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Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs
| dc.contributor.author | Gobet, Emmanuel | |
| dc.contributor.author | López Salas, José Germán | |
| dc.contributor.author | Turkedjiev, Plamen | |
| dc.contributor.author | Vázquez, Carlos | |
| dc.date.accessioned | 2024-07-18T07:57:13Z | |
| dc.date.available | 2024-07-18T07:57:13Z | |
| dc.date.issued | 2016-06 | |
| dc.identifier.citation | E. Gobet, J. G. López-Salas, P. Turkedjiev, y C. Vázquez, «Stratified Regression Monte-Carlo Scheme for Semilinear PDEs and BSDEs with Large Scale Parallelization on GPUs», SIAM J. Sci. Comput., vol. 38, n.o 6, pp. C652-C677, ene. 2016, doi: 10.1137/16M106371X | es_ES |
| dc.identifier.issn | 1064-8275 | |
| dc.identifier.issn | 1095-7197 | |
| dc.identifier.uri | http://hdl.handle.net/2183/38128 | |
| dc.description | ©2016 This version of the article has been accepted for publication, after peer review, but is not the version of record and does not reflect postacceptance improvements, or any corrections. The version of record is available online at: https://doi.org/10.1137/16M106371X | es_ES |
| dc.description.abstract | [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. | es_ES |
| dc.description.sponsorship | This research is part of the Chair Financial Risks of the Risk Foundation, the FiME Laboratory and the ANR project CAESARS (ANR-15-CE05-0024). This research is supported the Chair Financial Risks of the Risk Foundation and of the FiME Laboratory. J. G. López-Salas has been partially funded by Spanish Grant MTM2013- 47800-C2-1-P. | es_ES |
| dc.description.sponsorship | France. Agence Nationale de la Recherche; ANR-15-CE05-0024 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Society for Industrial and Applied Mathematics (SIAM) | es_ES |
| dc.relation | Info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2013-47800-C2-1-P/ES/MODELADO MATEMATICO, ANALISIS Y SIMULACION NUMERICA DE PROBLEMAS EN FINANZAS Y SEGUROS, PROCESOS INDUSTRIALES, BIOTECNOLOGIA Y MEDIOAMBIENTE | es_ES |
| dc.relation.uri | https://doi.org/10.1137/16M106371X | es_ES |
| dc.subject | Backward stochastic differential equations | es_ES |
| dc.subject | Dynamic programming equation | es_ES |
| dc.subject | Em-pirical regressions | es_ES |
| dc.subject | Parallel computing | es_ES |
| dc.subject | GPUs | es_ES |
| dc.subject | CUDA | es_ES |
| dc.title | Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs | es_ES |
| dc.type | info:eu-repo/semantics/article | es_ES |
| dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
| UDC.journalTitle | SIAM Journal on Scientific Computing | es_ES |
| UDC.volume | 38 | es_ES |
| UDC.issue | 6 | es_ES |
| UDC.startPage | 652 | es_ES |
| UDC.endPage | 677 | es_ES |
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