SAW: System-assisted wear leveling on the write endurance of NAND flash devices

The write endurance of NAND Hash memory adversely impacts the lifetime of flash devices. A flash cell is likely to wear out after undergoing excessive program/erase (P/E) flips. Wear leveling is hence employed to spread erase operations as evenly as possible. It is traditionally conducted by the flash translation layer (FTL), a management firmware residing in Hash devices. In this paper, we shall propose a novel wear leveling algorithm involving the operating system (OS). We will show that our operating System-Assisted Wear leveling (SAW) algorithm can significantly improve the wear evenness. SAW takes advantage of OS's knowledge about files at a higher level of abstraction, and provides useful hints to the lower-level FTL to accommodate data. A prototype based on a file system and an FTL has been developed to verify the effectiveness of SAW. Experiments show that wear evenness can be improved by as much as 85.0% compared to the state-of-the-art FTL wear leveling schemes.

[1]  Tei-Wei Kuo,et al.  Endurance Enhancement of Flash-Memory Storage, Systems: An Efficient Static Wear Leveling Design , 2007, 2007 44th ACM/IEEE Design Automation Conference.

[2]  David Hung-Chang Du,et al.  Hot data identification for flash-based storage systems using multiple bloom filters , 2011, 2011 IEEE 27th Symposium on Mass Storage Systems and Technologies (MSST).

[3]  Tei-Wei Kuo,et al.  Joint management of RAM and flash memory with access pattern considerations , 2012, DAC Design Automation Conference 2012.

[4]  Nikil D. Dutt,et al.  Meta-Cure: A reliability enhancement strategy for metadata in NAND flash memory storage systems , 2012, DAC Design Automation Conference 2012.

[5]  Jeffrey Katcher,et al.  PostMark: A New File System Benchmark , 1997 .

[6]  Li-Pin Chang,et al.  On efficient wear leveling for large-scale flash-memory storage systems , 2007, SAC '07.

[7]  Chundong Wang,et al.  Extending the lifetime of NAND flash memory by salvaging bad blocks , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[8]  Nikolai Joukov,et al.  A nine year study of file system and storage benchmarking , 2008, TOS.

[9]  Margo I. Seltzer,et al.  File classification in self-* storage systems , 2004, International Conference on Autonomic Computing, 2004. Proceedings..

[10]  Chundong Wang,et al.  Observational wear leveling: An efficient algorithm for flash memory management , 2012, DAC Design Automation Conference 2012.

[11]  Li-Pin Chang,et al.  A low-cost wear-leveling algorithm for block-mapping solid-state disks , 2011, LCTES '11.

[12]  Youngjae Kim,et al.  FlashSim: A Simulator for NAND Flash-Based Solid-State Drives , 2009, 2009 First International Conference on Advances in System Simulation.

[13]  Tei-Wei Kuo,et al.  Efficient identification of hot data for flash memory storage systems , 2006, TOS.

[14]  Tei-Wei Kuo,et al.  A file-system-aware FTL design for flash-memory storage systems , 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.

[15]  Aviral Shrivastava,et al.  FSAF: File system aware flash translation layer for NAND Flash Memories , 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.