  The amount of available data about complex systems is increasing every year,
measurements of larger and larger systems are collected and recorded. A natural
representation of such data is given by networks, whose size is following the
size of the original system. The current trend of multiple cores in computing
infrastructures call for a parallel reimplementation of earlier methods. Here
we present the grid version of CFinder, which can locate overlapping
communities in directed, weighted or undirected networks based on the clique
percolation method (CPM). We show that the computation of the communities can
be distributed among several CPU-s or computers. Although switching to the
parallel version not necessarily leads to gain in computing time, it definitely
makes the community structure of extremely large networks accessible.
