A high-performance solid-state drive by garbage collection overhead suppression

Author(s):  
Tomoaki Yamada ◽  
Chao Sun ◽  
Ken Takeuchi
Author(s):  
Chihiro Matsui ◽  
Asuka Arakawa ◽  
Chao Sun ◽  
Tomoko Ogura Iwasaki ◽  
Ken Takeuchi

2014 ◽  
Vol 1042 ◽  
pp. 212-217 ◽  
Author(s):  
Zheng Guo Chen ◽  
Nong Xiao ◽  
Fang Liu ◽  
Yu Xuan Xing ◽  
Zhen Sun

Data deduplication technology applied in solid state disks (SSD), can reduce the amount of write operations and garbage collection, and thus improve writing performance and prolong lifetime. With the significant increase of write performance onto SSD, whether deduplication based on SSD could be a performance bottleneck of SSD comes to a spot worthy of our attention. To this end, this paper, firstly, performs an experiment on achieving deduplication via software method, and reveals that software-based deduplication decreases SSD's read and write performance. And then a hardware-based deduplication with details is proposed and implemented to accelerate deduplication using FPGA, and expected results are achieved. Finally, we come to the conclusion that hardware-based deduplication can not only guarantee read and write performance of SSD, but also save storage capacity and enhance endurance.


2012 ◽  
Vol E95-C (4) ◽  
pp. 609-616
Author(s):  
Kousuke MIYAJI ◽  
Ryoji YAJIMA ◽  
Teruyoshi HATANAKA ◽  
Mitsue TAKAHASHI ◽  
Shigeki SAKAI ◽  
...  

Author(s):  
Jaeyoung Shin ◽  
Soomin Kim ◽  
Kihyun Sung ◽  
Hyunwoo Jung ◽  
Jinwook Song ◽  
...  

2021 ◽  
Vol 11 (24) ◽  
pp. 11842
Author(s):  
Gijun Oh ◽  
Junseok Yang ◽  
Sungyong Ahn

Log-structured merge-tree (LSM-Tree)-based key–value stores are attracting attention for their high I/O (Input/Output) performance due to their sequential write characteristics. However, excessive writes caused by compaction shorten the lifespan of the Solid-state Drive (SSD). Therefore, there are several studies aimed at reducing garbage collection overhead by using Zoned Namespace ZNS; SSD in which the host can determine data placement. However, the existing studies have limitations in terms of performance improvement because the lifetime and hotness of key–value data are not considered. Therefore, in this paper, we propose a technique to minimize the space efficiency and garbage collection overhead of SSDs by arranging them according to the characteristics of key–value data. The proposed method was implemented by modifying ZenFS of RocksDB and, according to the result of the performance evaluation, the space efficiency could be improved by up to 75%.


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