UDC 004.415.538 Research of Acceleration Calculations in Solving Scientific Problems on the Heterogeneous Cluster HybriLIT E. I. Alexandrov∗, D. V. Belyakov∗, M. A. Matveyev∗, D. V. Podgainy∗, O. I. Streltsova∗, Sh. <...> G. Torosyan∗, E. V. Zemlyanaya∗, P. V. Zrelov∗†, M. I. Zuev∗ ∗ Laboratory of Information Technologies Joint Institute for Nuclear Research 6, Joliot-Curie str., Dubna, Moscow region, Russia, 141980 † Plekhanov Russian University of Economics 36, Stremyanny per., Moscow, Russia, 117997 The paper presents some test results of the heterogeneous computing cluster HybriLIT put into operation at the Laboratory information technologies of the Joint Institute for Nuclear Research. <...> The structure of the cluster includes computational nodes with NVIDIA graphical accelerators and Intel Xeon Phi coprocessors. <...> The necessity of integration of such a computational platform in the JINR Multifunctional Information and Computing Complex is determined by a global tendency to use hybrid computing architectures for carrying out massive-parallel computations in applied scientific problems solution. <...> Test of the cluster aimed at: first of all, test of the efficiency of hardware and software settings that include operational system, resource manager, file system, compilers, and, secondly, test of the efficiency of using different architectures for the solution of particular applied problems in order to provide user guides on specialized libraries. <...> For realization of the cluster test, an approach that includes test computations by means of standard program packages such as Linpack and program complexes established in LIT has been developed. <...> The presented results show that the use of hybrid computing architectures allow accelerate the solution of applied scientific problems, and heterogeneous computing cluster HybriLIT is an effective means of accomplishing this aim. <...> Key words and phrases: high performance platform, Linpack benchmarks, technology of parallel programming, heterogeneous computing. 1. <...> Introduction include different types of computation accelerators are becoming widespread in scientific and applied scientific researches. <...> This is clear from the list of TOP500 supercomputer sites [1]; according to the 45th edition of the TOP500, 35% of all platforms performance is provided by coprocessors of various architectures; and half of them – by NVIDIA graphical processors [2]. <...> Following this tendency, the producers of applied software are adjusting the developed <...>