A technique to improve garbage collection performance for NAND flash-based storage systems

2012 ◽  
Vol 58 (2) ◽  
pp. 470-478 ◽  
Author(s):  
Jaehyeong Jeong ◽  
Yong Song
Keyword(s):  
Garbage Collection ◽  
Storage Systems ◽  
Nand Flash

scholarly journals A Cache Policy Based on Request Association Analysis for Reliable NAND-Based Storage Systems

2021 ◽  
Vol 11 (14) ◽  
pp. 6623
Author(s):  
Chi-Hsiu Su ◽  
Chin-Hsien Wu
Keyword(s):  
Association Analysis ◽  
Flash Memory ◽  
Free Space ◽  
Garbage Collection ◽  
Storage Systems ◽  
Nand Flash ◽  
Solid State Drives ◽  
Nand Flash Memory ◽  
Spatial Locality ◽  
Cache Hit Ratio

Compared with the traditional hard-disk drives (HDDs), solid-state drives (SSDs) have adopted NAND flash memory and become the current popular storage devices. However, when the free space in NAND flash memory is not enough, the garbage collection will be triggered to recycle the free space. The activities of the garbage collection include a large amount of data written and time-consuming erase operations that can reduce the performance of NAND flash memory. Therefore, DRAM is usually added to NAND flash memory as cache to store frequently used data. The typical cache methods mainly utilize the data characteristics of temporal locality and spatial locality to keep the frequently used data in the cache as much as possible. In addition, we find that there are not only temporal/spatial locality, but also certain associations between the accessed data. Therefore, we suggest that a cache policy should not only consider the temporal/spatial locality but also consider the association relationship between the accessed data to improve the cache hit ratio. In the paper, we will propose a cache policy based on request association analysis for reliable NAND-based storage systems. According to the experimental results, the cache hit ratio of the proposed method can be increased significantly when compared with the typical cache methods.

Energy-Scalable 4KB LDPC Decoding Architecture for NAND-Flash-Based Storage Systems

2016 ◽  
Vol E99.C (2) ◽  
pp. 293-301 ◽  
Author(s):  
Youngjoo LEE ◽  
Jaehwan JUNG ◽  
In-Cheol PARK
Keyword(s):  
Storage Systems ◽  
Nand Flash ◽  
Ldpc Decoding

BAGC: Buffer-Aware Garbage Collection for Flash-Based Storage Systems

2013 ◽  
Vol 62 (11) ◽  
pp. 2141-2154 ◽  
Author(s):  
Sungjin Lee ◽  
Dongkun Shin ◽  
Jihong Kim
Keyword(s):  
Garbage Collection ◽  
Storage Systems

FeGC: An efficient garbage collection scheme for flash memory based storage systems

2011 ◽  
Vol 84 (9) ◽  
pp. 1507-1523 ◽  
Author(s):  
Ohhoon Kwon ◽  
Kern Koh ◽  
Jaewoo Lee ◽  
Hyokyung Bahn
Keyword(s):  
Flash Memory ◽  
Garbage Collection ◽  
Storage Systems

Garbage Collection Algorithms for NAND Flash Memory Devices -- An Overview

2013 ◽  
Author(s):  
Raja Subramani ◽  
Haritima Swapnil ◽  
Niharika Thakur ◽  
Bharath Radhakrishnan ◽  
Krishnamurthy Puttaiah
Keyword(s):  
Flash Memory ◽  
Garbage Collection ◽  
Memory Devices ◽  
Nand Flash ◽  
Nand Flash Memory

scholarly journals A Block Classification Method with Monitor and Restriction in NAND Flash memory

2021 ◽  
Vol 12 (5) ◽  
pp. 209-215
Author(s):  
Myungsub Lee
Keyword(s):  
Performance Evaluation ◽  
Standard Deviation ◽  
Flash Memory ◽  
Garbage Collection ◽  
Memory Systems ◽  
Nand Flash ◽  
Nand Flash Memory ◽  
Wear Leveling ◽  
Block Classification ◽  
Update Frequency

In this paper, we propose a block classification with monitor and restriction (BCMR) method to isolate and reduce the interference of blocks in garbage collection and wear leveling. The proposed method monitors the endurance variation of blocks during garbage collection and detects hot blocks by making a restriction condition based on this information. This method induces block classification by its update frequency for garbage collection and wear leveling, resulting in a prolonged lifespan for NAND flash memory systems. The performance evaluation results show that the BCMR method prolonged the life of NAND flash memory systems by 3.95% and reduced the standard deviation per block by 7.4%, on average.

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