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Article Dans Une Revue SIAM Journal on Scientific Computing Année : 2016

Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs

Résumé

In this paper, we design a novel algorithm based on Least-Squares Monte Carlo (LSMC) in order to approximate the solution of discrete time Backward Stochastic Differential Equations (BSDEs). Our algorithm allows massive parallelization of the computations on multicore devices such as graphics processing units (GPUs). Our approach consists of a novel method of stratification which appears to be crucial for large scale parallelization.
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Dates et versions

hal-01186000 , version 1 (27-08-2015)

Identifiants

Citer

Emmanuel Gobet, Jose Lopez-Salas, Plamen Turkedjiev, C. Vázquez. Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs. SIAM Journal on Scientific Computing, 2016, 38 (6), pp.C652-C677. ⟨10.1137/16M106371X⟩. ⟨hal-01186000⟩
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