  In this paper, we design a novel algorithm based on Least-Squares Monte Carlo
(LSMC) in order to approximate the solution of discrete time Backward
Stochastic Differential Equations (BSDEs). Our algorithm allows massive
parallelization of the computations on many core processors such as graphics
processing units (GPUs). Our approach consists of a novel method of
stratification which appears to be crucial for large scale parallelization. In
this way, we minimize the exposure to the memory requirements due to the
storage of simulations. Indeed, we note the lower memory overhead of the method
compared with previous works.
