We consider the problem of efficiently coupling multiple data-parallel programs at runtime. We propose an approach that establishes a mapping between data structures in different data-parallel programs and implements a user specified consistency model. Mappings are established at runtime and new mappings between programs can be added and deleted while the programs are in execution. Mappings, or the identity of the processors involved, do not have to be known at compile-time or even link-time. Programs can be made to interact with different granularities of interaction without requiring any re-coding. A priori knowledge of data movement requirements allows for buffering of data and overlap of computations between coupled applications. Efficient data movement is achieved by pre-computing an optimized schedule. We describe our prototype implementation and evaluate its performance for a set of synthetic benchmarks that examine the variation of performance with coupling parameters. We demonstrate that the cost of the added flexibility gained by our coupling method is not prohibitive when compared with a monolithic code that does the same computation. (Also cross-referenced as UMIACS-TR-95-116)