FTL (Flash Translation Layer)

Yoon Jae Seong (yjsung@archi.snu.ac.kr)School of Computer Science and Engineering

Seoul National University

Contents

NAND flash memory characteristics

Flash Translation Layer

Mapping algorithms

Summary

2

NAND flash memory characteristics

Two faces of NAND flash memory

3

-High density -Low power consumption-Low access latency-High shock/vibration resistance-Small form factor….

-No in-place updating-Limited endurance-Bad blocks-Worsening reliability ….

FROM THE DARK NIGHT

Layered approach : Abstraction

4

NAND flash memory

Applications

Flash memory software/hardware

By overcoming the limitations of underlying flash memory

To provide the illusion of fast/reliable storage system

Flash memory software

5

Flash Translation Layer

NAND flash memory

Legacy file systems (EXT2, VFAT..)

Flash file systems (JFFS2, YAFFS..)

NAND flash interface

Block device interface

Flash-aware system software(Virtual memory, DBMS)

Block-erasePage-programPage-read

Sector writeSector read

Flash Translation Layer (FTL)

Definition A software layer that emulates the functionality of an HDD

while hiding the peculiarities of flash memory

Roles Re-mapping Wear-leveling Bad block management ……

6

Wear-leveling

Limited endurance of NAND flash memory The number of P/E (program/erase) cycles for each block is limited to 100,000 for

SLC and <10,000 for MLC

7

Wear-leveling

Bad block management

Types of bad block Initial bad blocks

Identified by a special mark at a designated location in each block

Run-time bad blocks worn-out blocks (i.e., an error returned during a program or an erase

operation)

8

Data blocks Reserved blocks

Swap

Re-mapping

9

Mapping table

NAND flash memory

LBA address spacewrite

old data

new data

(As seen by the host)

Plethora of FTLs

10

AFTL

CNFTL

JFTL

CFTL

µ-FTL

super-block scheme

Log block scheme

Replacement block scheme

DFTL

LASTFAST

Reconfigurable FTL

???

………..and so onVanilla FTL

MS FTL

LazyFTL

SFTL

Mapping granularity

Block-level mapping Page-level mapping

11NAND flash block

Logical sector address

Logical block #

Block-level mapping table

Sector # within a block

Physical block #

NAND flash block

Logical sector address

Logical page#

page-level mapping table

Sector # within a page

Physical block #

Physical page #

Block-mapping vs. Page-mapping

Block-level mapping Requires a much smaller mapping table But, at the cost of inefficient handling of small-sized writes

Page-level mapping Allows more flexible management

Efficient for small-sized writes But, requires a larger mapping table

12

Block-mapping vs. Page-mapping

In terms of mapping table size Assuming 32GB flash storage with 128KB blocks and 2KB pages

Block-mapping requires 256K mapping entries (32GB/128KB) 256K * 4B (for each mapping entry) = 1MB for mapping table

Page- mapping requires 16M mapping entries (32GB/2KB) 16M * 4B (for each mapping entry) = 64MB for mapping table

In terms of flexibility of management Block-mapping requires “data in a block” to be moved together Page-mapping requires “data in a page” to be moved together

13

What is the implication?

A simple page-mapped FTL

14

Append only

free blocks

data blocks

Garbage collection

Page-level mapping table

LBA address spacewrite

Logical page #

cc

b

b

a

a

d

d

f

f

f

Challenges in page-mapped FTLs Mapping information management

Long reconstruction time Birrell et al. “A design for high-performance flash disks”

Large memory requirement Gupta et al. “DFTL : a flash translation layer employing demand-based

selective caching of page-level address mappings”

Garbage collection overhead

15

data block

Summary page(Sequence#, LPNs of its pages)

free block

Seal

SRAM Flash Global Mapping Table

Cached Mapping Table

DFTL

Architecture

16

…… ……

Translation blocks Data-blocks

FlashTranslation page

Data-page

Volatile Memory

Cached mapping table

Global translation directory

Map entry Directory entry

Consult location of translation

pages in flash

Fetch mapping

entry Evict mapping

entry

Stores active address mapping

Tracks translation pages in flash

DFTL variants (1)

17

Convertible FTL Park et al. “a convertible flash translation layer adaptive to data

access pattern” To improve read performance of DFTL

(1) Grouping logically consecutive “cold” pages into a physical block during garbage collection and providing cached block-mapping table

(2) Exploiting spatial locality by augmenting consecutive field to cached (page) map entry

Only benefits reading sequentially written pages

Garbage collection

Physical block W

LPN i LPN i+1 LPN i+(n-1)

Physical block X

Physical block Y

Physical block Z

Logical block K

…..….. ….. …..

