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Shuffle up and deal: accelerating GPGPU Monte Carlo simulation with application to option pricing
Author(s) -
Cassagnes Aurelien,
Chen Yu,
Ohashi Hirotada
Publication year - 2015
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3561
Subject(s) - shuffling , monte carlo method , speedup , computer science , leverage (statistics) , computational finance , general purpose computing on graphics processing units , monte carlo integration , control variates , quasi monte carlo method , parallel computing , hybrid monte carlo , algorithm , markov chain monte carlo , graphics , computer graphics (images) , artificial intelligence , mathematics , statistics , programming language
Summary In this paper, we demonstrate some speedup opportunity regarding Monte Carlo simulation on graphic processing unit architecture, with financial application. We leverage on the possibility of reducing the volume of actually generated random numbers, by replacing the generation phase with some shuffling using Compute Unified Device Architecture's built‐in shuffle instructions. We will study various shuffling patterns and duration, elect the best among them with regard to induced correlation, using Granger causality test. We will then study the accuracy and variance of results actually achieved by our general‐purpose computing on graphic processing unit shuffled Monte‐Carlo, exhibiting a computational time reduced by half while error remains marginal. Copyright © 2015 John Wiley & Sons, Ltd.