  Stochastic solutions provide new rigorous results for nonlinear PDE's and,
through its local non-grid nature, are a natural tool for parallel computation.
There are two different approaches for the construction of stochastic
solutions: McKean's and superprocesses. In favour of superprocesses is the fact
that they handle arbitrary boundary conditions. However, when restricted to
measures, superprocesses can only be used to generate solutions for a limited
class of nonlinear PDE's. A new class of superprocesses, namely superprocesses
on ultradistributions, is proposed to extend the stochastic solution approach
to a wider class of PDE's.
