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Design productivity issues, including difficult hardware design and long compile times, are major barriers to the widespread adoption of FPGA-based accelerations in mainstream computing. Enabling virtualized execution of software and hardware tasks on FPGA platforms would make them more accessible to application developers accustomed to software API abstractions such as MPI and fast development cycles. In this work, we show that the MATIP platform provides a viable and efficient FPGA overlay architecture for the design of MPI parallel applications. We support this with a parallel model implementation of a feature extraction algorithm for tone language recognition, which is shown to be at least 7 times more efficient than a C++ MPI-2 RMA implementation of the same parallel model on a CPU and almost 3 times more efficient than a naive FPGA IP implementation.