low latency SSDs, which complete I/O operations in a few microseconds, the use of polling is becoming an attractive solution for alleviating the overheads in interrupt-driven I/O completion. However, careful use of polling is essential because of its inherent CPU overhead. Hybrid polling, in which a timer-based sleep is inserted in the middle of polling, has recently been proposed to relieve the CPU overhead. However, there is still substantial headroom for further optimization to save CPU cycles. In this paper, we propose efficient hybrid polling scheme that minimizes the CPU cycles for polling without sacrificing the I/O latency. By considering I/O time characteristics of idle and busy storage devices, our scheme makes an appropriate sleep time decision that maximizes the I/O performance and minimizes the CPU cycles for polling. The proposed scheme is implemented in the Linux kernel and evaluated with various I/O workloads. The evaluation results show that whenever an SSD is heavily or lightly loaded, our scheme achieves I/O latency identical to that of classical polling while maintaining a low CPU utilization. Compared to the original hybrid polling, our scheme reduces CPU utilization by 5%–40% and provides faster I/O latency by up to 10%.

    Original languageEnglish
    Article number102338
    JournalJournal of Systems Architecture
    Publication statusPublished - 2022 Jan

    Bibliographical note

    Funding Information:
    We thank the anonymous reviewers for their valuable comments. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) ( NRF-2020R1A2C2102406 ), by the MSIT (Ministry of Science and ICT) , Korea under the ICT Creative Consilience program ( IITP-2021-0-00773 , (IITP-2020-0-01821 ), and by Samsung Electronics .

    Publisher Copyright:
    © 2021 Elsevier B.V.

    All Science Journal Classification (ASJC) codes

    • Software
    • Hardware and Architecture


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