IEEE Internet Computing · 2021 · 74 citations · 6 references
ComputingCloud ComputingComputer ScienceCloud ArchitectureCloud InfrastructureQuantum ComputingQuantum AlgorithmsQuantum ComputationPay-per-use ModelsQuantum Computing ArchitectureQuantum Programming AbstractionsRun-time Adaptation
Quantum computers are increasingly offered as cloud services, and as quantum software grows more complex, new engineering methods and abstractions are required to adapt service‑oriented practices to quantum hardware limitations. The article proposes the Quantum API Gateway, an adaptation of the API Gateway pattern tailored to quantum services that cannot be deployed as traditional services. The gateway selects the optimal quantum computer at runtime to execute a given quantum service. A proof‑of‑concept implementation of the gateway was demonstrated on Amazon Braket.
As quantum computers mature, the complexity of quantum software increases. As we move from the initial standalone quantum algorithms toward complex solutions combining quantum algorithms with traditional software, new software engineering methods and abstractions are needed. Nowadays, quantum computers are usually offered in the cloud, under a pay-per-use model, leading to the adoption of the service-oriented good practices that dominate the cloud today. However, specific adaptations are needed to reap the benefits of service-oriented computing while dealing with quantum hardware limitations. In this article, we propose the Quantum API Gateway—an adaptation of the API Gateway pattern that takes into account the fact that quantum services cannot be deployed as traditional services. Instead, the Quantum API Gateway recommends the best quantum computer to run a specific quantum service at run time. As proof of concept, we provide an implementation of the Quantum API Gateway for the Amazon Braket platform.
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Quantum Software Engineering: Landscapes and Horizons
Jianjun Zhao · arXiv (Cornell University) · 2020 · 118 citations · Full text
Mario Piattini, Guido Peterssen, Ricardo Pérez‐Castillo · ACM SIGSOFT Software Engineering Notes · 2020 · 105 citations · Full text