QASMTrans: A QASM Quantum Transpiler Framework for NISQ Devices

Fei Hua, Meng Wang, Gushu Li, Bo Peng, Chenxu Liu, Muqing Zheng, Samuel Stein, Yufei Ding, Eddy Z. Zhang, Travis Humble, Ang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The success of a quantum algorithm hinges on the ability to orchestrate a successful application induction. Detrimental overheads in mapping general quantum circuits to physically implementable routines can be the deciding factor between a successful and erroneous circuit induction. In QASMTrans, we focus on the problem of rapid circuit transpilation. Transpilation plays a crucial role in converting high-level, machine-agnostic circuits into machine-specific circuits constrained by physical topology and supported gate sets. The efficiency of transpilation continues to be a substantial bottleneck, especially when dealing with larger circuits requiring high degrees of inter-qubit interaction. QASMTrans is a high-performance C++ quantum transpiler framework that demonstrates 3-1111 × speedups compared to the commonly used Qiskit transpiler. We observe speedups on large dense circuits such as 'uccsd-n24' which require gates. QASMTrans successfully transpiles the aforementioned circuits in 7.9s, whilst Qiskit needs 502 seconds with optimization 1 and exceeds an hour of transpilation time with optimization 3. With QASMTrans providing transpiled circuits in a fraction of the time of prior transpilers, potential design space exploration, and heuristic-based transpiler design becomes substantially more tractable. QASMTrans is released at http://github.com/pnnl/qasmtrans.

Original languageEnglish
Title of host publicationProceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
PublisherAssociation for Computing Machinery
Pages1468-1477
Number of pages10
ISBN (Electronic)9798400707858
DOIs
StatePublished - Nov 12 2023
Event2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 - Denver, United States
Duration: Nov 12 2023Nov 17 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
Country/TerritoryUnited States
CityDenver
Period11/12/2311/17/23

Funding

This material is mainly based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-design Center for Quantum Advantage (C2QA) under contract number DE-SC0012704. The contribution from Meng Wang, Yufei Ding, and Travis Humble are supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center (QSC). This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. We acknowledge support from Microsoft’s Azure Quantum for providing credits and access to the ion-trap quantum hardware. The Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830.

FundersFunder number
Microsoft’sDE-AC05-76RL01830
National Quantum Information Science Research CentersDE-SC0012704
Quantum Science Center
U.S. Department of Energy
Office of ScienceDE-AC05-00OR22725
Lawrence Berkeley National LaboratoryDE-AC02-05CH11231

    Keywords

    • Compiler
    • IO
    • Optimizaton
    • QASMTrans

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