The use of modern multi-core and multi-processor computer systems for actual tasks is not effective enough, even taking into account the use of parallel programming technologies. The solution to the problem of efficient loading of computing resources can be the transition to computing models and architectures that are inherently parallel. One of such architectures is the Parallel Dataflow Computing System (PDCS) "Buran", which implements a dataflow computing model with a dynamically formed context. A feature of the dataflow computing model is the activation of computations by data readiness, which affects both the architecture of the computing system and the creation of programs for such systems. Differences between imperative and dataflow programming paradigms are also reflected in the route of creating a program, especially its parallel implementation. The route of creating a dataflow parallel program differs markedly from the traditional one. Already at the first stage, a parallel algorithm is created and implemented (including the algorithm for generating initial data). Next, this algorithm is debugged when it is executed on an emulator or model of the system with one computing core. After that, the selection and configuration of function of computation distribution is performed, the program is executed (without changing its code) on the emulator or model of the system with several computing cores, and, finally, the program is debugged in multi-core mode. These stages of the route differ from similar stages of the traditional route, both in form and in essence. Unlike traditional parallel, and even more so sequential programs, it can be said that a dataflow program in equal parts consists of a program code that implements a task, an algorithm for generating initial data, and a function of computation distribution. This thesis is demonstrated by the example of solving the problem of finding sum of array elements, where the difference between the implementations is in the algorithm for generating initial data, which radically affects the nature of the dataflow program passing. Careful attention to each of the parts of the dataflow program is the key to the correct and efficient solution of problems on the PDCS, which provides support to the programmer at the hardware level.