The paper deals with the formation of system interfaces of a digital platform to manage the process of providing scientific services, including integration of scientific services to solve a complex research problem, for example, the multiscale modeling of the properties of new materials or conducting interdisciplinary research. Based on the functional structure of the integration of the scientific services of a digital platform (as applied to multiscale modeling) presented in this study, the requirements for the system interface are formulated, and the architecture of the system interface for the integration of scientific services of the digital platform is proposed. The proposed model of a system interface for informational interaction with the services and datasets of a digital platform in management processes for the provision of scientific services is based on modern solutions for managing a virtual infrastructure, based on container processing technologies and microservices, as well as means of orchestration and communication of containers (service mesh) and agile integration technologies. Taking into account the fact that the main function of the digital platform is to ensure the processes of preparation and conduct of research by formalizing the interaction scenarios of researchers, suppliers (sources) of the initial data, and consumers of the results, together with tools for supporting system interfaces to the catalogs of the digital platform, the project offers tools for organizing the interaction of services registered on the platform in order to ensure the execution of scientific research. Synchronization of the processes of providing services, ensuring the transfer of data between services, and obtaining the final result are also ensured through the implementation of control processes of the digital platform, which is based on the proposed system interface. The developed model of system interfaces is new in this work. The proposed interaction interface allows us to effectively consolidate high-performance computing resources and mathematical models based on digital platform technologies. This is especially important for organizing the solution of multiscale modeling problems as a kit of models, each of which operates on the same space-time scale.

The work presents the algorithms for managing and organization of scientific activity as services in hybrid computing environments of digital platforms. They expand the management algorithms for the deterministic research services of a digital platform. Their joint use allows, within the framework of a single information and computing space of a digital platform, to carry out a full cycle of management of scientific research processes, including cooperative research using digital economy tools, and to ensure the provision of scientific infrastructure resources to a wide range of consumers.

Fast Fourier transform is widely used to solve numerous scientific and engineering problems. In particular, this transform is behind the software dealing with speech and image recognition, signal analysis, modeling of properties of new materials and substances, etc. Newly emerging high-performance hybrid computing systems, as well as systems with alternative architectures, require research on discrete Fourier transform computation efficiency on these new platforms. The results of such research allow assessing the feasibility of certain solutions for building modern computing and data processing centers. This paper presents the results of such research covering modern hybrid computing systems based on the IBM POWER and Intel Xeon processors, as well as on NVIDIA Tesla co-processors. The analysis is carried out, and conclusions are presented on their performance when executing fast Fourier transforms. The impact of the existing architectural aspects of the hardware (CPU simultaneous multithreading mode, GPU data transfer bus, etc.) on the transform performance efficiency is assessed. The obtained results are used to provide recommendations on the optimal operation modes and settings of the considered mathematical libraries.

The article discusses methods of consolidating scientific services of a digital platform for integrating a set of scientific services for various fields of science for conducting interdisciplinary research. Solutions for creating consolidated services can be widely used for multilevel, multiscale modeling in the field of materials science, which provides complex modeling at several levels of the hierarchy. Currently, this problem is being solved by creating multicomponent hierarchical software systems on corporate computing systems. With the advent of high-performance cloud computing platforms, it will be possible to order services for solving particular modeling problems as a scientific service. In this case, the tasks of complex hierarchical modeling will be solved by a consolidated service—a service providing sequential-parallel execution of complex modeling components in the form of specialized scientific services. The description of the processes for the provision of scientific services is based on the research methodology and is a research plan (the work process mapping), which describes a set of operations related to time and includes a list of necessary resources for their implementation. In modern conditions of the development of a microservice approach to the creation of computing systems and the evolution of the Service Oriented Architecture and of the Enterprise Service Bus integration, special attention is paid to the problems of efficient integration of platform services. The paper proposes to supplement the existing description of a scientific service with the possibility of ordering a third-party service based on agile integration. This approach will allow at the present stage of development of service architectures to overcome the shortcomings of centralized systems such as Enterprise Service Bus and take advantage of the elasticity of cloud computing and a microservice approach to creating information and computing systems.

To solve the problems of materials science, including multiscale modeling for the synthesis of materials with specified properties, a modern digital platform for scientific research has been created at the FRC CSC RAS. The digital platform is a combination of a competence center, a high-performance computing complex and a set of scientific services that are provided to researchers in the form of traditional cloud services in software (SaaS), platform (PaaS) and infrastructure (IaaS) services, as well as using specific technologies for providing researchers scientific service as a service (RaaS, Research as a Service).Other examples of scientific fields for which scientific services are used in conjunction with high-performance computing services are: biomedical chemistry, crystallography, computational linguistics, artificial intelligence.The article describes the information and computing environment of the sharing research facilities Center for Collective Use “Informatics”, which forms the basis of the instrumental and technological infrastructure for prototyping, as well as the layout of the control system for deterministic scientific services of the digital platform.The article presents the results of experimental studies carried out in relation to algorithms for the transfer and intermediate storage of initial data, data exchange services when interacting with a platform user, cloud scientific high-performance computing services, algorithms for the interaction of data exchange adapters when ensuring interaction between the platform, which are relevant in solving problems of multiscale modeling for the synthesis of materials with desired properties.The results obtained allow us to evaluate the practical aspects of the functioning of a digital platform for scientific research, designed for the effective organization of scientific research and management of the scientific instrument base in the interests of a wide range of research teams and industrial consumers.

