Problems of high-performance processing of mass cluster data are considered. Estimates of execution times of parallel data processing programs and a heuristic algorithm of optimization of cluster architectures for such problems are proposed.

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Parallel algorithms and programs for solving so-called problems of transcomputational complexity are addressed. Quality requirements to both IT program component and development tools for parallel MPI-programs are formulated. An intelligent IT for research automation and solution of scientific and engineering problems is proposed and used to formulate principles of creating Inparcom knowledge-based computers.Keywords: cluster complex, scheme of parallel computations, mathematical model of a problem, host processor, operating environment.