jürgen lambrecht– desics © imec 2002 multi-objective refinement of mapping tables in telecom...

Jürgen Lambrecht– DESICS© imec 2002

Multi-objective refinement of Mapping Tables in

Telecom Network Applications

Jürgen Lambrecht, Chantal Ykman-Couvreur, Armin van der Togt,

Francky CatthoorThe Protocol Processor Project (PRO3)

Contract No IST-1999-11449

Jürgen Lambrecht – DESICS© imec 2002

Outline

Introduction Context Example: network switch Related Work Our contribution

Design space and Method Mapping table implementations: primitives Primitives characteristics Mapping table implementations: multi-layer Exploration Method System Level Cost Factors

Results Multi Objective Exploration Impact of network Impact of operation characteristics

Future work and Conclusions


Context

Data type refinement

Mapping tables

Application domain: telecom network, database, multimedia, ...

Design Technology for Integrated Information and Communication Systems

Memory system: bottleneck

Methodology: system level specification optimised embedded implementation


Example: network switch

port 1

Port 2

x2 5Y2 1

Y2 5x4 7

ATMMUX

ATMMUX

2 = 0000 0010

2 = 0000 0010

5 = 0000 0000 0000 0101

1 = 0000 0000 0000 0001

1 = 0000 0001

1 = 0000 0001

4 = 0000 01007 = 0000 0000 0000 01112 = 0000 0010

2 = 0000 00105 = 0000 0000 0000 01012 = 0000 0010

Key1 ( VPI[8] ) Key3 ( port[8] ) { VPI, VCI, port } [32]Key2 ( VCI[16] )Table (with active

connections)16 284 MB


Related Work

Programming theory STL

SETL

Embedded systems imec - Wuytack et al. 1996

Design space characterisation for mapping tablesPreliminary exploration and optimisation method

imec - Ykman et al. ISSS 1999

Extended design space (key merging/splitting)Improved cost function


Our contribution

Area

Power

Objective trade-off

With all relevant application characteristics

Automated fast exploration and optimisation

simulates the application

collects profiling info

runs the tool

pareto curves resultGoal:

optimised implementation

trade-off multiple objectives

taking all relevant system characteristics into account


Outline






Mapping table implementations: primitives

keydata

keydata

keydata

Linked List (LL) keydata

Array (AR)

data

data

data

data

Pointer Array (PA)

data

data

data

data


Primitives' characteristics

50 Kb M acc/sec mW sec0

25

50

75

100

125

150

175

200

225

250

275

300

325

AR

PA

LL


Mapping table implementations: multi-layer

Lay

er 1

key1key1key1key1

LL(7)

Lay

er 2

PA(4)2 4

Lay

er 3

AR(3)

data

data

data

data

data

data

data


Exploration method

Key ordering

Key hashing

Key concatenation

Key splitting

2 = 0000 0010

2 = 0000 0010

5 = 0000 0000

0000 0101

1 = 0000 0000

0000 0001

1 = 0000 0001

1 = 0000 0001

4 = 0000 0100

7 = 0000 0000 0000 0111

2 = 0000 0010

2 = 0000 0010

5 = 0000 0000 0000 0101

2 = 0000 0010

Key1 ( VPI[8] ) Key3 ( port[8] ) { VPI, VCI, port } [32]Key2 ( VCI[16] )

port 1

Port 2

x2 5Y2 1

Y2 5

x4 7

ATMMUX


Exploration method

Key ordering

Key hashing

Key concatenation

Key splitting

Assignment of primitivesCost vector calculation

Lay

er 1

key1key1key1key1

LL(7)L

ayer

2

PA(4)24

Lay

er 3 AR(3)

data

data

data

data

data

data

data


System Level Cost Factors

Application characteristics

Data: size, average number

Keys: size, average number, dependencies, frequency distributions

Operations: accesses and proportion

AR(3)

data

data

data

data

data

data

data

PA(4)24

Memory cost Area: bits Performance: accesses Power: vendor model


Outline






Multi Objective Exploration

DifferenceFactor

2 in size5 in power

8 in accesses2 in performance


Impact of network


Impact of operation characteristics


Future work

Better memory library Off-chip memory support

On/Off-chip partitioning

Include fixed platforms (w. caches…)

Further automation

New primitive data structures Internet multimedia data sets Trees


Conclusions

Bottleneck in embedded system synthesis: memory performance, area, and power

our focus: Mapping Tables

Optimisation at system level

Automated method needed Multi-objective exploration All relevant application characteristics Fast Power-objective result

90% area savings80% power savingswithout decreasing the performance


www.imec.beWorldwide collaboration with more than 450 companies and institutes.

IMEC – Kapeldreef 75 – B-3001 Leuven – Belgium – Tel. +32 16 281211 – Fax +32 16 229400 – www.imec.be


Dynamic

Memory

Mngnt.

Physical

Memory

Mngnt.

VirtualMemory

Segments

Selecteddata

structures

PhysicalMemories

ADT Abstract Data TypeRefinement

Virtual memory mngntRefinement

Physical memory mngntRefinement

Memory Management in Matisse


Exploration and Optimization

Power

Layers

20,000

2,000

200

100

1,000

10,000

1 2 3 4

jürgen lambrecht– desics © imec 2002 multi-objective refinement of mapping tables in telecom...

Documents