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Energy-efficient superparamagnetic Ising machine and its application to traveling salesman problems.

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  • 1Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.

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|April 24, 2024
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Researchers developed an Ising annealing computer using superparamagnetic tunnel junctions (SMTJs) to tackle complex computational problems like the traveling salesman problem (TSP). This novel approach offers improved energy efficiency and scalability for artificial intelligence challenges.

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Area of Science:

  • Materials Science
  • Computer Engineering
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) growth intensifies computational demands for solving complex non-deterministic polynomial-time (NP)-hard problems.
  • Existing Ising computers face challenges including high power consumption and limited scalability.

Purpose of the Study:

  • To experimentally demonstrate an Ising annealing computer utilizing superparamagnetic tunnel junctions (SMTJs).
  • To address the computational burden and limitations of current NP-hard problem-solving methods.

Main Methods:

  • Construction of an Ising annealing computer with 80 superparamagnetic tunnel junctions (SMTJs) and all-to-all connections.
  • Application of the system to solve a 70-city traveling salesman problem (TSP), equivalent to a 4761-node Ising problem.
  • Leveraging intrinsic SMTJ randomness, a global annealing scheme, and an efficient algorithm.

Main Results:

  • The SMTJ-based Ising annealer demonstrated superior performance over other Ising schemes in power consumption and energy efficiency.
  • Successfully solved a complex 70-city traveling salesman problem.
  • Proposed a scalable cross-bar array architecture for integration with magnetic random-access memories.

Conclusions:

  • The SMTJ-based Ising computer presents a highly energy-efficient and scalable solution for complex computational problems.
  • This approach offers a promising pathway for solving challenging problems with constrained hardware resources.
  • SMTJ-based Ising computers are strong candidates for future unconventional computing paradigms.