HAML-SSD: A hardware accelerated hotness-aware machine learning based SSD management

Bingzhe Li, Chunhua Deng, Jinfeng Yang, David Lilja, Bo Yuan, David Du

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Solid state drive (SSD) as a fast storage device has been playing an important role across many applications from mobile computing to large distributed systems in recent years. However, the performance of the SSD can be degraded tremendously due to the intrinsic properties of NAND-based flash memory including limited erase cycles and asymmetric write and erase operations. Previous works separated hot/cold data into different blocks in order to improve SSD performance. 'Hotness' is typically defined as the cumulative update frequencies of pages. However, we believe that an additional new parameter, average update time interval, should also be considered into the 'hotness' definition associated with the update frequency. Moreover, to adaptively classify hot/cold data, a machine learning algorithm is applied to better accommodate the dynamically changed I/O access patterns of traces. In this paper, a machine learning (ML) based SSD management called HAML-SSD is proposed. The purpose of applying the ML algorithm is to dynamically cluster the data with similar 'hotness' based on a new definition of 'hotness'. Thus, a two-dimension clustering algorithm is used for storing the pages categorized into the same cluster within the same block. Moreover, to obtain reasonable training time, a specific hardware component called HAML-unit is designed in the SSD. Finally, the experimental results indicate that the HAML-SSD decreases the response time around 26.3%-57.7% compared to previous works with the evaluation of real traces.

Original languageEnglish (US)
Title of host publication2019 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 - Digest of Technical Papers
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728123509
DOIs
StatePublished - Nov 2019
Event38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 - Westin Westminster, United States
Duration: Nov 4 2019Nov 7 2019

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Volume2019-November
ISSN (Print)1092-3152

Conference

Conference38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019
CountryUnited States
CityWestin Westminster
Period11/4/1911/7/19

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Li, B., Deng, C., Yang, J., Lilja, D., Yuan, B., & Du, D. (2019). HAML-SSD: A hardware accelerated hotness-aware machine learning based SSD management. In 2019 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 - Digest of Technical Papers [8942140] (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD; Vol. 2019-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAD45719.2019.8942140