  Multiscale and inhomogeneous molecular systems are challenging topics in the
field of molecular simulation. In particular, modeling biological systems in
the context of multiscale simulations and exploring material properties are
driving a permanent development of new simulation methods and optimization
algorithms. In computational terms, those methods require parallelization
schemes that make a productive use of computational resources for each
simulation and from its genesis. Here, we introduce the heterogeneous domain
decomposition approach which is a combination of an heterogeneity sensitive
spatial domain decomposition with an \textit{a priori} rearrangement of
subdomain-walls. Within this approach, the theoretical modeling and
scaling-laws for the force computation time are proposed and studied as a
function of the number of particles and the spatial resolution ratio. We also
show the new approach capabilities, by comparing it to both static domain
decomposition algorithms and dynamic load balancing schemes. Specifically, two
representative molecular systems have been simulated and compared to the
heterogeneous domain decomposition proposed in this work. These two systems
comprise an adaptive resolution simulation of a biomolecule solvated in water
and a phase separated binary Lennard-Jones fluid.
