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1、EffectiveExploitationofParallelisminNLPM.P.vanLohuizenDept.ofInformationTechnologyandSystemsDelftUniversityofTechnologyZuidplantsoen4,2628BZDelft,TheNetherlandsmpvl@acm.orgKeywords:NaturalLanguageProcessing,ParallelParsing,Fine-GrainedParallelismAbstractseenasanextrac
2、onstraintonthecontext-freeback-bone.Often,theunificationoperations(whichareTheincreasingdemandforaccuracyandrobust-similartothosefoundinProlog)arethemostcostlynessfortoday'snaturallanguageprocessingsystemspartofparsing.Basically,onecantaketwoap-bringsonanincreasingdema
3、ndforcomputingpower.proachestoparallelizingaunification-basedparser.Experimentsonourunification-basedparserindicatedFirst,onecantakeunification(andsubsumption)asthatonlyfine-grainedparallelismcouldyieldaccept-anatomicoperation,andexploittheparallelismcon-ablespeedup.Wepre
4、sentaparallelizationtechniquetainedinthecontext-freepartofparsing.Second,onetoexploitthisfine-grainedparallelism.Althoughthecouldparallelizetheunificationoperationitself.Mostapproachwasdesignedfortheparallelizationofaresearchhasfocussedontheformerapproach.unification-bas
5、edparser,mostofthecomplexityiscapturedinanindependentmodulethatcanbeusedforotherapplicationsaswell.OneofthereasonsforthischoiceisthatunificationisnotinNick'sClassandthereforegenerallyconsid-1Introductioneredtobeahardtoparallelizeproblem[1,2].In[3],however,itisshownthat
6、thispropertydoesnotmeanTheperformanceofnaturallanguageprocessingitisnotfeasibletomakeanefficientparallelunifica-(NLP)applicationshasalwaysbeenlimitedbythetionalgorithm(seealsoremarksin[4]).Thereare,speedoftheworkstationsathand.Wheneverfasterhowever,otherreasonthatmaketh
7、eformerapproachcomputersenteredthemarket,NLPapplicationsweremoreattractive.Theparallelisminherentintheuni-extendedtodealwithevenmorecomplexlinguisticficationalgorithmisveryfine-grained.Thisensuresphenomenaandanevenlargerdomainofdiscourse.thatworkcanbebalancedevenlyamong
8、stprocessors,Withtheintroductionofrobustparsingtechniquesbutalsoincreasesthepotentialoverheadofthesys-(parsingofpartiallycor