1. A computer-implemented method of identifying and extracting mutually independent computations in a dataflow program for exploiting massive parallelism, the method comprising: receiving a dataflow program having a number of actors and a multiplicity of connections connecting the actors, the dataflow program providing: specified consumption rates on the multiplicity of connections; specified production rates on the multiplicity of connections; a specified number of initial samples on at least a part of the multiplicity of connections, the initial samples providing input for a first set of actors; generating, from the specified consumption rates, the specified production rates, and the specified number of initial samples, at least one model of a precedence graph for the dataflow program, the model: representing dependence constraints between distinct firings of the number of actors; having a number of vertices, having associated therewith an actor-index pair; having edges representing precedent constraints; for the at least one model: determining a feedback distance between multiple firings of a same actor in the model; determining sets of parallel regions for at least a part of the vertices of the model, such that each set of parallel regions comprises a given number of actor firings of a same actor, the given number being dependent on the determined feedback distance; composing mutually independent component regions, each component region comprising at least a part of one or more sets of parallel regions; composing one or more composite regions so as to satisfy a predetermined criteria; the one or more composite regions comprising at least one of: one or more component regions; and one or more sets of parallel regions; extracting composite regions from the model.