  We provide a representation result of parabolic semi-linear PD-Es, with
polynomial nonlinearity, by branching diffusion processes. We extend the
classical representation for KPP equations, introduced by Skorokhod (1964),
Watanabe (1965) and McKean (1975), by allowing for polynomial nonlinearity in
the pair $(u, Du)$, where $u$ is the solution of the PDE with space gradient
$Du$. Similar to the previous literature, our result requires a non-explosion
condition which restrict to "small maturity" or "small nonlinearity" of the
PDE. Our main ingredient is the automatic differentiation technique as in Henry
Labordere, Tan and Touzi (2015), based on the Malliavin integration by parts,
which allows to account for the nonlinearities in the gradient. As a
consequence, the particles of our branching diffusion are marked by the nature
of the nonlinearity. This new representation has very important numerical
implications as it is suitable for Monte Carlo simulation. Indeed, this
provides the first numerical method for high dimensional nonlinear PDEs with
error estimate induced by the dimension-free Central limit theorem. The
complexity is also easily seen to be of the order of the squared dimension. The
final section of this paper illustrates the efficiency of the algorithm by some
high dimensional numerical experiments.
