This white paper presents an overview of the current state of the art in high-performance computing (HPC) and its convergence with cloud technologies, with a strategic focus on innovation management and exploitation. It outlines recent advances in cloud-based HPC services, hybrid architectures, and federated systems that integrate edge, cloud, and HPC resources. Emerging paradigms such as federated learning, AIdriven optimization, and sustainable computing are analyzed for their transformative potential. Special emphasis is placed on the NOUS project, which exemplifies a holistic approach to federated HPC-cloud services, combining technical innovation with robust exploitation strategies. NOUS goes one step beyond and explores the integration of quantum computing in handling data existing in the cloud. As of late 2025, the synergy between Cloud Computing and Quantum Computing (QC) has matured into a functional "Quantum-as-a-Service" (QaaS) model. While physical quantum hardware remains too fragile for on-premise deployment, cloud providers have democratized access to the "Quantum Stack." This report highlights this progress, the issues and real future applications. NOUS addresses European priorities for digital sovereignty and data interoperability, supporting scalable, privacy-preserving, and AI-enabled HPC workflows. The paper concludes with a roadmap that positions NOUS as a reference architecture and innovation catalyst for Europe's distributed computing ecosystem.
This white paper presents an overview of the current state of the art in high-performance computing (HPC) and its convergence with cloud technologies, with a strategic focus on innovation management and exploitation. It outlines recent advances in cloud-based HPC services, hybrid architectures, and federated systems that integrate edge, cloud, and HPC resources. Emerging paradigms such as federated learning, AIdriven optimization, and sustainable computing are analyzed for their transformative potential. Special emphasis is placed on the NOUS project, which exemplifies a holistic approach to federated HPC-cloud services, combining technical innovation with robust exploitation strategies. NOUS goes one step beyond and explores the integration of quantum computing in handling data existing in the cloud. As of late 2025, the synergy between Cloud Computing and Quantum Computing (QC) has matured into a functional "Quantum-as-a-Service" (QaaS) model. While physical quantum hardware remains too fragile for on-premise deployment, cloud providers have democratized access to the "Quantum Stack." This report highlights this progress, the issues and real future applications. NOUS addresses European priorities for digital sovereignty and data interoperability, supporting scalable, privacy-preserving, and AI-enabled HPC workflows. The paper concludes with a roadmap that positions NOUS as a reference architecture and innovation catalyst for Europe's distributed computing ecosystem.
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously intractable problems. This manuscript provides a comprehensive overview of the current state of HPC-QC interfacing, detailing architectural methodologies, software stack developments, middleware functionalities, and hardware integration strategies. It critically assesses existing hardware-level integration models, ranging from standalone and loosely-coupled architectures to tightly-integrated and on-node systems. The software ecosystem is analyzed, highlighting prominent frameworks such as Qiskit, PennyLane, CUDA-Q, and middleware solutions like Pilot-Quantum, essential for seamless hybrid computing environments. Furthermore, the manuscript discusses practical applications in optimization, machine learning, and many-body dynamics, where hybrid HPC-QC systems can offer substantial advantages. It also describes existing challenges, including hardware limitations (coherence, scalability, connectivity), software maturity, communication overhead, resource management complexities, and cost factors. Finally, future directions towards tighter hardware and software integration are discussed, emphasizing ongoing research developments and emerging trends that promise to expand the capabilities and accessibility of hybrid HPC-QC systems.
Abstract: This article presents a comprehensive review of the integration of quantum computing with High-Performance Computing (HPC), examining current trends, challenges, and future directions. We explore the fundamental principles of quantum computing and their relevance to HPC, followed by an analysis of state-of-the-art quantum algorithms and hybrid quantum-classical systems. The article addresses key technical challenges in hardware and software integration, as well as scalability and stability issues in quantum-enhanced HPC systems. Through a series of case studies, we demonstrate the practical applications and potential impact of quantum-HPC integration across various industries, including finance, drug discovery, and logistics. Our findings highlight the transformative potential of quantum computing in HPC, suggesting unprecedented improvements in computational speed and efficiency. The article concludes with an overview of emerging quantum technologies and identifies promising research opportunities, emphasizing the importance of collaboration between academia and industry. This work serves as a valuable resource for researchers, engineers, and industry professionals seeking to understand and leverage the synergy between quantum computing and HPC, paving the way for future innovations in computational capabilities
The rapid advancement of quantum computing technology presents an opportunity to revolutionize cloud computing platforms, enabling the execution of complex workloads that are beyond the reach of classical systems. This paper explores the potential of quantum-enhanced cloud platforms, focusing on bridging classical and quantum computing to support future workloads. We examine the integration of quantum processors with classical cloud infrastructure, highlighting the challenges and benefits of hybrid architectures that combine the strengths of both paradigms. Key topics include quantum resource management, quantum programming models, and the development of algorithms that leverage quantum speedup for optimization, machine learning, and data analysis. Additionally, we address the scalability, security, and interoperability concerns that must be overcome for effective deployment in real-world cloud environments. By offering insights into the convergence of classical and quantum computing, this paper provides a roadmap for the evolution of cloud platforms capable of supporting next-generation applications and workloads.
