An approach to dynamic parallelizing of coarse grained pro- gram 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 depen- dences. 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. Auto- mated 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.