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




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1 CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique 2 Department of Mathematics, Faculty of Informatics, Universidade da Coruna

Abstract : 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.

Keywords : parallel computing em-pirical regressions Backward stochastic differential equations dynamic programming equation GPUs CUDA





Autor: Emmanuel Gobet - Jose Lopez-Salas - Plamen Turkedjiev - Carlos Vasquez -

Fuente: https://hal.archives-ouvertes.fr/



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