EMSOFT 09 Yangwook Kang Ethan L. Miller Hongik Univ UC Santa Cruz 2009/11/09 Yongseok Oh

Transcription

1 RCFFS : Adding Aggressive Error Correction to a high-performance Compressing Flash File System EMSOFT 09 Yangwook Kang Ethan L. Miller Hongik Univ UC Santa Cruz 2009/11/09 Yongseok Oh ysoh@uos.ac.kr 1

2 Index Introduction Related Work Design Implementation Evaluation Future Work Conclusions 2

3 Introduction NAND Flash Memory High performance Low power consumption Shock resistance SLC(Single Level Cell) Higher cost Smaller capacity Write endurance 100k MLC(Multi Level Cell) Lower cost Larger capacity Write endurance 5k-10k 3

4 Current Problem of Flash File System Reliability MLC flash chips has become larger. The reliability of flash memory has decreased. Many flash controllers can detect 2 bit errors and correct 1 bit error per bytes. Space efficiency Internal fragmentation Data size is smaller than page size. Slow mount YAFFS and JFFS2 do not have on-flash index structures(scalability). They scan the flash media to build an index structure during the mounting process. 4

5 Introduction RCFFS (Reliable Compressing Flash File System) Reliability Space efficiency Fast mount 5

6 Related Work Flash Based File Systems JFFS2 Node based Log-structured File System in memory index UBIFS Wandering tree to support the on flash index YAFFS2 In memory index CFFS Reducing mount time ScaleFFS Multi-gigabyte flash memories u-tree Enhanced B+tree 6

7 YAFFS Architecture - Mount time - Scalability problem DRAM NAND Scan In memory yaffs_object Header page page Header page page Header page page On flash spare spare spare spare spare spare spare spare spare Load yaffs_object *parent yaffs_object sibling *parent yaffs_tnod yaffs_object sibling e *parent yaffs_object yaffs_tnod sibling yaffs_tnod e *parent sibling e yaffs_tnode yaffs_object *parent sibling children yaffs_object

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9 Related Work Error Detection and Correction Derivative of Hamming code Simple Low requirements Computation power and space Hamming code used in flash memories are limited Detecting 2-bit errors Correcting single-bit errors per 256 or 512 bytes. Thus, our approach leverages Galois field-based Reed-Solomon codes at the page level to correct entire pages that are found to have errors. This approach has long been used in RAID systems. 9

10 Terms Reed Solomon error correction is an errorcorrecting code that works by oversampling a polynomial constructed from the data. Reed Solomon codes are used in a wide variety of commercial applications, most prominently in DVDs and Blue-ray Discs, in data transmission technologies such as DSL & WiMAX, in broadcast systems such as DVB and ATSC, and in computer applications such as RAID 6 systems. 10

11 Related Work Compression Burrows, et al. provided on-line data compression in a diskbased log structured file system. Similarly, JFFS2 and UBIFS both provide compression. However, neither can utilize the remaining space in a page. 11

12 Design The primary design goal of RCFFS Reliability Reed-solomon code Space efficiency Packing more data into page On-line data compression u-tree Performance 12

13 RCFFS Structure RCFFS stores data and meta data in a log-structure. It uses write-back to gather dirty data in the segment buffer. When is the segment buffer flushed? the segment buffer is full. a timeout threshold is reached. It writes out all modified data,u-tree and segment summary. Maintaining two kinds of index structures. The first index is to look up the physical location of a file block given an inode number. (u-tree) The second index is a reverse index for cleaner 13

14 Segment 14

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17 RCFFS Reliability Typically, this ECC can detect two bit errors and correct one bit error per bytes. Small spare area Complexity To detect errors It stores an algebraic signature in the spare area. To correct error It also maintains extra pages that contain parity or Reed- Solomon redundancy in data and metadata pages. 17

18 RCFFS Reliability When the computed signature of the contents of a page than has been read does not match the stored signature, RCFFS notices the corruption and first tries to use the parity page from the erase block to correct the error. This correction is similar to that used in a RAID system: the erroneous page is marked as missing, and the RAID algorithm regenerates it by combining the remaining pages in the erase block, including the parity pages. If an erase block has k parity pages, the file system can recover locally from errors in k different pages regardless of the number of bit errors within each page. If, however, there are too many faulty pages in the erase block, the file system must read the entire segment and use both the data blocks and segment-wide Reed- Solomon blocks to recover the corrupted pages. RCFFS takes advantages of high level error correction 18

