With the deeply studied of quantum computing by research fellows, the computational complexity and time complexity of quantum algorithms gradually increase. The quantum computing simulator provides an effective platform for the development and verification of quantum algorithms. However, the running time and memory overhead during calculation will increase exponentially with the number of qubits. Therefore, the difficulty of high-speed quantum computing on classical computers will gradually increase. At present, a single node has been unable to meet the resource requirements of the algorithm in the quantum computing process, and it is necessary to expand the memory resources in the multi-node computing cluster. Message passing interface has high performance inter-process communication capabilities, which can balance the data transmission between different hosts. Quantum computing tasks can be distributed on several servers to work together to solve the same problem. Therefore, this paper designs an advanced scheme of deploying quantum computing programs on cloud computing platform to support message exchanging between servers using message passing interface to accelerate quantum computing.
With the deeply studied of quantum computing by research fellows, the computational complexity and time complexity of quantum algorithms gradually increase. The quantum computing simulator provides an effective platform for the development and verification of quantum algorithms. However, the running time and memory overhead during calculation will increase exponentially with the number of qubits. Therefore, the difficulty of high-speed quantum computing on classical computers will gradually increase. At present, a single node has been unable to meet the resource requirements of the algorithm in the quantum computing process, and it is necessary to expand the memory resources in the multi-node computing cluster. Message passing interface has high performance inter-process communication capabilities, which can balance the data transmission between different hosts. Quantum computing tasks can be distributed on several servers to work together to solve the same problem. Therefore, this paper designs an advanced scheme of deploying quantum computing programs on cloud computing platform to support message exchanging between servers using message passing interface to accelerate quantum computing.
Quantum computing has been an attractive method adapted for increasing the computational speed and it is governed by the laws of quantum mechanics. Quantum computers are not limited to two states as compared with classical systems, but they encode information as quantum bits or qubits. A qubit represents atoms, ions, photons or electrons and their respective control devices that are working together to act as computer memory and processors. The power of quantum computing lies in its multi-state representation which makes it million times more powerful than classical computer systems. Quantum computers also use another aspect of quantum mechanics known as entanglement, which is a property where multiple objects existing in the states that can be linked together. There exists a standard/specification of message passing library, known as message passing interface (MPI) that can be used for achieving high-performance computing. The goal of MPI is to provide a standardized framework for writing message-passing programs which can be used for programming systems that require distributed processing. The superposition principle used by the quantum algorithm can be simulated in the MPI environment with a cluster of computers or multi-CPU systems. This paper focuses on exposing the strength of quantum algorithm in high performance computing by using MPI, and also on comparing the sequential and parallel execution of programs on the basis of execution time and CPU utilization.
The objective of this research is to explore the integration of quantum computing with multi-cloud architectures, aiming to enhance computational efficiency and security in advanced cloud environments. The study seeks to identify the potential benefits and challenges of incorporating quantum computing capabilities within a multi-cloud framework and to evaluate the impact on performance and security metrics. The research employs a hybrid methodological approach, combining both theoretical analysis and practical implementation. Initially, a detailed literature review is conducted to understand the current state of quantum computing and multi-cloud architectures. This is followed by the design and development of an integration framework that leverages quantum computing technologies in a multi-cloud environment. Key steps include developing a multi-cloud architecture that integrates quantum computing resources alongside classical computing resources, deploying quantum algorithms and protocols within the multi-cloud setup, implementing advanced security measures to protect data and computational processes, using a set of predefined metrics to evaluate computational efficiency and security, and employing statistical tools and techniques to analyze the collected data and draw meaningful insights. The integration of quantum computing with multi-cloud architectures resulted in significant improvements in computational efficiency, particularly in tasks that are traditionally resource-intensive. Key findings include enhanced computational speed, where quantum algorithms demonstrated superior performance in solving complex problems compared to classical algorithms, optimized resource utilization through dynamic allocation of quantum and classical resources leading to cost efficiency, improved security with quantum-enhanced protocols providing robust protection against cyber threats, and high scalability of the integrated architecture to accommodate increasing computational demands without compromising performance. The research concludes that integrating quantum computing with multi-cloud architectures offers substantial benefits in terms of computational efficiency and security. The findings indicate that such integration can revolutionize cloud computing, providing a powerful platform for handling complex computations and enhancing data security. However, the study also highlights several challenges, including the need for specialized hardware, the complexity of integration, and the necessity for ongoing research to fully harness the potential of quantum computing in cloud environments. Future research should focus on addressing these challenges and exploring further applications of quantum computing in various cloud-based scenarios.
Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resource requirements of quantum algorithms in a distributed setting, where multiple quantum processors are interconnected by a coherent network. We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms. In turn, these implementations can be used for testing, debugging, and resource estimation. In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ. The model is inspired by the classical LogP model, making it useful to inform algorithmic decisions when programming distributed quantum computers. Specifically, we consider several optimizations of two quantum algorithms for problems in physics and chemistry, and we detail their effects on performance in the SENDQ model.
The growing demand of better functionality in the distributed computing systems has discovered the limitations of the conventional cloud systems in operating under the complicated model, particularly with the computation, security risk, and processing time in a low latency. Even though the distributed systems can work with a much larger number of clients, as they have more computing power, in practice they are limited by the speed of traditional processors and classical encryption model protection. The provided paper describes a quantum-enabled model of cloud computing to facilitate the deployment of quantum processors within the framework of the infrastructure of distributed systems and also facilitates hybrid classical-quantum computing on the bundled runtime level. The proposed model employs quantum algorithms to optimize the optimization and speed up the performances of solving problems, improve security by using quantum-proven cryptographic, and distribute resources to the distributed nodes in the cloud computing system in an intelligent manner. Computational structure implies that it has a layered architecture that comprises of quantum processing units, cloud-level software coordination, and quantum communication protocols. Qiskit and cloud-native applications are used to test the model by simulation. Results indicate that the run time on complex optimization problems may be reduced by a maximum of 45 per cent, and the ability to provide more data security against quantum threat. Results provide a clue on the possible transformation quantum can impose on the next generation cloud-based distributed systems and transform continuous work and research to enable sustainable, secure and efficient infrastructures to maximize future computing.
Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelity for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected is highly demanding. To realize the inter-node communication of quantum information, the software interface, Quantum Message Passing Interface (QMPI), leveraging the framework built for classical MPI but taking advantage of quantum teleportation to communicate between different quantum nodes was proposed. In this work, we developed a QMPI implementation with a variety of point-to-point and collective operations in Qiskit and characterize its performance by demonstrating the reference implementations on a few benchmark quantum applications. Moreover, we developed a new approach for optimizing collective communications for the distributed quantum programs with multi-controlled Toffoli gates. This approach outperforms current state-of-the-art in terms of fidelity and the number of remote EPR pairs in both simulations and experiments over IBM’s quantum platforms.
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