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The emergence of grid and a new class of data-driven applications is making a new form of parallelism desirable, which we refer to as coarse-grained pipelined parallelism. This paper reports on a compilation system developed to exploit this form of parallelism. We use a dialect of Java that exposes both pipelined and data parallelism to the compiler. Our compiler is responsible for selecting a set of candidate filter boundaries, determining the volume of communication required if a particular boundary is chosen, performing the decomposition, and generating code. We have developed a one-pass algorithm for determining the required communication between consecutive filters. We have developed a cost model for estimating the execution time for a given decomposition, and a dynamic programming algorithm for performing the decomposition. Detailed evaluation of our current compiler using four data-driven applications demonstrate the feasibility of our approach.