19 Fast Mounting Most flash file systems require a scan to locate the metadata information. Scanning time depends on the media size. To reduce scanning time, YAFFS writes RAM summary into flash. However, this approach works after a normal shutdown; system crashes still require a full scan. 19

20 Fast Mounting RCFFS uses pre-allocating segments and writing the locations of the next k segments. At mount time, RCFFS reads the segment info area from the first segment on the flash memory and retrieves the location of next k segments. It then quickly jumps to the kth segment in the list and checks to see if the segment is newer than the current one by comparing the timestamp. Finally, it finds u-tree root node. 20

21 Improving Space Efficiency Two approach To remove internal fragmentation from pages. Current most flash file system use a page, 2-4KB Compression In RCFFS, a page can have multiple data chunks by modified u-tree. <pagenumber, pageoffset, size> tuple instead of the page number. It uses a block compressor such as that in the LZO and deflate algorithm. It can take 4KB page as an input. 21

22 Terms Lempel-Ziv-Oberhumer (LZO) is a lossless data compression algorithm that is focused on decompression speed. Deflate is a lossless data compression algorithm that uses a combination of the LZ77 algorithm and Huffman coding. 22

23 Implementation RCFFS was implemented on Fedora core 9(Linux kernel ) using NANDsim. Modified u-tree for index key/value pair Key Inode number Index number Flag 32bit 31bit 1bit Value Physical address Offset Length 32bit 16bit 16bit LRU cache 23

24 Implementation RB-tree(Red-Black) Dirty data is collected. I/O queue sorted by physical page number. LZO compression algorithm in Linux kernel. 24

25 Evaluation Experiment Environment Machine Virtual Machine CPU Single CPU RAM 512MB Hard Disk 20GB NANDsim 128MB Block Size 128KB Page Size 2KB Segment Size 2MB Mounting time File I/O Performance Reliability 25

26 Mounting Time Recently versions of YAFFS writes a RAM summary before shutting down, a process called checkpointing. Two files systems have similar mounting times. However, when a failure occurs, YAFFS still must scan the media, a process that can take several seconds. In contrast, RCFFS only needs to scan the pages in a single segment. 26

27 Mounting Time 27

28 FILE I/O Performance RCFFS can take advantages write-back compression fragment avoidance RCFFS nocomp occupies more than twice as much space as RCFFS comp. The added overhead of computing parity pages is seen in write performance. However, reads in RCFFS are comparable to YAFFS; the computation of algebraic signatures for verification do not significantly slow down page reads. 28

29 FILE I/O Performance Seltzer s large file benchmark computing parity overhead and meta data?? read cache effect decompression 29

30 FILE I/O Performance Small file benchmark a 5KB file a thousand times and shuts down the file system. On average, YAFFS takes seconds and RCFFS comp takes seconds to complete this benchmark; the two file systems show similar performance. 30

31 FILE I/O Performance Postmark RCFFS outperforms YAFFS by a factor of

32 Reliability Three kind of flash errors First, we generated up to 1000 random bitflip errors per page. Second, we generated some pages that lose data due to page failure. Finally, we terminated the file system during a write to emulate power failure. 32

33 For random bitflip NAND ECC only provides 1bit error correction. RCFFS recovered all error pages. Recovery of a corrupted page ms. Segment-wide parity block - 57ms. Sufficient error recovery performance. 33

34 Future Work Garbage collector Consistency checker Compressing u-tree u-tree s maximum height, which limits scalability 34

35 Discussion High CPU Performance Benchmark generates simple patterns. Compression is not effective for JPEG and MPEG files. Delayed Write(Write-back) Write buffer size is 2MB. YAFFS - Write-through FTL employed this approach 35

36 Conclusion High-level reliability with Galois field-based signatures and parity and Reed-Solomon redundancy pages. Space efficiency using compression. Fast Mounting with Next-k-algorithm and On-flash index 36

37 Questions? The end. 37