  Quantum computing has gained considerable attention, especially after the
arrival of the Noisy Intermediate-Scale Quantum (NISQ) era. Quantum processors
and cloud services have been made world-wide increasingly available.
Unfortunately, programs on existing quantum processors are often executed in
series, and the workload could be heavy to the processor. Typically, one has to
wait for hours or even longer to obtain the result of a single quantum program
on public quantum cloud due to long queue time. In fact, as the scale grows,
the qubit utilization rate of the serial execution mode will further diminish,
causing the waste of quantum resources. In this paper, to our best knowledge
for the first time, the Quantum Program Scheduling Problem (QPSP) is formulated
and introduced to improve the utility efficiency of quantum resources.
Specifically, a quantum program scheduling method concerning the circuit width,
number of measurement shots, and submission time of quantum programs is
proposed to reduce the execution latency. We conduct extensive experiments on a
simulated Qiskit noise model, as well as on the Xiaohong (from QuantumCTek)
superconducting quantum processor. Numerical results show the effectiveness in
both QPU time and turnaround time.
