Quantum cloud computing is a promising paradigm for efficiently provisioning quantum resources (i.e., qubits) to users. In quantum cloud computing, quantum cloud providers provision quantum resources in reservation and on-demand plans for users. Literally, the cost of quantum resources in the reservation plan is expected to be cheaper than the cost of quantum resources in the on-demand plan. However, quantum resources in the reservation plan have to be reserved in advance without information about the requirement of quantum circuits beforehand, and consequently, the resources are insufficient, i.e., under-reservation. Hence, quantum resources in the on-demand plan can be used to compensate for the unsatisfied quantum resources required. To end this, we propose a quantum resource allocation for the quantum cloud computing system in which quantum resources and the minimum waiting time of quantum circuits are jointly optimized. Particularly, the objective is to minimize the total costs of quantum circuits under uncertainties regarding qubit requirement and minimum waiting time of quantum circuits. In experiments, practical circuits of quantum Fourier transform are applied to evaluate the proposed qubit resource allocation. The results illustrate that the proposed qubit resource allocation can achieve the optimal total costs.
翻译:量子云计算是高效率地向用户提供量子资源(即qubits)的一个有希望的模式。在量子云计算中,量子云提供商在用户保留和需求计划中提供量子资源。从字面上看,保留计划中量子资源的成本预计将比点机计划中量子资源的成本更低。然而,保留计划中量子资源必须预先保留,而没有预先提供关于量子电路要求的信息,因此,资源不足,即保存不足。因此,点子云计划的数量资源可用于补偿未满足的量子资源。为此,我们提议为量子云计算系统分配量子资源,在量子资源和量子电路最低等待时间方面共同优化。特别是,目标是在量子电路要求不确定和最小等待时间不确定的情况下,最大限度地减少量子电路的总成本。在试验中,应用量子四变换的实用电路来评估拟议的量平位资源分配总额。结果表明,拟议的量云计算资源配置能够达到最佳的成本。