Many parallel applications involve different independent tasks with their own data. Using the MPMD model, programmers can have a modular view and simplified structure of the parallel programs. Although MPI supports both SPMD and MPMD models for programming, MPI libraries do not provide an efficient way for task communication for the MPMD model. We have developed a programming environment, called ClusterGOP, for building and developing parallel applications. Based on the graph-oriented programming (GOP) model, ClusterGOP provides higher-level abstractions for message-passing parallel programming with the support of software tools for developing and running parallel applications. In this paper, we describe how ClusterGOP supports programming of MPMD parallel applications on top of MPI. We discuss the issues of implementing the MPMD model in ClusterGOP using MPI and evaluate the performance by using example applications.