Title :
Improving write performance by enhancing internal parallelism of Solid State Drives
Author :
Xiaojun Ruan ; Ziliang Zong ; Alghamdi, Mohammed I. ; Yun Tian ; Xunfei Jiang ; Xiao Qin
Author_Institution :
Dept. of Comput. Sci., West Chester Univ. of Pennsylvania, Chester, PA, USA
Abstract :
Most researches of Solid State Drives (SSDs) architectures rely on Flash Translation Layer (FTL) algorithms and wear-leveling; however, internal parallelism in Solid State Drives has not been well explored. In this research, we proposed a new strategy to improve SSD write performance by enhancing internal parallelism inside SSDs. A SDRAM buffer is added in the design for buffering and scheduling write requests. Because the same logical block numbers may be translated to different physical numbers at different times in FTL, the on-board SDRAM buffer is used to buffer requests at the lower level of FTL. When the buffer is full, same amount of data will be assigned to each storage package in SSDs to enhance internal parallelism. To accurately evaluate performance, we use both synthetic workloads and real-world applications in experiments. We compare the enhanced internal parallelism scheme with the traditional LRU strategy since it is unfair to compare an SSD having buffer with an SSD without a buffer. The simulation results demonstrate that the writing performance of our design is significantly improved compared with the LRU-cache strategy with the same amount of buffer sizes.
Keywords :
DRAM chips; buffer storage; disc drives; flash memories; parallel memories; scheduling; FTL algorithms; LRU-cache strategy; SSD architecture; SSD write performance; buffer sizes; enhanced internal parallelism scheme; flash translation layer algorithms; logical block numbers; on-board SDRAM buffer; real-world applications; solid state drive architecture; storage package; synthetic workloads; wear-leveling; write request buffering; write request scheduling; Algorithm design and analysis; Ash; Benchmark testing; Educational institutions; Kernel; Parallel processing; SDRAM;
Conference_Titel :
Performance Computing and Communications Conference (IPCCC), 2012 IEEE 31st International
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4673-4881-2
DOI :
10.1109/PCCC.2012.6407767