The article discusses the application of MPI technology when performing calculations on a hybrid high-performance computing cluster using virtualization on a container base. The features of the ...application of interprocess interaction in a virtualization environment associated with the construction of a single space of containers interacting over a high-performance computing network interconnect are considered. Approaches and algorithms for deploying and executing parallel processes in a computer cluster are proposed. The issue of the functioning of computing process control systems in the provision of PaaS services using virtualization technologies is considered.
In this paper, we consider the problem of solving scientific problems in the field of materials science in the environment of high-performance computing systems. Mathematical modeling methods ...implemented by specialized modeling systems is used to solve a certain kind of problems in materials science. The modeling systems show the greatest efficiency when deployed in hybrid high-performance computing systems (HHPC) that allow solving problems in a reasonable time period with sufficient accuracy. However, there are a number of restrictions that affect the work of research teams with modeling systems in the HHPC computing environment: the need to access graphics accelerators at the stage of developing and debugging algorithms in the modeling system, the need to use several modeling systems in order to obtain the optimal solution, and the need to dynamically change the settings of modeling systems for solving problems. The solution to the problem of these restrictions is assigned to the individual modeling environment operating in the HHPC computing environment. The best solution for creating an individual modeling environment is virtual containerization technology. We propose an algorithm for the formation of an individual modeling environment in a hybrid high-performance computing complex based on the Docker virtual containerization system. An individual simulation environment is created by installing the required software in the base container, setting environment variables, and installing custom software and licenses. A feature of the algorithm is the ability to form a library image from a base container with a customized individual modeling environment. The direction for further research work is indicated in the conclusion. The algorithm presented here is independent of the implementation of the problems’ control system and may be used for any high-performance computing system.
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