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Real-space mesh approach is really efficient in terms of performance. {\sc Octopus} has shown a high performance in current architectures \cite{Alberdi_2014}, not only because of the mesh-partitioning but also because of other kind of parallelizations. One of those natural way of parallelization is the state parallelization. Indeed, every state (or wavefunction) of the system is represented over a discrete mesh, being each state independent of the others.  In general, besides the general mesh, another one is used for the Poisson solver. This latter one has to be necessarily parallelepiped and it will be denoted as \emph{cube}. Involved number of MPI processes in the general mesh and in the \emph{cube} mesh  might be different, so a mapping between both is computed and saved. This map enables the possibility for a rapid transfer between both representation.