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ExLRU : A Unified Write Buffer Cache Management for Flash Memory EMSOFT '11 Liang Shi 1,2, Jianhua Li 1,2, Chun Jason Xue 1, Chengmo Yang 3 and Xuehai.

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Presentation on theme: "ExLRU : A Unified Write Buffer Cache Management for Flash Memory EMSOFT '11 Liang Shi 1,2, Jianhua Li 1,2, Chun Jason Xue 1, Chengmo Yang 3 and Xuehai."— Presentation transcript:

1 ExLRU : A Unified Write Buffer Cache Management for Flash Memory EMSOFT '11 Liang Shi 1,2, Jianhua Li 1,2, Chun Jason Xue 1, Chengmo Yang 3 and Xuehai Zhou 2 1 Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong 2 Department of Computer Science, University of Science and Technology of China, Hefei, China 3 Department of Electrical & Commputer Engineering, University of Delaware 2012. 01. 12 (Thu) Kwangwoon univ. SystemSoftware Lab. HoSeok Seo 1

2 Introduction  Propose  Write buffer management scheme for Flash memory  Purpose of write buffer?  Increase the write performance  Reduce the number of erase operations on flash memory  Why consider NAND Flash characteristics?  Write operation time is longer than read operation  NAND Flash has limited erase operation count  Out-place-update 2

3 Background  Previous study for NAND flash & Access patterns  FAB, BPLRU, etc 3 Weak from sequential write patterns Weak from random write patterns

4 Motivation  Previous schemes is  Managed with the block-level information.  Lack of the page-level information.  Result in inappropriate eviction decisions, as follows:  Slow retirement of large cold blocks. -Block size is big, but pages is cold.  Early eviction of small hot blocks. -Block size is small, but pages is hot.  Cold page retention in heat-imbalanced blocks. -Few pages is hot, but most pages is cold.  Thus, ExLRU takes the page-level access information and the characteristics of flash memory. 4

5 Cost Model of ExLRU  The page-level information and the block-level information 5

6 Cost Model of ExLRU  Averaged Frequency of Pages (AFP)  Averaged Frequency of Block (AFB)  Unified eviction cost of block x (UC) 6

7 Cost Model of ExLRU  Example  Cost is 7

8 Efficient ExLRU  The cost model of ExLRU has the overhead of O(n).  Efficient ExLRU  Proposed to reduce the overhead.  Identify the block with UC value low enough, not the lowest.  Pre-identify blocks during the idle time between two write requests  Cost is 8

9 Efficient ExLRU  Two processes  Scanning process and victim block selection process 9 (WR)(ER)

10 Efficient ExLRU  In scanning process.  Work in time between two write requests, if the number of blocks in ER is smaller than a threshold N min.  Move blocks into ER, if UC < T UC  In victim block selection process.  Select a block at LRU position of ER when the buffer is full.  If block miss in ER, UC values of blocks decrease.  If hit in ER, re-compute UC, and move a block WR or not.  If page miss in ER, add pages a block, and re-compute UC, and move a block MRU position of ER 10

11 Experimental Methodology  Use event-driven Simulator  SSD capacity : 8GB  A page size : 2KB  A block size : 64 pages  FTL algorithm : FAST  Trace : Financial, PC 11

12 Experimental Results  Average Size and Number of Evicted Blocks 12 ExLRU_S : T UC is static ( 0.1 x 10-5 ) ExLRU_D : T UC is dynamic 19.7% decrease19.1% increase

13 Experimental Results  Write and Erase Reduction in Financial trace 13 Best case 10.4% decrease Average 3% decrease

14 Experimental Results  Write and Erase Reduction in Financial trace 14

15 Parameter Sensitive Studies 15 N min : Min number of blocks of ER T UC : Max value for ER T SCAN. : Max number of blocks at scan

16 Conclusion  This scheme is designed to improve the write performance and reduce the number of erase operations  Care about diverse type of access patterns.  Exploit the page-level information and the block size 16


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