TY - GEN
T1 - AutoSSD
T2 - 2018 USENIX Annual Technical Conference, USENIX ATC 2018
AU - Kim, Bryan S.
AU - Yang, Hyun Suk
AU - Min, Sang Lyul
N1 - Funding Information:
We thank the anonymous reviewers for their constructive and insightful comments, and also thank Jaejin Lee, Jongmoo Choi, Hyeonsang Eom, and Eunji Lee for reviewing the early stages of this work. This work was supported in part by SK Hynix and the National Research Foundation of Korea under the PF Class Heterogeneous High Performance Computer Development (NRF-2016M3C4A7952587). Institute of Computer Technology at Seoul National University provided the research facilities for this study.
Publisher Copyright:
© Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018. All rights reserved.
PY - 2020
Y1 - 2020
N2 - From small mobile devices to large-scale storage arrays, flash memory-based storage systems have gained a lot of popularity in recent years. However, the uncoordinated use of resources by competing tasks in the flash translation layer (FTL) makes it difficult to guarantee predictable performance. In this paper, we present AutoSSD, an autonomic SSD architecture that self-manages FTL tasks to maintain a high-level of QoS performance. In AutoSSD, each FTL task is given an illusion of a dedicated flash memory subsystem, allowing tasks to be implemented oblivious to others and making it easy to integrate new tasks to handle future flash memory quirks. Furthermore, each task is allocated a share that represents its relative importance, and its utilization is enforced by a simple and effective scheduling scheme that limits the number of outstanding flash memory requests for each task. The shares are dynamically adjusted through feedback control by monitoring key system states and reacting to their changes to coordinate the progress of FTL tasks. We demonstrate the effectiveness of AutoSSD by holistically considering multiple facets of SSD internal management, and by evaluating it across diverse workloads. Compared to state-of-the-art techniques, our design reduces the average response time by up to 18.0%, the 3 nines (99.9%) QoS by up to 67.2%, and the 6 nines (99.9999%) QoS by up to 76.6% for QoS-sensitive small reads.
AB - From small mobile devices to large-scale storage arrays, flash memory-based storage systems have gained a lot of popularity in recent years. However, the uncoordinated use of resources by competing tasks in the flash translation layer (FTL) makes it difficult to guarantee predictable performance. In this paper, we present AutoSSD, an autonomic SSD architecture that self-manages FTL tasks to maintain a high-level of QoS performance. In AutoSSD, each FTL task is given an illusion of a dedicated flash memory subsystem, allowing tasks to be implemented oblivious to others and making it easy to integrate new tasks to handle future flash memory quirks. Furthermore, each task is allocated a share that represents its relative importance, and its utilization is enforced by a simple and effective scheduling scheme that limits the number of outstanding flash memory requests for each task. The shares are dynamically adjusted through feedback control by monitoring key system states and reacting to their changes to coordinate the progress of FTL tasks. We demonstrate the effectiveness of AutoSSD by holistically considering multiple facets of SSD internal management, and by evaluating it across diverse workloads. Compared to state-of-the-art techniques, our design reduces the average response time by up to 18.0%, the 3 nines (99.9%) QoS by up to 67.2%, and the 6 nines (99.9999%) QoS by up to 76.6% for QoS-sensitive small reads.
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M3 - Conference contribution
AN - SCOPUS:85077042151
T3 - Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018
SP - 677
EP - 689
BT - Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018
PB - USENIX Association
Y2 - 11 July 2018 through 13 July 2018
ER -