  The Classic Howard's algorithm, a technique of resolution for discrete
Hamilton-Jacobi equations, is of large use in applications for its high
efficiency and good performances. A special beneficial characteristic of the
method is the superlinear convergence which, in presence of a finite number of
controls, is reached in finite time. Performances of the method can be
significantly improved by using parallel computing; how to build a parallel
version of method is not a trivial point, the difficulties come from the strict
relation between various values of the solution, even related to distant points
of the domain. In this contribution we propose a parallel version of the
Howard's algorithm driven by an idea of domain decomposition. This permits to
derive some important properties and to prove the convergence under quite
standard assumptions. The good features of the algorithm will be shown through
some tests and examples.
