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基于异构众核架构的BSDE期权定价并行算法研究.docx

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基于异构众核架构的BSDE期权定价并行算法研究 Title:ResearchonParallelAlgorithmforPricingBSDEOptionsBasedonHeterogeneousMany-coreArchitecture Abstract: Inrecentyears,thepricingoffinancialderivatives,particularlyoptions,hasbecomeanessentialtopicinthefieldofquantitativefinance.BackwardStochasticDifferentialEquations(BSDEs)haveemergedasapopularmathematicalframeworkforthevaluationofoptionsduetotheirflexibilityandabilitytoincorporatemarketuncertainties.However,duetothecomplexityandhighdimensionalityofBSDEs,theirnumericalsolutionrequiressignificantcomputationalresources.ThisresearchaimstoexploreanddevelopaparallelalgorithmforpricingBSDEoptionsbyleveragingthepowerofheterogeneousmany-corearchitectures. 1.Introduction: Theaccuratepricingoffinancialderivativesiscrucialforeffectiveriskmanagementandinvestmentdecision-making.BSDEshavedemonstratedgreatpotentialinsolvingpricingproblemsduetotheirbackwardtimeevolutionandabilitytocapturemarketuncertainties.WhiletraditionalcomputationalmethodshavebeenusedtosolveBSDEs,theirsequentialnaturelimitstheirperformance.Therefore,itisimperativetoinvestigateanddevelopparallelalgorithmsthatcanexploitthecomputationalpowerofheterogeneousmany-corearchitectures. 2.LiteratureReview: ThissectionprovidesanoverviewofexistingresearchinthefieldofBSDEoptionpricingandparallelcomputing.IthighlightsthechallengesassociatedwithsolvingBSDEs,suchashighdimensionality,non-linearity,andcomputationalcomplexity.Furthermore,theliteraturereviewdelvesintovariousparallelcomputingparadigmsandalgorithms,includingGPUcomputing,FPGAacceleration,anddistributedcomputing,thathavebeenappliedtofinancialderivativepricing. 3.Methodology: TheproposedmethodologyfocusesonleveragingtheinherentparallelismofBSDEsolutionalgorithmsinaheterogeneousmany-corearchitecture.Thisinvolvesbreakingdowntheproblemintosmallersub-problemsthatcanbesolvedconcurrentlyacrossmultiplecoresorprocessingunits.Thespecificparallelcomputingparadigms,suchasOpenCLorCUDA,willbeanalyzedandchosenbasedontheirsuitabilityforthegivenheterogeneousma