Abstract. An approach to dynamic parallelizing of coarse grained program where the parallelization sources are both dataflow analysis and the features pointed out in the program by annotating is proposed. Program annotating enables to hold two additional types of parallel computations which cannot be found out only from the analysis of dataflow dependences. Firstly, there are speculative computations based on anticipating alternative branches of the program's computational process. Secondly, there are pipeline computations that sometimes may be initialised for operators at the moment when their input data are not complete. Automated program analysis of this type of concurrence is either very hard or it generates a lot of surplus computation, thus absorbing the effect of program parallelization. The implementation of the system of dynamic program parallelization for clusters of PCs and results of some experiments performed on it are described.

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