Reducing Write Amplification of Flash Storage through Cooperative - - PowerPoint PPT Presentation

1

Chungbuk National University

Reducing Write Amplification of Flash Storage through Cooperative Data Management with NVM

32nd International Conference on Massive Storage Systems and Technology (MSST) May, 2016 Eunji Lee, Chungbuk Natational University Julie Kim, Ewha University Hyokyung Bahn, Ewha University Sam H. Noh, UNIST

2

Chungbuk National University

Write Amplification in SSD

 Undesirable phenomenon associated with flash memory  Number of writes to storage is higher than the number of

writes issued by a host

 Key aspect limiting stable performance and endurance of

SSD

Source: Radian Memory Systems

Performance is fluctuating!

3

Chungbuk National University

Write Amplification in SSD

 Garbage collection is performed to recycle used blocks  Copy out valid pages in a victim block into a free block

B C D F G H write (B’ F’ G’ H’) B’ F’ G’ H’ B’ F’ G’ H’ A C D E A E write (B’ F’ G’ H’) + write (A C D E ) in GC Write 4 Blocks

Write 8 Blocks

2x Writes! Write Amplification Factor : 2.0

4

Chungbuk National University

Workload and WAF Relationship

 Analyze WAF with respect to workload characteristics  Generate two synthetic workloads using SSDsim

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

4GB 8GB 16GB 32GB 64GB

SSD Capacity

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

4GB 8GB 16GB 32GB 64GB

SSD Capacity

Random writes Sequential writes WAF

6x writes! No write amplification

Random updates incur the dispersed distribution of the valid pages

5

Chungbuk National University

Workload and WAF Relationship

 Real workload is a mixture of random and sequential

accesses

 Observe WAF varying the level of randomness

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

random r:s = 9:1 r:s = 8:2 r:s = 7:3 r:s = 6:4 r:s = 5:5 r:s = 4:6 r:s = 3:7 r:s = 2:8 r:s = 1:9 sequential

100% random 100% Sequential A low level of randomness amplifies writes! Real workloads are likely to be between two opposites

WAF

6

Chungbuk National University

NVM Technology

 Becoming increasingly viable as leading semi-conductor

manufacturers are eagerly investing in it

• Diablo Technologies, Memory 1
• All-flash system memory module
• 4TB Memory
• Intel and Micron, 3DXpoint
• All-new memory technology
• 8x-10x denser than DRAM
• 1000 times less latency than NAND

 Fast, scalable, and persistent memory is being realized in

computer systems

7

Chungbuk National University

Cooperative Data Management (CDM)

 Goal: Reduce WAF by taking advantage of non-

volatility of caches

 Using NVM as a storage cache – promising option

B C D F G H B’ F’ G’ H’ A E B C D F G H B’ F’ G’ H’ A E A C B’ D A C B’ D Volatile Cache Non-Volatile Cache Flash Storage Flash Storage

8

Chungbuk National University

Cooperative Data Management (CDM)

 In traditional systems, all valid pages in a victim

block should be copied into a free block during GC

 4 block writes !

B C D F G H B’ F’ G’ H’ A C D E A E A C B’ D Volatile Cache Flash Storage B C D F G H B’ F’ G’ H’ A E A C B’ D Non-Volatile Cache Flash Storage

9

Chungbuk National University

Cooperative Data Management (CDM)

 CDM skips the copying of valid pages in GC if the

data exist in non-volatile cache

 Only one block write!

B C D F G H B’ F’ G’ H’ A C D E A E B C D F G H B’ F’ G’ H’ E A E A C B’ D A C B’ D Volatile Cache Non-Volatile Cache Flash Storage Flash Storage NO NO NO

10

Chungbuk National University

Cooperative Data Management (CDM)

 Finite state diagram

• “Removable” state
• Can be erased if the data needs to be copied into

another block

• Or it is same as the valid state
• Data is set to “Removable” when

it is cached in a non-volatile cache

11

Chungbuk National University

Getting Real: Issues with CDM

 Implementation of CDM has several issues

depending on the architectures

 Feasible architectures

• NV-cache as a page cache in host
• NV-cache as an in-storage cache

NV-cache Flash Storage Host’s page cache DRAM-cache Flash Storage Host’s page cache NV-cache

12

Chungbuk National University

• 1. NV-cache as a host cache

 Issue 1. Consistency  Updating data in a cache touches a final copy  Crash during update results in inconsistent data

B’ F’ G’ H’ A C D E B’ F’ G’ H’ E A C B’ D A B’ D Volatile Cache Non-Volatile Cache Flash Storage Flash Storage C’ C’

crash crash

13

Chungbuk National University

• 1. NV-cache as a host cache

 Issue 1. Consistency  Solution is associated with specific file system

implementations

 Data consistency is managed in a file system layer

with different techniques

 File systems should be redesigned considering a

way of handling data in CDM

14

Chungbuk National University

Case Study: Ext4 with CDM

 Finite State Diagram  Introduce additional

states of cached data to determine whether its another copy remains in storage

 Update data with a copy-

• n-write technique if the

cached data serves as a final copy

15

Chungbuk National University

• 1. NV-cache as a host cache

 Issue 2. Communication Overhead  Events in cache and storage should be notified to

each other synchronously

• e.g., Garbage Collection, Erase of a block, Cached data

update, etc.

 Designing a new interface is no longer a big deal

• Recent packet-based interfaces like NVM-e are easy to

piggyback additional information on the original data

 However, frequent communication for additional

information transfer can be a burden

• Consider finding a way to relieve the overhead as a

future work

16

Chungbuk National University

• 2. NV-cache as an in-storage cache

 More deployable architecture  No consistency issue

• File systems assume that the data in storage can

become inconsistent if a system crashes during updates

 Not serious communication overhead

• Sharing information inside a storage

device is much cheaper and easier than synchronizing storage with a host cache

 Development can be achieved by

a single party - storage manufacturer

• No need to change file systems

DRAM-cache Flash Storage Host’s page cache NV-cache

17

Chungbuk National University

Performance Evaluation

 Trace-driven simulation with SSDsim

• Developed by MSR as an extension of Disksim
• Emulate SLC NAND Flash

18

Chungbuk National University

Performance Evaluation

 Implement the in-storage NV-cache module and

modify a storage controller to support CDM

 Compare with a NVM-basic model

• Manage NVM like a volatile cache
• Cache data on access and evict it with LRU policy

19

Chungbuk National University

Write Amplification Factor

 CDM reduces WAF by 2.1-17.6% and 4.3-38.2% in

JEDEC and OLTP workloads

20

Chungbuk National University

Response Time

 Average response time is improved by 9.7% and

20.3% on average in JEDEC and OLTP

21

Chungbuk National University

Standard Deviation of Response Time

 Reduce standard deviation of response time by

31% and 39% on average in JEDEC and OLTP

 Relieve the performance fluctuating

22

Chungbuk National University

Thank you!

 eunji@cbnu.ac.kr  http://oslab.cbnu.ac.kr