MEMS Based Storage Architecture for Relational Databases

Arjun SureshS7, R

College of Engineering Trivandrum

MEMS-based storageRelational database layoutFRM (Flexible Retrieval Model) Query Processing on FRMEvaluationConclusion

Outline

Building Storage on MEMSMEMS are Micro Electrical Mechanical Systems.

Basic functions: sensors and actuators

Built by standard silicon processing

Combine mechanical and electrical components

Enable “systems-on-a-chip”

Why need MEMS-based storage? Huge gaps between disks and RAM

1000,000 latency gap (10ms vs 50 ns), widening 50% yearly.

1000 price gap per byte 1000 life gap

MEMS narrows gaps 10X smaller latency than disk 100X cheaper than RAM in the range 1 – 10 GB 100 MB - 1 GB/s bandwidth 10 GB capacity with a penny size

Desired for energy and volume critical systems

EEPROM/Flash

DRAM

Hard Disk

Latency

Cos

t p

er B

yte

MEMS-based Storage

Technology Trends

Using pits in the polymers made by tip heating to store data

IBM Millipede

MEMS Storage Architecture

Read/writetips

Read/writetips

MediaMedia

Bits storedunderneatheach tip

Bits storedunderneatheach tip

side view


Media Sled

X

Y

Springs Springs

SpringsSprings


Anchors attachthe springs tothe chip.

Anchors attachthe springs tothe chip.

Anchor Anchor

AnchorAnchor

X

Y


Sled is freeto move

Sled is freeto move

X

Y


Sled is freeto move

Sled is freeto move

X

Y


Springs pullsled towardcenter


X

Y


X

Y




Actuators pullsled in bothdimensions


Actuator

Actuator

Actuator

X

Y




X

Y




X

Y




X

Y




X

Y


Probe tipsare fixed

Probe tipsare fixed

Probe tip

Probe tip

X

Y


X

Y

Probe tipsare fixed

Probe tipsare fixed


X

Y

Sled onlymoves overthe area of asingle rectangle

Sled onlymoves overthe area of asingle rectangle

One probe tipper rectangle

One probe tipper rectangle

Each tipaccesses dataat the samerelative position

Each tipaccesses dataat the samerelative position


Properties of MEMS Storage

Sweep area of

One probe tip

Properties of MEMS Storage

N bits

M b

its

One tip region

One tip sector

Physical Parameters

Number of tips 6400

Max number of active tips 1280

Tip sector size 8 bytes

Bits per tip region 2000X2000

X axis settle time 0.125ms

Average turnaround time 0.06ms

Existing Work on Integration of MEMS StorageSolution proposed by CMU researchers

Mapping MEMS storage into conventional diskAdapt I/O scheduling and data placement to

MEMS

Preliminary study showsReduce the I/O stall times by 4 to 74 times over

disksImprove the overall application run times by

1.9 to 4.4Reduce the energy consumption by 10-54 times

Better solutions??The approach of mapping MEMS into disk

Simplify the procedure of integration of MEMSDoes not consider the physical properties of

MEMS

Relational Data Placement

StudentGrade

recordIDname

char(16)

perm ID

int(8)

age

int(8)

grade

int(8)

record1 Mary 572 19 86

record2 John 582 18 90

record3 Bob 511 18 80

record4 Jane 537 20 91

N-ary Storage Model (NSM)

Store records in a relation in slotted disk pages

Organize records sequentially on the disk pages

Page Header Mary 572

19 86 John 582

18 90 Bob 511

18 80 Jane 537

20 91

P4 P3 P2 p1

Decomposition Storage Model(DSM)

Divide a relation into sub-relations based on the number of attributes

Each sub-relation corresponds to each attribute

Each sub-relation is organized into pages in the same way as NSM

Page Header 1 Mary 2

John 3 Bob 4 Jane

P4 P3 P2 P1

Page Header 1 572 2

582 3 511 4 537

P4 P3 P2 P1

Page Header 1 19 2

18 3 18 4 20

P4 P3 P2 P1

Page Header 1 86 2

90 3 80 4 91

P4 P3 P2 P1

grade

name perm ID

age

A disk page A disk page

A disk page A disk page

Partition Attributes Across (PAX)Within each page, PAX

groups all values of each attribute into a mini-page

A page is divided into mini-pages based on the number of attributes

It stores the same data as NSM in each page

Page Header Mary John

Bob Jane

P4 P3 P2 P1

572 582 511 537

P4 P3 P2 P1

19 18 18 20

P4 P3 P2 P1

81 90 80 91

P4 P3 P2 P1

A disk page

Common Workload RequirementsRelational data should be compatible with

OLTP workloads Due to the update characteristics, relations need to

be accessed in a row-wise mannerOLAP workloads

Only a subset of attributes is of interest, data placement should facilitate data retrieval on a column-wise fashion

Flexible Retrieval Model (FRM)

Facilitates data retrieval in both row-wise and column-wise mannerRetrieves the relevant subsets of the relationsUses two dimensional layout of MEMS storage

Improves the I/O utilizationMaximize the concurrent tips to only retrieve the

necessary data

It is also cache-friendlyUse intra-record locality

FRM Data Placement and Retrieval

Given a relation with three attributes, the size of each attribute is 8 bytes

Placing this relation in 4x4 MEMS-based storage

4 concurrent tips

(0, 0)

(0, 1)

(0, 0)

(0, 1)

Attr1 Attr2 Attr3

(0, 0)

(0, 0)

(0, 1)

(0, 1)

(0, 2)

(0, 2)

(0, 2)

(0, 2)

(1, 2)

Query Processing on FRMSelection and projection without index

Two-dimensional table scanSelection and projection with index

Encode data position as 4-tuple (tip-x, tip-y, offset-x, offset-y)

JoinsIndex-based or hash

Experiment SetupMEMS storage: 1280 concurrent tips out of

6400 total tipsPentium II Celeron 433X2 processorsL1 cache:16KB, 32-byte cache line, 20 ns

delayL2 cache:128KB, 32-byte cache line, 200

ns delayA relation R with 1.28 million recordsSixteen 8-byte attributes in each recordQueries:

SELECT A1, A2,…, An

FROM R WHERE A1 > Bound;

Memory utilization

The selected attributes in queries

Con

sum

ed m

emor

y(M

B)

I/O performance

NSM and PAX have the same I/O time

I/O time of FRM is proportional to the size of retrieved attributes

Selection Queries (2 attributes)

Cache Utilization

Selection Queries (13 attributes)

Selectivity = 50%

Projection Queries

Selectivity =10%

Conclusion and Future Work

Proposed a relational data placement scheme for MEMS-based storageTake advantage of two-dimensional MEMS access

featureArrange MEMS rows and columns to relational

attributes and recordsSave IO cost and improve cache performance

Other cache friendly techniques for MEMS-based storage devices are to be explored

Thank You……

Documents

MEMS Based Storage Architecture for Relational Databases