A Case for Multi-Programming Quantum Computers

Existing and near-term quantum computers face significant reliability challenges because of high error rates caused by noise. Such machines are operated in the Noisy Intermediate Scale Quantum (NISQ) model of computing. As NISQ machines exhibit high error-rates, only programs that require a few qubits can be executed reliably. Therefore, NISQ machines tend to underutilize its resources. In this paper, we propose to improve the throughput and utilization of NISQ machines by using multi-programming and enabling the NISQ machine to concurrently execute multiple workloads. Multi-programming a NISQ machine is non-trivial. This is because, a multi-programmed NISQ machine can have an adverse impact on the reliability of the individual workloads. To enable multi-programming in a robust manner, we propose three solutions. First, we develop methods to partition the qubits into multiple reliable regions using error information from machine calibration so that each program can have a fair allocation of reliable qubits. Second, we observe that when two programs are of unequal lengths, measurement operations can impact the reliability of the co-running program. To reduce this interference, we propose a Delayed Instruction Scheduling (DIS) policy that delays the start of the shorter program so that all the measurement operations can be performed at the end. Third, we develop an Adaptive Multi-Programming (AMP) design that monitors the reliability at runtime and reverts to single program mode if the reliability impact of multi-programming is greater than a predefined threshold. Our evaluations with IBM-Q16 show that our proposals can improve resource utilization and throughput by up to 2x, while limiting the impact on reliability.

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