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Evaluating Ising Processing Units with Integer Programming

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11494))

Abstract

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, present new opportunities for hybrid-optimization algorithms that are hardware accelerated by these devices. In this work, we propose the idea of an Ising processing unit as a computational abstraction for reasoning about these emerging devices. The challenges involved in using and benchmarking these devices are presented and commercial mixed integer programming solvers are proposed as a valuable tool for the validation of these disparate hardware platforms. The proposed validation methodology is demonstrated on a D-Wave 2X adiabatic quantum computer, one example of an Ising processing unit. The computational results demonstrate that the D-Wave hardware consistently produces high-quality solutions and suggests that as IPU technology matures it could become a valuable co-processor in hybrid-optimization algorithms.

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Notes

  1. 1.

    For MIP solvers, the runtime includes the computation of the optimally certificate.

  2. 2.

    The source code is available at https://github.com/lanl-ansi/ under the repository names bqpjson, dwig and bqpsolvers.

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Authors and Affiliations

  1. Los Alamos National Laboratory, Los Alamos, NM, USA

    Carleton Coffrin, Harsha Nagarajan & Russell Bent

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  1. Carleton Coffrin
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  2. Harsha Nagarajan
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  3. Russell Bent
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Correspondence to Carleton Coffrin .

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Editors and Affiliations

  1. Ecole Polytechnique de Montréal, Montréal, QC, Canada

    Louis-Martin Rousseau

  2. University of Western Macedonia, Kozani, Greece

    Kostas Stergiou

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Coffrin, C., Nagarajan, H., Bent, R. (2019). Evaluating Ising Processing Units with Integer Programming. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_11

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  • DOI: https://doi.org/10.1007/978-3-030-19212-9_11

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