Parallel solution of American option derivatives on GPU clusters

International audienceThis paper deals with the numerical solution of financial applications, more specifcally the computation of American option derivatives modelled by nonlinear boundary values problems. In such applications we have to solve largescale 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 presentedand analyzed.Keywords: Parallel asynchronous algorithms, iterative parallel numericalmethods, subdomain method, sparse nonlinear systems, large scale obstacleproblems, finance, GPU clusters, CUD