A large class of problems in the current era of quantum devices involve interfacing between the quantum and classical system. These include calibration procedures, characterization routines, and variational algorithms. The control in these routines iteratively switches between the classical and the quantum computer. This results in the repeated compilation of the program that runs on the quantum system, scaling directly with the number of circuits and iterations. The repeated compilation results in a significant overhead throughout the routine. In practice, the total runtime of the program (classical compilation plus quantum execution) has an additional cost proportional to the circuit count. At practical scales, this can dominate the round-trip CPU-QPU time, between 5% and 80%, depending on the proportion of quantum execution time. To avoid repeated device-level compilation, we identify that machine code can be parametrized corresponding to pulse/gate parameters which can be dynamically adjusted during execution. Therefore, we develop a device-level partial-compilation (DLPC) technique that reduces compilation overhead to nearly constant, by using cheap remote procedure calls (RPC) from the QPU control software to the CPU. We then demonstrate the performance speedup of this on optimal pulse calibration, system characterization using randomized benchmarking (RB), and variational algorithms. We execute this modified pipeline on real trapped-ion quantum computers and observe significant reductions in compilation time, as much as 2.7x speedup for small-scale VQE problems.

翻译：在当前量子设备时代，大量问题涉及量子系统与经典系统之间的交互。这些包括校准流程、表征例程和变分算法。这些例程中的控制会在经典计算机和量子计算机之间迭代切换，导致运行在量子系统上的程序被重复编译，其开销直接随电路数量和迭代次数增加。重复编译在整个例程中产生显著开销。实践中，程序总运行时间（经典编译加量子执行）的额外成本与电路数量成正比。在实际规模下，这可能会占据CPU-QPU往返时间的5%至80%，具体取决于量子执行时间的占比。为避免重复的设备级编译，我们发现机器代码可对应于可在执行期间动态调整的脉冲/门参数进行参数化。因此，我们提出一种设备级部分编译（DLPC）技术，通过从QPU控制软件到CPU使用廉价远程过程调用（RPC），将编译开销降低至接近恒定。随后，我们在最优脉冲校准、使用随机基准测试（RB）的系统表征以及变分算法上展示了该技术的性能加速。我们在真实离子阱量子计算机上执行了这一修改后的流水线，观察到编译时间显著减少，对于小规模VQE问题，加速比高达2.7倍。