Efficient Identification of Hot Data for Flash Memory Storage ...

Efficient Identification of Hot Data for Flash Memory Storage Systems

ACM Transaction on storage, Feb. 2006

JenWei Hsieh (National Taiwan University),LiPin Chang (National Chiao-Tung University),and TeiWei Kuo (National Taiwan University)

Speaker: Soyoon Lee

Hot data

• Frequently access data.• Usages

- garbage collection- performance of the flash memory access- longer lifetime ( wear leveling)

A Multihash-Function Framework- use independent multiple hash functions- reduce the chances of false identification of hot data- on-line- provide excellent performance- reduce the hash table space

Highly Efficient Method On-line Hot Data Identification!

non hot data hot data

• Garbage collection• Wear leveling• Physical/logical mapping

• lower level functionalities• read/ write/ erase

The count updating of an LBA

Hot data identifier

FTL

block write ( LBA , size ) from File

System

x

Logical Block Address x

f1(x)

f2(x)

f3(x)

f4(x)

K-dimensionalHashing Table

Hash Functions

H Most Significant Bits

+1

+1

+1

+1

y +1

The count updating of an LBA

• Freeze a counter once it reaches the maximum positive values

• Right-shift all counters for 1 bit whenever any counter is overflowed

• Exponential decaying

• When? : per decay period

• How? : the values of all counters divided by two Right-shift all counters

Count Overflow Decaying of count

The hot data identification of an LBA

Hot data identifier

FTLx

Logical Block Address x

f1(x)

f2(x)

f3(x)

f4(x)

K-dimensionalHashing Table

Hash Functions

H Most Significant Bits

block write ( LBA , size ) from File

System

Hot data H MSB of every counter of hashed values contain a

nonzero bit value

X is not hot data

Experimental setup• A Multihash-Function Framework setup

- The number of hash functions: 2 (the division method, the multiplication method)- Each counter for a hash table entry: 4 bits - hash table size: 1~8 KB

• Flash memory size: 512MB

• Traces of data access: the Hard disk of a mobile PC (a 20GB hard disk, 384MB RAM, Intel Pentium-III 800MHz)

• Comparison method- direct address method*M.L Chiang, C.H. Paul, and R.C. Chang, “Manage flash memory in personal communicate devices,” Procee

dings of International Symposium on Consumer Electronics,1997.

- two-level LRU*CHANG,L.P. AND KUO, T. W. “An adaptive striping architecture for flash memory storage systems of embed

ded systems. In Proceedings of the 8th IEEE Real-Time and Embedded Technology and Applications Symposium, 2002.

The locality in data access

• Direct address method• No false hot data identification• Decay period: 5117 writes• hot data threshold on the number of writes to an LBA: 4

Performance EvaluationHash table size vs False Identification

1 KB: basic

1 KB: enhanced

2 KB : basic

2KB enhanced,4KB basic,

8 KB enhanced

• basic: multi-hash function framework• enhanced: the framework with an enhanced counter update policy

512 flash memory, 2KB hash table 0.871% !!

Performance Evaluation

Decay period (setup: 5117 writes)

6396 writes

Performance Evaluation

Runtime Overheads

CPU Cycles per Operation (Unit: CPU Cycles)

The runtime overheads on the maintenance of the hash table (i.e., the decay process) is also limited

(e.g.,3,565 CPU cycles per 5,117 writes over 512MB flash memory).

Two – level LRU

Two-level LRU: hot data 512, candidate data 1024 nodes

Thank you!