ABSTRACT. We study a parallel implementation on a Graphics Processing Unit (GPU) of Alternating Direction Implicit (ADI) time-discretization methods for solving time-dependent parabolic Partial Differential Equations (PDEs) in three spatial dimensions with mixed spatial derivatives in a variety of applications in computational finance. Finite differences on uniform grids are used for the spatial discretization of the PDEs. As examples, we apply the GPU-based parallel methods to price European rainbow and European basket options, each written on three assets. Numerical results showing the efficiency of the parallel methods are provided.
The researchers in REF obtained a speedup of about 18x for the doubleprecision calculations of a parallel implementation on a GPU (CUDA) of ADI timediscretization methods for European Rainbow and Basket options compared to the optimized sequential CPU computations.
A Parallel Implementation on GPUs of ADI Finite Difference Methods for Parabolic PDEs with Applications in Finance
SSRN Electronic Journal
SSRN Electronic Journal
Computer Science