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POOL VS. ISLAND BASED EVOLUTIONARY ALGORITHMS: AN INITIAL EXPLORATION J.J. Merelo 1 , A.M. Mora 1 , C.M. Fernandes 1 , Anna Esparcia-Alcázar 2 , J.L.J. Laredo 3 University of Granada 1 S2 Grupo 2 University of Luxembourg 3

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Page 1: Sofea

POOL VS. ISLAND BASED EVOLUTIONARY ALGORITHMS: AN INITIAL EXPLORATION

J.J. Merelo1, A.M. Mora1, C.M. Fernandes1, Anna Esparcia-Alcázar2,

J.L.J. Laredo3

University of Granada1

S2 Grupo2

University of Luxembourg3

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Scope

• EAs are optimization algorithms

• Typically running in single sequential computers

OR

• Parallel symetric computers

• Proof of Concept (PoC)

• Pool-based EAs (Shared Memory: here CouchDB)

• OneMax:

• Evaluation time (small)

• Concurrent access (big)

• Small number of clients

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Outline

• Introduction

– Evolutionary Algorithms (EAs)

– Pool and Island EAs on CouchDB (SofEA)

– CouchDB

• Analysis of results

– Improving baseline

– SofEA: Island vs. Elite

– Scalability

• Conclusions

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Introduction

EA

SofEA

CouchDB

Bio-inspired optimization methods based on population

1 0 0 1 1 1 1 1 1 1

1 0 1 1 0 0 1 0 0 1

1 0 0 1 1 1 0 1 1 1

1 0 0 0 1 0 0 0 0 0

1 0 0 0 0 0 0 1 1 1

14)( xf

25)( xf

10)( xf

8)( xf

4)( xf

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Introduction

Selection

Bio-inspired optimization methods based on population

1 0 0 1 1 1 1 1 1 1

1 0 1 1 0 0 1 0 0 1

1 0 0 1 1 1 0 1 1 1

1 0 0 0 1 0 0 0 0 0

1 0 0 0 0 0 0 1 1 1

14)( xf

25)( xf

10)( xf

8)( xf

4)( xf

EA

SofEA

CouchDB

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1 0 0 1 1 1 1 1 1 1

Introduction

Selection

Recombination

Bio-inspired optimization methods based on population

1 0 1 1 0 0 1 0 0 1 14)( xf

25)( xf

1 0 1 1 0 1 1 1 1 1 30)( xf

1 0 1 1 0 1 0 1 1 1 29)( xf

EA

SofEA

CouchDB

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Block

Introduction

EA

SofEA

CouchDB

BaseSofEA

1 Step EA

• Persistance

• Resilience

• Asynchrony

CouchDB

Page 8: Sofea

Block

Introduction

EA

SofEA

CouchDB

BaseSofEA

1 Step EA

Block

EliteSofEA

1 Step EA

• Persistance

• Resilience

• Asynchrony

• Reducing the design space

CouchDB

CouchDB

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•D

ecre

asin

g C

om

mu

nic

atio

ns

Block

Introduction• Persistance

• Resilience

• Asynchrony

EA

SofEA

CouchDB

BaseSofEA

1 Step EA

Block

EliteSofEA

1 Step EA

Block

IslandSofEA

25 Steps EA

• Reducing the design space

CouchDB

CouchDB

CouchDB

Page 10: Sofea

Introduction

EA

SofEA

CouchDB

• Document-oriented STORE

• Stores Key-Documents pairs

• Map/Reduce requests using JavaScript

• API RESTfull with JSON

Olainberg at Flickr

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Analysis of results

Improving baseline

SofEA: Island vs. Elite

Scalability

• Running times:

• EliteSofEA vs. BaseSofEA

• Block size:

• BaseSofEA: 128

• EliteSofEA: 128, 32

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Analysis of results

Improving baseline

SofEA: Island vs. Elite

Scalability

• 1 to 8 clients

• Population 256

• Algorithmic performance:

• Evaluation-to-solutions:EliteSofEA vs. IslandSofEA

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Analysis of results

Improving baseline

SofEA: Island vs. Elite

Scalability

Algorithm 1 Client(1x256)

8 Clients(8x32)

Speed-up

EliteSofEA 30.43 12.19 2.5

IslandSofEA 2.067 1.173 1.7

• Running times: EliteSofEA vs. IslandSofEA

• Speed-up: EliteSofEA vs. IslandSofEA

• EliteSofEA accesses 25 more times CouchDB

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Conclusions

• SofEA: Persistent, Asynchronous, Resilient pool-based EA

• PoC: It finds the optimum, it scales, it works!!

• Future works:

• Limit of scalability on time-consuming problems

• Latency/computation decreases

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THANKS FOR YOUR ATTENTION!!