Parallel solution of American option derivatives on GPU clusters

This paper deals with the numerical solution of financial applications, more specifically the computation of American option derivatives modeled by nonlinear boundary values problems. In such applications we have to solve large-scale algebraic systems. We concentrate on synchronous and asynchronous parallel iterative algorithms carried out on CPU and GPU networks. The properties of the operators arising in the discretized problem ensure the convergence of the parallel iterative synchronous and asynchronous algorithms. Computational experiments performed on CPU and GPU networks are presented and analyzed.