Quantum computing has emerged as a transformative technology capable of solving complex computational problems beyond the capabilities of classical systems. However, severe hardware limitations, qubit decoherence, and high implementation costs prevent it from replacing classical cloud infrastructure. Instead, cloud and quantum computing are evolving as complementary technologies. Through Quantum-as-a-Service (QaaS) and hybrid cloud–quantum architectures, cloud platforms provide scalable infrastructure, data management, and resource orchestration, while quantum processors accelerate specialized computational tasks. This review systematically examines the relationship between cloud computing and quantum computing by analyzing their technical differences, capabilities, application areas, current challenges, limitations, and future research directions. The findings indicate that cloud computing will continue to serve as the backbone of modern digital infrastructure, while quantum computing will enhance its capabilities for solving complex computational problems. Together, these technologies are expected to drive the next generation of intelligent, scalable, and high-performance computing systems. Keywords: cloud computing; quantum computing; Quantum as a Service (QaaS); Hybrid Cloud–Quantum Architecture; Post-Quantum Security; QMLOps
Abstract: This article explores the convergence of quantum computing and cloud technologies, representing a pivotal advancement in computational power with far-reaching implications across various industries and scientific domains. It examines the current state of quantum computing, elucidating its fundamental principles and recent hardware advancements, while comparing its capabilities to classical computing systems. The integration of quantum computing with cloud platforms is analyzed, highlighting the emergence of cloud-based quantum services and their advantages in democratizing access to this cutting-edge technology. The article delves into potential applications of quantum cloud computing, including cryptography, material science, artificial intelligence, and financial modeling, showcasing its transformative potential. Critical challenges facing quantum cloud computing are addressed, such as error correction, scalability issues, and the development of quantumsafe encryption methods. Looking ahead, the article discusses prospects and research directions, including anticipated breakthroughs in quantum hardware, emerging quantum cloud architectures, and the potential impact on various industries. By synthesizing current research and industry developments, this comprehensive overview provides insights into the revolutionary potential of quantum cloud computing and its role in shaping the future of computational capabilities.
The growing integration of cloud computing and artificial intelligence (AI) has remarkably transformed modern computing, enabling organizations and researchers to process vast amounts of data and solve increasing complex problems. However, as data volumes and computational requirements continue to grow, traditional computing systems are increasingly challenged in meeting these demands. In this context, quantum computing has evolved as a revolutionary technology with the potential to perform certain computations far more efficiently than classical computers. When integrated with cloud platforms, quantum computing becomes accessible to a broader community through remote, on-demand services, giving rise to the concept of Quantum Cloud Computing. At the same time, Quantum Machine Learning (QML) is opening new possibilities by combining the power of quantum computing with advanced machine learning techniques. Together, these technologies are shaping a new paradigm known as Quantum Cloud Intelligence, where cloud infrastructure, quantum resources, and AI work in synergy to enhance computational capabilities and support intelligent decision-making. This chapter examines the foundations and evolution of Quantum Cloud Intelligence, highlighting its key technologies, architectures, and emerging applications. It explores how quantum-enabled cloud platforms can contribute to fields such as healthcare, finance, cybersecurity, scientific research, smart cities, and industrial automation. The chapter also discusses the opportunities offered by quantum-enhanced analytics, optimization, and predictive modelling, while addressing important challenges related to scalability, security, privacy, hardware constraints, and skill development. Looking ahead, the chapter considers future trends including hybrid quantum-classical systems, Quantum Computing as a Service (QCaaS), and the development of scalable quantum AI ecosystems. It argues that the integration of quantum computing, cloud technologies, and AI has the potential to redefine the future of intelligent computing and drive innovation across multiple disciplines. As these technologies continue to mature, Quantum Cloud Intelligence is expected to play a pivotal role in addressing complex global challenges and shaping the next generation of digital transformation.