Increasing the performance of the software framework for implementing the algorithms of the group method of data handling

In previous works the author has proposed a universal software framework that allows implementing the known algorithms of group method of data handling, model bases, training methods and model selection criteria. This paper introduces the solution of a topical problem of increasing the performance of the framework. Based on the review of existing computing architectures for parallel data processing and software systems for inductive modeling supporting parallel computations the author has worked out the requirements for the subsystems of parallel computing and memory management of the software framework. Using the methodology of object-oriented analysis and design the author developed the object-oriented structure of these subsystems and introduced the specifics of their operation on each of the mentioned computing architectures. The performance of the parallel implementation of the combinatorial group method of data handling algorithm on basis of the software framework was evaluated experimentally for multi-core processors.