@Article{Supelec815,
author = {Lokman Abbas-Turki and Stephane Vialle and Bernard Lapeyre and Patrick Mercier},
title = {{Pricing derivatives on graphics processing units using Monte Carlo simulation}},
journal = {Concurrency and Computation: Practice and Experience},
year = {2012},
doi = {http://dx.doi.org/10.1002/cpe.2862},
abstract = {This paper is about using the existing Monte Carlo approach for
pricing European and American contracts on a state-of-the-art
graphics processing unit (GPU) architecture. First, we adapt on a
cluster of GPUs two different suitable paradigms of parallelizing
random number generators, which were developed for CPU clusters.
Because in financial applications, we request results within
seconds of simulation, the sufficiently large computations should
be implemented on a cluster of machines. Thus, we make the
European contract comparison between CPUs and GPUs using from one
up to 16 nodes of a CPU/GPU cluster. We show that using GPUs for
European contracts reduces the execution time by\ \∼\ 40 and
diminishes the energy consumed by\ \∼\ 50 during the simulation. In
the second set of experiments, we investigate the benefits of
using GPUs’ parallelization for pricing American options that
require solving an optimal stopping problem and which we
implement using the Longstaff and Schwartz regression method. The
speedup result obtained for American options varies between two
and 10 according to the number of generated paths, the
dimensions, and the time discretization.}
}