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Resource-Efficient Quantum Computing by Breaking Abstractions

Shi, Yunong and Gokhale, Pranav and Murali, Prakash and Baker, Jonathan M. and Duckering, Casey and Ding, Yongshan and Brown, Natalie C. and Chamberland, Christopher and Javadi-Abhari, Ali and Cross, Andrew W. and Schuster, David I. and Brown, Kenneth R. and Martonosi, Margaret and Chong, Frederic T. (2020) Resource-Efficient Quantum Computing by Breaking Abstractions. Proceedings of the IEEE, 108 (8). pp. 1353-1370. ISSN 0018-9219. doi:10.1109/jproc.2020.2994765.

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Building a quantum computer that surpasses the computational power of its classical counterpart is a great engineering challenge. Quantum software optimizations can provide an accelerated pathway to the first generation of quantum computing (QC) applications that might save years of engineering effort. Current quantum software stacks follow a layered approach similar to the stack of classical computers, which was designed to manage the complexity. In this review, we point out that greater efficiency of QC systems can be achieved by breaking the abstractions between these layers. We review several works along this line, including two hardware-aware compilation optimizations that break the quantum instruction set architecture (ISA) abstraction and two error-correction/information-processing schemes that break the qubit abstraction. Last, we discuss several possible future directions.

Item Type:Article
Related URLs:
URLURL TypeDescription
Shi, Yunong0000-0002-0824-6107
Gokhale, Pranav0000-0003-1946-4537
Murali, Prakash0000-0003-3378-8589
Duckering, Casey0000-0002-4656-9644
Ding, Yongshan0000-0002-2338-1315
Chamberland, Christopher0000-0003-3239-5783
Schuster, David I.0000-0002-8989-1801
Brown, Kenneth R.0000-0001-7716-1425
Martonosi, Margaret0000-0001-9683-8032
Chong, Frederic T.0000-0001-9282-4645
Additional Information:© 2020 IEEE. Manuscript received October 1, 2019; revised December 29, 2019 and March 23, 2020; accepted May 5, 2020. Date of publication June 15, 2020; date of current version July 17, 2020. This work was supported in part by Enabling Practical-scale Quantum Computing (EPiQC), an NSF Expedition in Computing, under Grant CCF-1730449/1832377/1730082; in part by Software-Tailored Architectures for Quantum co-design (STAQ) under Grant NSF Phy-1818914; and in part by DOE under Grant DE-SC0020289 and Grant DE-SC0020331. Yunong Shi is funded in part by the NSF QISE-NET fellowship under grant number 1747426. Pranav Gokhale is supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. This work was completed in part with resources provided by the University of Chicago Research Computing Center.
Group:Institute for Quantum Information and Matter
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0020289
Department of Energy (DOE)DE-SC0020331
National Defense Science and Engineering Graduate (NDSEG) FellowshipUNSPECIFIED
Subject Keywords:Quantum computing (QC), software design, system analysis and design
Issue or Number:8
Record Number:CaltechAUTHORS:20200624-155135309
Persistent URL:
Official Citation:Y. Shi et al., "Resource-Efficient Quantum Computing by Breaking Abstractions," in Proceedings of the IEEE, vol. 108, no. 8, pp. 1353-1370, Aug. 2020, doi: 10.1109/JPROC.2020.2994765
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104024
Deposited By: George Porter
Deposited On:25 Jun 2020 14:23
Last Modified:16 Nov 2021 18:27

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