Revisiting widely held SSD expectations and rethinking system-level implications

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 46
  • Download : 0
Storage applications leveraging Solid State Disk (SSD) technology are being widely deployed in diverse computing systems. These applications accelerate system performance by exploiting several SSD-specific characteristics. However, modern SSDs have undergone a dramatic technology and architecture shift in the past few years, which makes widely held assumptions and expectations regarding them highly questionable. The main goal of this paper is to question popular assumptions and expectations regarding SSDs through an extensive experimental analysis using 6 state-of-the-art SSDs from different vendors. Our analysis leads to several conclusions which are either not reported in prior SSD literature, or contradict to current conceptions. For example, we found that SSDs are not biased toward read-intensive workloads in terms of performance and reliability. Specifically, random read performance of SSDs is worse than their sequential and random write performance by 40% and 39% on average, and more importantly, the performance of sequential reads gets significantly worse over time. Further, we found that reads can shorten SSD lifetime more than writes, which is very unfortunate, given the fact that many existing systems/platforms already employ SSDs as read caches or in applications that are highly read intensive. We also performed a comprehensive study to understand the worst-case performance characteristics of our SSDs, and investigated the viability of recently proposed enhancements that are geared towards alleviating the worst-case performance challenges, such as TRIM commands and background-tasks. Lastly, we uncover the overheads brought by these enhancements and their limits, and discuss system-level implications. Copyright © 2013 ACM.
ACM Special Interest Group on Performance Evaluation (SIGMETRICS)
Issue Date

2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013, pp.203 - 216

Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.


  • mendeley


rss_1.0 rss_2.0 atom_1.0