In spite of the high parallelism exhibited by cellular automata architectures, most implementations are usually run in software. For increasing execution parallelism, hardware implementations on FPGAs have been proposed, under the cost of being un-flexible, and inefficient in terms of resource utilization. In this paper we present a platform for evolving CA by exploiting the partial re-configurability of current commercial FPGAs. Our implementation includes an on-chip soft-processor that generates a partial bitstream, reconfigures the FPGA, and computes the fitness. After finding a good individual, the evolved CA can be used as a peripheral for performing useful computation. As case study we present CA co-evolution for a random number generator and for the firefly synchronization problem.