Creating Hybrid Computing Architectures for Data Centers
Nataliya Grigorievna Kuftinova, Andrey Vladimirovich Ostroukh, C. B. Pronin, Aleksandr A. Podberezkin · 2025
This is article examines the issue of new conceptual architectures of ultrafast hybrid computing devices based on digital technologies, where the size of an elementary computing device approaches the size of a molecule or even an atom. At this level, the laws of classical physics stop working and quantum laws begin to operate, which for many important dynamic problems have yet to be described theoretically. For such practically significant examples of the use of quantum computers as the training of language models, as well as the analysis of the effectiveness of model training on specified chips and with specified train characteristics (model depth, dataset size, etc.), a new concept for the use of hybrid computing platforms in data centers has emerged. Hybrid computing platforms for data centers represent the integration of various computing resources, including on-premises servers, cloud solutions and virtualized environments. These platforms allow organizations to optimize their computing power, providing flexibility, scalability and costeffectiveness. With the increase in data volumes and the need for cloud services, there is an increase in the creation of data centers. The edge-computing extension, which supports real-time processing at data collection points, matches the potential of quantum computing for revolutionary tasks such as optimization and decision-making. As peripheral systems evolve, the integration of algorithms with quantum technologies can expand their capabilities. This raises pitfalls in evaluating processor performance in hybrid computers, which can vary depending on many factors, including the processor architecture, the types of cores used (for example, high-performance and energy-efficient), as well as the nature of the tasks performed. In this study, a mathematical model of the presented systems is proposed as a combination of combining various concepts that will help to understand and evaluate the performance of hybrid computing, allowing you to optimize the use of resources and improve overall efficiency. Today, there is a growing dependence on hybrid models - mixing local, cloud and peripheral systems, which further emphasizes the need for an infrastructure that accommodates both classical and quantum resources. Quantum computing is increasingly seen as an important part of these hybrid architectures, preparing organizations to meet the new challenges of the advanced computing landscape.