…..….. K W

Cached BlockMapping Table

LPN PPN Cached PageMapping Table

Consecutive

DFTL variants (2) Lazy FTL

Ma et al. “LazyFTL: A Page-level Flash Translation Layer Optimized for NAND Flash Memory

To improve crash recovery time of DFTL Cached portion of mapping table is lost when crash occurs (in DFTL)

Consistent mapping table can be recovered using logical page number recorded in the spare area of data page (but it is too slow)

18

Data region

Map region

Update Mapping Table

Update region

G.C. Host write

Flash

Global Mapping Table

Lazy update

- Contain most recent data - Maintained with small number of blocks

(Consistent mapping information at T-K)

(Most up-to-date mapping information at T)

Vanilla FTL A simplistic block-mapping FTL

19Data block Free block

New dataOld data

copy

Block-level mapping table

LBA address spacewrite

A challenge in block-mapped FTLs

Achilles´heel of block-mapped FTLs Poor small-random write performance

Due to expensive copy operations when only a part of block is modified

Write buffering schemes Temporarily store the data from the host to write buffer blocks

before block remapping is performed Various schemes have been introduced

Replacement block scheme Log block scheme Super block scheme FAST and LAST …….

20

Replacement block scheme (1)

Key idea A data block has a chain of write buffer blocks called replacement blocks Mapping within a replacement block is managed in block-level

21

data block Replacement blocks

Replacement block scheme (2)

Merge operation Is triggered when there is no free block for a replacement block gathers valid pages in a data block and write buffer blocks (replacement

blocks) to form a single complete data block

22

Replacement block scheme (3)

Problems Low utilization of replacement blocks Sequential traverse over replacement blocks during reads and writes No consideration for sequential programming constraint

23

data block Replacement blocks

Log block scheme (1)

Key idea One dedicated log block for a data block Mapping within a log block is managed in page-level

Update is performed in an append-only manner from the first page

24

Data block Log block

Write request 1

Write request 2

Write request 3

invalid

invalidinvalid

validvalidvalid

Volatile memory

Block-mapping table

Page-mapping table for each

log block

+

Logical address of a page in spare

area

Log block scheme (2)

Merge operation Is triggered when

All the pages in a log block is consumed # of free blocks is below a certain threshold

Three types of merge

25

1132

0123

Free block pool

[Full merge]Data block log block

0123

01

Data block log block

Free block pool

0123

01

Data block log block

Free block pool

23

[Partial merge] [Switch merge]

Log block scheme (3)

Log block thrashing Occurs when the number of log blocks is not enough to cover the

write working set Example scenario

There are only two log blocks in the system Workload : P1 P5 P9 P1 P5 P9 P1 P5 P9 ……

26

Data blockp4p5p6p7

p8p9p10p11

p0p1p2p3

p1Log block

p5

p9?

FAST (1)

Key idea FAST : Fully Associative Sector Translation

Fully associative mapping between data blocks and log blocks Mapping within a log block is managed in page-level as in log block

scheme (referred to as BAST : Block Associative Sector Translation)

27

data block X data block Y data block Z

Log block A

Write 1Write 2

Write 3

Log block B

Write 4Write 5

FAST (2)

Two different types of log block Sequential log block and random log block

28

01234567

01234567

Sequential log blockdata block21

Random log block1617181920212223

data block

Sequentiality detect algorithm

Task 1 Task 2Sequential write request(LPN 0,1,2,3,4,5,6,7)

Random write request(LPN 21), (LPN 145)

O/S (File System)

Mixed write request(LPN 0,1,2,3,21,4,5,6,145,7)

Switch merge

Full merge

FAST (3)

Pros Higher utilization of log blocks when merged Delayed merge operation

increases the probability of page invalidation

29

Data blockp4p5p6p7

p8p9p10p11

p0p1p2p3

p1p5

Log block

p9p1

p5p9p1p5

Workload : P1 P5 P9 P1 P5 P9 P1 P5

FAST (4)

Cons Slower address translation time

Due to full scan of page(sector)-level mapping table Excessive overhead for a single log block reclamation

Severely skewed performance depending on the number of data blocks involved in a log block

30

log block data blocks

Reconfigurable FTL

Key idea A log block is shared only by a set of adjacent data blocks, called a

super-block

31

N data blocks

Super-block

… …

K log blocks M log blocks

N data blocks

Chameleon

Key idea Garbage collection among random log blocks as an

alternative to full merge operation

32

Garbage collection

Random log blocks

Merge

Data blocks

LAST : Locality-Aware Sector Translation

Key idea Hot/cold partition in random log blocks

Increase the probability of page invalidation in hot partition

33

Figures from LAST : Locality-Aware Sector Translation for NAND Flash Memory-Based Storage Systems by Lee et al.

Effect of hot/cold partitioning in LAST

34

Evolution of block-mapped FTLs

35

Vanilla FTL

Replacement block scheme

Log block scheme(BAST)

FAST

Reconfigurable FTL

Chameleon LAST

AFTL

[Non-volatile write buffering]

[Volatile write buffering]

BPLRU

HYDRA

Summary

Three primary roles of FTL Re-mapping Wear-leveling Bad block management

Mapping algorithms Page-level mapping Block-level mapping

Various write buffering schemes Hybrid mapping

36

To provide fast and reliable flash storage