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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.11 No.1
- 발행연도
- 2022.2
- 수록면
- 40 - 48 (9page)
- DOI
- 10.5573/IEIESPC.2021.11.1.40
이용수
초록· 키워드
오류제보하기
Quantum computers are superior to existing classical supercomputers in terms of run time for specific tasks, and various studies on quantum computers are in progress. Despite this, there is a significant gap in technology between available technologies and actual quantum computers on the noisy intermediate-scale quantum-scale. Currently, various quantum algorithms have been implemented and verified using quantum simulations. Therefore, the runtime performance of a quantum circuit can be verified in the same environment as a real quantum machine. A quantum compiler compiles quantum circuits. When a quantum circuit is compiled, logical qubits in a quantum circuit should be mapped to physical qubits, called qubit mapping. As qubit mapping is an NP-Complete problem, the compilation time increases exponentially according to the number of qubits. Therefore, various studies on effective qubit mapping techniques have been developed to accelerate the execution time. This paper proposes a new parallelized Qubit mapping algorithm. The proposed method consists of three-step processes: one circuit is divided into several circuits; the SABRE enhanced algorithm is executed on each circuit in parallel and then merged. The performance was evaluated using 10 benchmarks. The experimental results revealed an acceleration of up to 6.42x and an average speed up of 4.8x, with an average overhead of 1.03x in terms of the number of gates obtained. The proposed method outperformed the well-known modern qubit-mapping algorithm in terms of the execution time with exponential speedup improvement.
목차
Abstract
1. Introduction
2. Background and Related Works
3. Parallelized Qubit Mapping Algorithm
4. Performance Evaluation
5. Conclusion
References
참고문헌 (26)
참고문헌 신청
A. Steane, “Quantum computing,” Rep. Prog. Phys., vol. 61, no. 2, pp. 117-173, Feb. 1998. Article (CrossRef Link)
T. Hey, “Quantum computing: An introduction,” Comput. Control Eng. J. vol. 10, no. 3, pp. 105-112, Jun. 1999. Article (CrossRef Link)
“D-Wave Systems | The Practical Quantum Computing Company.” (accessed Oct. 18, 2021). Article Link
F. Hu et al., “Quantum computing cryptography: Finding cryptographic Boolean functions with quantum annealing by a 2000 qubit D-wave quantum computer,” Phys. Lett. A, vol. 384, no. 10, p. 126214, Apr. 2020. Article (CrossRef Link)
F. Hu, L. Lamata, C. Wang, X. Chen, E. Solano, and M. Sanz, “Quantum Advantage in Cryptography with a Low-Connectivity Quantum Annealer,” Phys. Rev. Applied, vol. 13, no. 5, p. 054062, May 2020. Article (CrossRef Link)
T. Hey, “Quantum computing: An introduction,” Comput. Control Eng. J. vol. 10, no. 3, pp. 105-112, Jun. 1999. Article (CrossRef Link)
“D-Wave Systems | The Practical Quantum Computing Company.” (accessed Oct. 18, 2021). Article Link
F. Hu et al., “Quantum computing cryptography: Finding cryptographic Boolean functions with quantum annealing by a 2000 qubit D-wave quantum computer,” Phys. Lett. A, vol. 384, no. 10, p. 126214, Apr. 2020. Article (CrossRef Link)
F. Hu, L. Lamata, C. Wang, X. Chen, E. Solano, and M. Sanz, “Quantum Advantage in Cryptography with a Low-Connectivity Quantum Annealer,” Phys. Rev. Applied, vol. 13, no. 5, p. 054062, May 2020. Article (CrossRef Link)
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