Introduction to Grid Introduction to Grid ComputingComputing

Felix HagelohFelix HagelohRoberto Roberto ValentiValenti

Deployment of a Language Detector Deployment of a Language Detector Grid ServiceGrid Service

University of Amsterdam, 02-11-University of Amsterdam, 02-11-20052005

OverviewOverview IntroductionIntroduction Required StepsRequired Steps Our Service Our Service

IntroductionIntroduction The basic ideaThe basic idea Use CaseUse Case InterfaceInterface ImplementationImplementation

Problems EncounteredProblems Encountered Future WorkFuture Work ConclusionsConclusions QuestionsQuestions

IntroductionIntroduction

Our chosen task: Grid ServicesOur chosen task: Grid Services

Task Goals:Task Goals: Build a grid service. Build a grid service. Aggregate the service with another to Aggregate the service with another to

provide additional, higher-level provide additional, higher-level servicesservices

StepsSteps Get access to the systemsGet access to the systems

AuthenticationAuthentication Security issuesSecurity issues

Obtain User CertificateObtain User Certificate Obtain Host CertificateObtain Host Certificate

Implement the serviceImplement the service Create required filesCreate required files

WSDLWSDL QNamesQNames WSDDWSDD JNDIJNDI

Compile and create GAR fileCompile and create GAR file As Globus user:As Globus user:

Deploy service Deploy service Start containerStart container

But you all know this…But you all know this…

So… we jump to our service.So… we jump to our service.

Our ServiceOur Service

Our Service: IntroductionOur Service: Introduction

We were requested to implement a We were requested to implement a useful service which could be useful service which could be integrated on other servicesintegrated on other services

We are AI students so…We are AI students so…

Let’s Merge AI and Grid Computing!!Let’s Merge AI and Grid Computing!!

Our Service: The Basic IdeaOur Service: The Basic Idea

Idea: Language Detection Is a Idea: Language Detection Is a necessary first step in a multitude of necessary first step in a multitude of applicationsapplications

Useful Web Service Examples:Useful Web Service Examples: Email filteringEmail filtering Information retrievalInformation retrieval Spell checkersSpell checkers

Can also be component of an Can also be component of an aggregated grid serviceaggregated grid service

Our Service: The Basic IdeaOur Service: The Basic Idea

What about creating a Language What about creating a Language Detector on the Grid?Detector on the Grid? Training and Testing can be extremely Training and Testing can be extremely

time consuming running on a single time consuming running on a single machinemachine

Data difficult to obtain -> can be Data difficult to obtain -> can be shared on the Gridshared on the Grid Duplicate data for parallel computingDuplicate data for parallel computing

Our Service: Use CaseOur Service: Use Case

Simple Interface:Simple Interface: Receives a Receives a

piece of textpiece of text Returns a string Returns a string

indicating the indicating the languagelanguage

Our Service: Adding StatesOur Service: Adding States

Grid services can have states (as Grid services can have states (as opposed to web services)opposed to web services)

Not necessary for our service but Not necessary for our service but for the learning factorfor the learning factor

Added “dummy” states to our Added “dummy” states to our service:service: Last OperationLast Operation Times UsedTimes Used

Our Service: Statefull Use Our Service: Statefull Use CaseCase

Our Service: InterfaceOur Service: Interface

Requests and ResponsesRequests and Responses

<xsd:element name="detect" type="xsd:string" /> <xsd:element name="detectResponse“ type="xsd:string“ />  <xsd:element name="getLanguageRP">  <xsd:complexType />   </xsd:element>  <xsd:element name="getLanguageRPResponse" type="xsd:string" /> <xsd:element name="getLastOpRP">  <xsd:complexType />   </xsd:element>  <xsd:element name="getLastOpRPResponse" type="xsd:string" /> <xsd:element name="getTimesUsedRP">  <xsd:complexType />   </xsd:element>  <xsd:element name="getTimesUsedRPResponse" type="xsd:int" />

