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On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Program Scheduling (2404.07882v1)

Published 11 Apr 2024 in cs.AR and quant-ph

Abstract: 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.

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References (21)
  1. Qiskit: An open-source framework for quantum computing. Accessed on: Mar 16 (2019).
  2. Quantum supremacy using a programmable superconducting processor. Nature 574, 7779 (2019), 505–510.
  3. Generation of genuine entanglement up to 51 superconducting qubits. Nature 619, 7971 (2023), 738–742.
  4. Variational quantum algorithms. Nature Reviews Physics 3, 9 (2021), 625–644.
  5. IBM Quantum Computing. 2019. Retrieved Nov 10, 2023 from https://www.ibm.com/quantum.
  6. A case for multi-programming quantum computers. In Proc. of MICRO. 291–303.
  7. A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028 (2014).
  8. Lov K Grover. 1996. A fast quantum mechanical algorithm for database search. In Proc. of STOC. 212–219.
  9. Tackling the qubit mapping problem for NISQ-era quantum devices. In Proc. of ASPLOS. 1001–1014.
  10. Lei Liu and Xinglei Dou. 2021. Qucloud: A new qubit mapping mechanism for multi-programming quantum computing in cloud environment. In 2021 IEEE HPCA. IEEE, 167–178.
  11. Mark EJ Newman. 2004. Fast algorithm for detecting community structure in networks. Physical review E 69, 6 (2004), 066133.
  12. Michael A Nielsen and Isaac L Chuang. 2010. Quantum computation and quantum information. Cambridge university press.
  13. A hardware-aware heuristic for the qubit mapping problem in the nisq era. IEEE TQE 1 (2020), 1–14.
  14. Siyuan Niu and Aida Todri-Sanial. 2023. Enabling multi-programming mechanism for quantum computing in the NISQ era. Quantum 7 (2023), 925.
  15. QuantumCTek Quantum Cloud Platform. 2022. Retrieved Nov 15, 2023 from https://quantumctek-cloud.com/.
  16. John Preskill. 2018. Quantum computing in the NISQ era and beyond. Quantum 2 (2018), 79.
  17. Accelerating variational quantum algorithms using circuit concurrency. arXiv:2109.01714 (2021).
  18. Peter W Shor. 1994. Algorithms for quantum computation: discrete logarithms and factoring. In Proc. of FOCS. Ieee, 124–134.
  19. Qubit allocation. In Proc. of CGO. 113–125.
  20. Revkit: a Toolkit for reversible circuit design. J. Multiple Valued Log. Soft Comput. (2012).
  21. Swamit S Tannu and Moinuddin K Qureshi. 2019. Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In Proc. of ASPLOS. 987–999.
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