@article{b0c7ddaad83c4478a3618bba9fd91996,
title = "Resource-Efficient Quantum Computing by Breaking Abstractions",
abstract = "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.",
keywords = "Quantum computing (QC), software design, system analysis and design",
author = "Yunong Shi and Pranav Gokhale and Prakash Murali and Baker, {Jonathan M.} and Casey Duckering and Yongshan Ding and Brown, {Natalie C.} and Christopher Chamberland and Ali Javadi-Abhari and Cross, {Andrew W.} and Schuster, {David I.} and Brown, {Kenneth R.} and Margaret Martonosi and Chong, {Frederic T.}",
note = "Funding Information: 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. (Corresponding author: Frederic T. Chong.) Yunong Shi and David I. Schuster are with the Department of Physics, The University of Chicago, Chicago, IL 60637 USA. Pranav Gokhale, Jonathan M. Baker, Casey Duckering, Yongshan Ding, and Frederic T. Chong are with the Department of Computer Science, The University of Chicago, Chicago, IL 60637 USA (e-mail: chong@cs.uchicago.edu). Prakash Murali and Margaret Martonosi are with the Department of Computer Science, Princeton University, Princeton, NJ 08544 USA. Natalie C. Brown and Kenneth R. Brown are with the Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708 USA. Christopher Chamberland is with the AWS Center for Quantum Computing, Pasadena, CA 91125 USA, and also with the Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA 91125 USA. Ali Javadi-Abhari and Andrew W. Cross are with the IBM Thomas J. Watson Research Center, Ossining, NY 10598 USA. Publisher Copyright: {\textcopyright} 1963-2012 IEEE.",
year = "2020",
month = aug,
doi = "10.1109/JPROC.2020.2994765",
language = "English (US)",
volume = "108",
pages = "1353--1370",
journal = "Proceedings of the Institute of Radio Engineers",
issn = "0018-9219",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "8",
}