2R: Efficiently Isolating Cold Pages in Flash Storages
Minji Kang, Soyee Choi, Gihwan Oh, Sang Won Lee
Abstract
Given skewed writes common in databases, the conventional 1R-Greedy FTL incurs huge write amplification, most of which is contributed by cold pages amounting to 80% of data. Since 1R-Greedy manages all flash blocks in one region at no type distinction, cold pages will be mixed with noncold ones in the same blocks, spread across blocks over time, and thus repeatedly relocated upon garbage collections.
In this paper, we propose "two region" FTL (2R in short); with two flash regions of normal and cold, it focuses on isolating cold pages into cold region and thus preventing their repetitive relocations. 2R has two versions. The optimized version, 2R-FIFO, can further prevent the problem of false cold pages in the basic version, 2R-Greedy, by taking FIFO instead of Greedy as its victim selection policy. 2R is unique in that all its design decisions, including page placement and migration between regions, cold page identification, victim block selection, and space allocation among regions, capitalize on workload characteristics such as write skews, temporal locality, and frozen pages. Thanks to the principled approach, 2R is, unlike the existing hot/cold separation FTLs, a statistics-free and practical solution which can efficiently and effectively separate cold pages using only two regions.
Experimental results using a real OpenSSD as well as trace-driven simulations confirm that 2R-FIFO can, compared to 1R-Greedy, halve the write amplification in two OLTP benchmarks, TPC-C and LinkBench, thereby doubling IO performance and transaction throughput. In particular, as flash storage becomes nearly full, 2R-FIFO starts outperforming 1R-Greedy by 4x or more.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 78843315-be5b-41b7-a081-42dc7c2beca3Cited by top-tier papers2
- Learning-based Data Separation for Write Amplification Reduction in Solid State DrivesPenghao Sun, Litong You, Shengan Zheng, Wanru Zhang et al.DAC 2023 · 9 citations
- Why Files If You Have a DBMS?Lam-Duy Nguyen, Viktor LeisICDE 2024 · 7 citations
Related papers
- Your Read is Our Priority in Flash StorageMijin An, Soojun Im, Dawoon Jung, Sang Won LeeVLDB 2022 · 9 citations
- LRU-C: Parallelizing Database I/Os for Flash SSDsBo-Hyun Lee, Mijin An, Sang-Won LeeVLDB 2023 · 14 citations
- FlashAlloc: Dedicating Flash Blocks By ObjectsJonghyeok Park, Soyee Choi, Gihwan Oh, Soojun Im et al.VLDB 2023 · 3 citations
- Avoiding Read Stalls on Flash StorageMijin An, In-Yeong Song, Yong Ho Song, Sang-Won LeeSIGMOD 2022 · 10 citations
- How to Cut Out Expired Data with Nearly Zero Overhead for Solid-State DrivesWei-Lin Wang, Tseng-Yi Chen, Yuan-Hao Chang, Hsin-Wen Wei et al.DAC 2020 · 2 citations
