Low I/O Intensity-aware Partial GC Scheduling to Reduce Long-tail Latency in SSDs

Author:

Sha Zhibing1,Li Jun1,Song Lihao1,Tang Jiewen1,Huang Min1,Cai Zhigang1,Qian Lianju2,Liao Jianwei1,Liu Zhiming1

Affiliation:

1. Southwest University of China, China

2. Chengdu SGK Semiconductor Co, Ltd, China

Abstract

This article proposes a low I/O intensity-aware scheduling scheme on garbage collection (GC) in SSDs for minimizing the I/O long-tail latency to ensure I/O responsiveness. The basic idea is to assemble partial GC operations by referring to several determinable factors (e.g., I/O characteristics) and dispatch them to be processed together in idle time slots of I/O processing. To this end, it first makes use of Fourier transform to explore the time slots having relative sparse I/O requests for conducting time-consuming GC operations, as the number of affected I/O requests can be limited. After that, it constructs a mathematical model to further figure out the types and quantities of partial GC operations, which are supposed to be dealt with in the explored idle time slots, by taking the factors of I/O intensity, read/write ratio, and the SSD use state into consideration. Through a series of simulation experiments based on several realistic disk traces, we illustrate that the proposed GC scheduling mechanism can noticeably reduce the long-tail latency by between 5.5% and 232.3% at the 99.99th percentile, in contrast to state-of-the-art methods.

Funder

NSFC

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference38 articles.

1. W. Choi and M. Kandemir. 2018. Parallelizing garbage collection with I/O to improve flash resource utilization. In HPDC’18. W. Choi and M. Kandemir. 2018. Parallelizing garbage collection with I/O to improve flash resource utilization. In HPDC’18.

2. S. Choudhuri and T. Givargis. 2008. Deterministic service guarantees for NAND flash using partial block cleaning. In CODES+ISSS’08. S. Choudhuri and T. Givargis. 2008. Deterministic service guarantees for NAND flash using partial block cleaning. In CODES+ISSS’08.

3. J. Cui Y. Zhang and J. Huang. 2018. ShadowGC: Cooperative garbage collection with multi-level buffer for performance improvement in NAND flash-based SSDs. In DATE’18. J. Cui Y. Zhang and J. Huang. 2018. ShadowGC: Cooperative garbage collection with multi-level buffer for performance improvement in NAND flash-based SSDs. In DATE’18.

4. C. Gao L. Shi and Y. Di. 2018. Exploiting chip idleness for minimizing garbage collection–induced chip access conflict on SSDs. ACM Trans. Des. Automat. Electron. Syst.2018. DOI:https://doi.org/10.1145/3131850 C. Gao L. Shi and Y. Di. 2018. Exploiting chip idleness for minimizing garbage collection–induced chip access conflict on SSDs. ACM Trans. Des. Automat. Electron. Syst.2018. DOI:https://doi.org/10.1145/3131850

5. S. Hahn J. Kim and S. Lee. 2015. To collect or not to collect: Just-in-time garbage collection for high-performance SSDs with long lifetimes. In DAC. S. Hahn J. Kim and S. Lee. 2015. To collect or not to collect: Just-in-time garbage collection for high-performance SSDs with long lifetimes. In DAC.

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