Towards parallel and distributed computing on GPU for American basket option pricing

Author

Benguigui, M. ; Baude, Francoise

fYear

2012

fDate

3-6 Dec. 2012

Firstpage

723

Lastpage

728

Abstract

This article presents a GPU adaptation of a specific Monte Carlo and classification based method for pricing American basket options, due to Picazo. Some optimizations are exposed to get good performance of our parallel algorithm on GPU. In order to benefit from different GPU devices, a dynamic strategy of kernel calibration is proposed. Future work is geared towards the use of distributed computing infrastructures such as Grids and Clouds, equipped with GPUs, in order to benefit for even more parallelism in solving such computing intensive problem in mathematical finance.

Keywords

graphics processing units; optimisation; parallel programming; pattern classification; pricing; American basket option pricing; GPU; Monte Carlo method; classification based method; distributed computing infrastructure; dynamic strategy; kernel calibration; mathematical finance; optimization; parallel computing; Computational modeling; Computer architecture; Graphics processing units; Instruction sets; Kernel; Pricing; Training; Cloud; Distributed and parallel computing; GPU; Grid; OpenCL; machine learning; mathematical finance; option pricing;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on

Conference_Location

Taipei

Print_ISBN

978-1-4673-4511-8

Electronic_ISBN

978-1-4673-4509-5

Type

conf

DOI

10.1109/CloudCom.2012.6427593

Filename

6427593