Abstract—Hierarchical dependencies are presented as an extension to data flow programming that allows parallel programs dynamically scale on a heterogeneous environment. The concept can help Grid parallel programs to cope with changes in processors, or Cloud and multi-core frameworks to manage energy use. A data stream with dependencies can be split, which in turn allows for a greater use of processors. The concept shows a 6 % overhead when running with split dependencies on shared memory. The overhead on a cluster environment is masked by the network delay. Hierarchical dependencies show a 18.23% increase in non-functional code when the feature was added to a 5-point stencil implementation. Index Terms—Skeletons, patterns, grid, cloud, multi-core. I.