Energy Efficiency of Quantum Statevector Simulation at Scale

Jakub Adamski; James Richings; Oliver Brown

doi:10.48550/arXiv.2308.07402

Energy Efficiency of Quantum Statevector Simulation at Scale

Jakub Adamski, James Richings, Oliver Brown

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Classical simulations are essential for the development of quantum computing, and their exponential scaling can easily fill any modern supercomputer. In this paper we consider the performance and energy consumption of large Quantum Fourier Transform (QFT) simulations run on ARCHER2, the UK's National Supercomputing Service, with QuEST toolkit. We take into account CPU clock frequency and node memory size, and use cache-blocking to rearrange the circuit, which minimises communications. We find that using 2.00GHz instead of 2.25GHz can save as much as 25% of energy at 5% increase in runtime. Higher node memory also has the potential to be more efficient, and cost the user fewer CUs, but at higher runtime penalty. Finally, we present a cache-blocking QFT circuit, which halves the required communication. All our optimisations combined result in 40% faster simulations and 35% energy savings in 44 qubit simulations on 4,096 ARCHER2 nodes.

Original language	English
Title of host publication	Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
Publisher	Association for Computing Machinery (ACM)
Pages	1871–1875
Number of pages	5
DOIs	https://doi.org/10.48550/arXiv.2308.07402
Publication status	Accepted/In press - 8 Sept 2023
Event	The International Conference for High Performance Computing, Networking, Storage, and Analysis - Denver, United States Duration: 12 Nov 2023 → 17 Nov 2023 https://sc23.supercomputing.org/

Publication series

Name
ISSN (Print)	2167-4329
ISSN (Electronic)	2167-4337

Conference

Conference	The International Conference for High Performance Computing, Networking, Storage, and Analysis
Abbreviated title	SC23
Country/Territory	United States
City	Denver
Period	12/11/23 → 17/11/23
Internet address	https://sc23.supercomputing.org/

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10.48550/arXiv.2308.07402Licence: Creative Commons: Attribution (CC-BY)

Energy Efficiency_ADAMSKI_DOA08092023_AFV_CC BYAccepted author manuscript, 546 KBLicence: Creative Commons: Attribution (CC-BY)

Cite this

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title = "Energy Efficiency of Quantum Statevector Simulation at Scale",

abstract = "Classical simulations are essential for the development of quantum computing, and their exponential scaling can easily fill any modern supercomputer. In this paper we consider the performance and energy consumption of large Quantum Fourier Transform (QFT) simulations run on ARCHER2, the UK's National Supercomputing Service, with QuEST toolkit. We take into account CPU clock frequency and node memory size, and use cache-blocking to rearrange the circuit, which minimises communications. We find that using 2.00GHz instead of 2.25GHz can save as much as 25% of energy at 5% increase in runtime. Higher node memory also has the potential to be more efficient, and cost the user fewer CUs, but at higher runtime penalty. Finally, we present a cache-blocking QFT circuit, which halves the required communication. All our optimisations combined result in 40% faster simulations and 35% energy savings in 44 qubit simulations on 4,096 ARCHER2 nodes.",

author = "Jakub Adamski and James Richings and Oliver Brown",

year = "2023",

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doi = "10.48550/arXiv.2308.07402",

language = "English",

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pages = "1871–1875",

booktitle = "Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis",

address = "United States",

note = "The International Conference for High Performance Computing, Networking, Storage, and Analysis, SC23 ; Conference date: 12-11-2023 Through 17-11-2023",

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Adamski, J, Richings, J & Brown, O 2023, Energy Efficiency of Quantum Statevector Simulation at Scale. in Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. Association for Computing Machinery (ACM), pp. 1871–1875, The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver, Colorado, United States, 12/11/23. https://doi.org/10.48550/arXiv.2308.07402

Energy Efficiency of Quantum Statevector Simulation at Scale. / Adamski, Jakub; Richings, James ; Brown, Oliver.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. Association for Computing Machinery (ACM), 2023. p. 1871–1875.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Energy Efficiency of Quantum Statevector Simulation at Scale

AU - Adamski, Jakub

AU - Richings, James

AU - Brown, Oliver

PY - 2023/9/8

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N2 - Classical simulations are essential for the development of quantum computing, and their exponential scaling can easily fill any modern supercomputer. In this paper we consider the performance and energy consumption of large Quantum Fourier Transform (QFT) simulations run on ARCHER2, the UK's National Supercomputing Service, with QuEST toolkit. We take into account CPU clock frequency and node memory size, and use cache-blocking to rearrange the circuit, which minimises communications. We find that using 2.00GHz instead of 2.25GHz can save as much as 25% of energy at 5% increase in runtime. Higher node memory also has the potential to be more efficient, and cost the user fewer CUs, but at higher runtime penalty. Finally, we present a cache-blocking QFT circuit, which halves the required communication. All our optimisations combined result in 40% faster simulations and 35% energy savings in 44 qubit simulations on 4,096 ARCHER2 nodes.

AB - Classical simulations are essential for the development of quantum computing, and their exponential scaling can easily fill any modern supercomputer. In this paper we consider the performance and energy consumption of large Quantum Fourier Transform (QFT) simulations run on ARCHER2, the UK's National Supercomputing Service, with QuEST toolkit. We take into account CPU clock frequency and node memory size, and use cache-blocking to rearrange the circuit, which minimises communications. We find that using 2.00GHz instead of 2.25GHz can save as much as 25% of energy at 5% increase in runtime. Higher node memory also has the potential to be more efficient, and cost the user fewer CUs, but at higher runtime penalty. Finally, we present a cache-blocking QFT circuit, which halves the required communication. All our optimisations combined result in 40% faster simulations and 35% energy savings in 44 qubit simulations on 4,096 ARCHER2 nodes.

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M3 - Conference contribution

SP - 1871

EP - 1875

BT - Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis

PB - Association for Computing Machinery (ACM)

T2 - The International Conference for High Performance Computing, Networking, Storage, and Analysis

Y2 - 12 November 2023 through 17 November 2023

ER -

Energy Efficiency of Quantum Statevector Simulation at Scale

Abstract / Description of output

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Conference

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