This article discusses a methodology for assessing the effectiveness of a high-performance research platform. The assessment is carried out for the example of the "Informatika" Center for Collective Use (CCU) established at the Federal Research Center of the Institute of Management of the Russian Academy of Sciences, for solving new materials synthesis problems. The main objective of the "Informatika" Center for Collective Use is to conduct research using the software and hardware of the data center of the FRC IU RAS, including for the benefit of third-party organizations and research teams. The general characteristics of the "Informatika" Center for Collective Use are presented, including the main characteristics of its scientific equipment, work organization and capabilities. The hybrid high-performance computing cluster of the FRC CSC RAS (HHPCC) is part of the data center of the FRC IU RAS and also part of the “Informatika” Center for Collective Use. HHPCC provides computing resources in the form of cloud services as software (SaaS) and platform (PaaS) services. With the aid of special technologies, scientific services are delivered to researchers in the form of subject-oriented applications. Based on the analysis of the structure and operation principles of the Informatika Center, key performance indicators of the Center have been developed taking into account its specific tasks in order to characterize its various activity aspects (development, activities and performance). CCU efficiency evaluation implies calculation, on the basis of the developed indicators, of overall (generalized) indicators that characterize the CCU operation efficiency in various areas. An integral indicator is also calculated showing the overall CCU efficiency. To develop the overall performance indicators and the integral performance indicator, it is suggested to use the methods of weighted average and analysis of hierarchies. The procedure of determining partial performance indicators has been considered. Specific features of the choice of CCU performance indicators for solving new materials synthesis problems have been identified that characterize computing complex capabilities in the creation of a virtualization environment (peak performance of a computing system, real performance of a computing system on specialized tests, equipment loading with applied tasks and program code efficiency).

The issues of offering services for providing resources of high-performance hybrid computer systems in applied and fundamental research within the framework of a unified digital platform are considered. Approaches for providing parallel execution of various tasks in a distributed computing cluster are proposed. The problems of organization of the computing process in the joint use of computing resources of a distributed hybrid cluster and organization of network interaction using software-defined networks are formulated.

Исследуются вопросы организации многопользовательской работы гибридных вычислительных систем. На примере кластера Центра коллективного пользования Центр данных ДВО РАН, построенного на архитектуре OpenPOWER, рассмотрены особенности функционирования систем подобного класса и предложены решения для организации их работы. С использованием механизма виртуальных узлов проведена адаптация системы диспетчеризации заданий PBS Professional, позволяющая организовать эффективное распределение аппаратных ресурсов кластера между пользовательскими задачами. Реализованное программное окружение кластера с системой комплексного планирования заданий рассчитано на работу с широким перечнем компьютерных приложений, включая программы, построенные с использованием различных технологий параллельного программирования. Для эффективного исполнения в данной среде решений на основе машинного обучения, глубокого обучения и искусственного интеллекта применены технологии виртуализации. С использованием возможностей среды контейнеризации Singularity сформирован специализированный стек программного обеспечения и реализован особый режим его работы в формате единой вычислительной цифровой платформы. Purpose. Improving the technology of machine learning, deep learning and artificial intelligence plays an important role in acquiring new knowledge, technological modernization and the digital economy development.An important factor of the development in these areas is the availability of an appropriate highperformance computing infrastructure capable of providing the processing of large amounts of data. The creation of coprocessorbased hybrid computing systems, as well as new parallel programming technologies and application development tools allows partial solving this problem. However, many issues of organizing the effective multiuser operation of this class of systems require a separate study. The current paper addresses research in this area. Methodology. Using the OpenPOWER architecturebased cluster in the Shared Services Center The Data Center of the Far Eastern Branch of the Russian Academy of Sciences, the features of the functioning of hybrid computing systems are considered and solutions are proposed for organizing their work in a multiuser mode. Based on the virtual nodes concept, an adaptation of the PBS Professional job scheduling system was carried out, which provides an efficient allocation of cluster hardware resources among user tasks. Application virtualization technology was used for effective execution of machine learning and deep learning problems. Findings. The implemented cluster software environment with the integrated task scheduling system is designed to work with a wide range of computer applications, including programs built using parallel programming technologies. The virtualization technologies were used in this environment for effective execution of the software, based on machine learning, deep learning and artificial intelligence. Having the capabilities of the container Singularity, a specialized software stack and its operation mode was implemented for execution machine learning, deep learning and artificial intelligence tasks on a unified computing digital platform. Originality. The features of hybrid computing platforms functioning are considered, and the approach for their effective multiuser work mode is proposed. An effective resource manage model is developed, based on the virtualization technology usage.

In article the basic features of the description of algorithms of telecommunication reports are considered, the concept of the hierarchical automatic device is defined and programming system Cell as tool means, first, for creation of the connected specification of the hierarchical automatic device on the basis of partially formalized descriptions of its parts, and, secondly, for synthesis of the executed code focused on consecutive performance of transitions of the hierarchical automatic device according to logic of execution of algorithm without use of methodology and technology of the organization of parallel calculations is offered