Resource-Efficient Quantum Computing by Breaking Abstractions

Yunong Shi, Pranav Gokhale, Prakash Murali, Jonathan M. Baker, Casey Duckering, Yongshan Ding, Natalie C. Brown, Christopher Chamberland, Ali Javadi-Abhari, Andrew W. Cross, David I. Schuster, Kenneth R. Brown, Margaret Martonosi, Frederic T. Chong

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


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.

Original languageEnglish (US)
Article number9116963
Pages (from-to)1353-1370
Number of pages18
JournalProceedings of the IEEE
Issue number8
StatePublished - Aug 2020

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


  • Quantum computing (QC)
  • software design
  • system analysis and design


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