Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers

Prakash Murali, Jonathan M. Baker, Ali Javadi Abhari, Frederic T. Chong, Margaret Rose Martonosi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

A massive gap exists between current quantum computing (QC) prototypes, and the size and scale required for many proposed QC algorithms. Current QC implementations are prone to noise and variability which affect their reliability, and yet with less than 80 quantum bits (qubits) total, they are too resource-constrained to implement error correction. The term Noisy Intermediate-Scale Quantum (NISQ) refers to these current and near-term systems of 1000 qubits or less. Given NISQ's severe resource constraints, low reliability, and high variability in physical characteristics such as coherence time or error rates, it is of pressing importance to map computations onto them in ways that use resources efficiently and maximize the likelihood of successful runs. This paper proposes and evaluates backend compiler approaches to map and optimize high-level QC programs to execute with high reliability on NISQ systems with diverse hardware characteristics. Our techniques all start from an LLVM intermediate representation of the quantum program (such as would be generated from high-level QC languages like Scaffold) and generate QC executables runnable on the IBM Q public QC machine. We then use this framework to implement and evaluate several optimal and heuristic mapping methods. These methods vary in how they account for the availability of dynamic machine calibration data, the relative importance of various noise parameters, the different possible routing strategies, and the relative importance of compile-time scalability versus runtime success. Using realsystem measurements, we show that fine grained spatial and temporal variations in hardware parameters can be exploited to obtain an average 2.9x (and up to 18x) improvement in program success rate over the industry standard IBM Qiskit compiler. Despite small qubit counts, NISQ systems will soon be large enough to demonstrate "quantum supremacy," i.e., an advantage over classical computing. Tools like ours provide significant improvements in program reliability and execution time, and offer high leverage in accelerating progress towards quantum supremacy.

Original languageEnglish (US)
Title of host publicationASPLOS 2019 - 24th International Conference on Architectural Support for Programming Languages and Operating Systems
PublisherAssociation for Computing Machinery
Pages1015-1029
Number of pages15
ISBN (Electronic)9781450362405
DOIs
StatePublished - Apr 4 2019
Event24th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2019 - Providence, United States
Duration: Apr 13 2019Apr 17 2019

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS

Conference

Conference24th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2019
CountryUnited States
CityProvidence
Period4/13/194/17/19

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture

Keywords

  • noise-adaptive compilation
  • qubit mapping

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  • Cite this

    Murali, P., Baker, J. M., Abhari, A. J., Chong, F. T., & Martonosi, M. R. (2019). Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers. In ASPLOS 2019 - 24th International Conference on Architectural Support for Programming Languages and Operating Systems (pp. 1015-1029). (International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS). Association for Computing Machinery. https://doi.org/10.1145/3297858.3304075