CONVERGENCE OF QUANTUM COMPUTING, HIGH-PERFORMANCE COMPUTING (HPC), AND AI: ARCHITECTURAL CHALLENGES AND DEVELOPMENT PROSPECTS OF HYBRID SYSTEMS (2025-2030)
M.A. KARAS, А.В. Забродин
The current stage in the development of computing systems is characterized by a transition to heterogeneous architectures that integrate multiple computational paradigms. The aim of this study is to analyze the current state and key directions of convergence among high-performance computing (HPC), artificial intelligence (AI), and quantum technologies. The paper presents an analytical review of the integration processes of HPC, AI, and quantum technologies as an emerging direction in the development of heterogeneous computing systems. The transition in 2024-2026from isolated NISQ experiments to the engineering integration of quantum processing units (QPU) into existing HPC infrastructures is analyzed. The bidirectional interaction between AI and quantum computing is examined, including the use of neural network methods for qubit calibration and quantum error correction decoding, as well as the potential of quantum machine learning for high-dimensional data processing. It is shown that supercomputing centers serve as a natural platform for deploying hybrid CPU+GPU+QPU architectures, while the development of a unified software stack and the transformation of competency requirements are essential conditions for the practical implementation of such convergence. The results obtained can be used in the design of hybrid computing systems, as well as in the development of research and educational programs in the fields of quantum and high-performance computing.
Informatization and communication•Jan 1, 2026•0 citations