Our Service: InterfaceOur Service: Interface

Port TypesPort Types<portType name="LanguageDetectorPortType" … > <operation name="detect"> <input message="tns:DetectInputMessage" /> <output message="tns:DetectOutputMessage" /> </operation> <operation name="getLanguageRP"> <input message="tns:GetLanguageRPInputMessage" /> <output message="tns:GetLanguageRPOutputMessage" /> </operation> <operation name="getLastOpRP"> <input message="tns:GetLastOpRPInputMessage" /> <output message="tns:GetLastOpRPOutputMessage" /> </operation> <operation name="getTimesUsedRP"> <input message="tns:GetTimesUsedRPInputMessage" /> <output message="tns:GetTimesUsedRPOutputMessage" /> </operation></portType>

Our ServiceOur ServiceImplementationImplementation

Language Detection: Basic Language Detection: Basic IdeaIdea

Essentially based on probabilities of Essentially based on probabilities of character combinationscharacter combinations

Every language has typical character Every language has typical character combinations that are very frequent in combinations that are very frequent in that languagethat language ““th” in englishth” in english ““ij” in dutchij” in dutch

Easy for humans to detect a language Easy for humans to detect a language even when we don’t know that specific even when we don’t know that specific languagelanguage

Language Learning: Standard Language Learning: Standard ProcessProcess

Standard machine learning processStandard machine learning process

Language Learning: Markov Language Learning: Markov ModelsModels

Basic Markov ModelBasic Markov Model

kkthth order Markov Model order Markov Model

n

iiinssssssS

21121

|PP,...,,PP

n

iikiiknssssssssS

21121

,...,|P,...,P,...,,PP

Language Detection: Language Detection: ClassificationClassification

Transitional probabilities estimated Transitional probabilities estimated asas

ClassificationClassification

21

21

21 ,#

,,#,|P

is

iii

iii ss

ssssss

)||P(max|Pmax2,1

3cii

n

ii

cCC

LsssLSC

Language Detection: Language Detection: ExampleExample

The training text for a The training text for a language consists of language consists of the stringthe string

Learned model:Learned model:

test text

( ^^, t, 1.0 )( ^t, e, 1.0 )( te, s, 0.5 )( es, t, 1.0 )( st, , 1.0 )( te, x, 0.5 )( ex, t, 1.0 )( xt, , 1.0 )

the probability of the the probability of the stringstring

would be:would be:

test

P(test|L) = P(t|^^)*P(e|^t)*P(s|te) *P(t|es)*P(_|st) = 1*1*0.5*1*1=0.5

Language Detection: Language Detection: PerformancePerformance

60%

70%

80%

90%

100%

number of words

% c

orr

ec

tly

cla

ss

ifie

d

German 78,91 92,91 96,84 98,15 98,81

English 73,89 90,55 95,07 97,18 98,10

Dutch 68,32 88,66 94,70 97,12 98,09

one two three four five

Problems EncounteredProblems Encountered

Necessary tools had to be installed Necessary tools had to be installed (ANT)(ANT)

Problems on our machine (GRAM)Problems on our machine (GRAM) Conflicts with other teamConflicts with other team Buggy shell script to build gar fileBuggy shell script to build gar file

Sensitive to path lengths/ namesSensitive to path lengths/ names

Future WorkFuture Work

Connect with other servicesConnect with other services Make training and evaluation a grid Make training and evaluation a grid

serviceservice Make it part of a multi lingual retrieval Make it part of a multi lingual retrieval

engineengine

Web interface (interactive)Web interface (interactive)

ConclusionsConclusions

Successfully managed to create Successfully managed to create and deploy our own web serviceand deploy our own web service Broke loose from the tutorial web Broke loose from the tutorial web

service structureservice structure Merged Grid Computing with AIMerged Grid Computing with AI

Got hands on experience with Grid Got hands on experience with Grid applications and structureapplications and structure

A lot of possibilities to integrate A lot of possibilities to integrate and/or extend the implemented and/or extend the implemented serviceservice

QuestionsQuestions

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