### Abstract

As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of 'let physics do the computing' can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.

Original language | English (US) |
---|---|

Article number | 8565896 |

Pages (from-to) | 73-89 |

Number of pages | 17 |

Journal | Proceedings of the IEEE |

Volume | 107 |

Issue number | 1 |

DOIs | |

State | Published - Jan 1 2019 |

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### All Science Journal Classification (ASJC) codes

- Electrical and Electronic Engineering

### Cite this

*Proceedings of the IEEE*,

*107*(1), 73-89. [8565896]. https://doi.org/10.1109/JPROC.2018.2878854

}

*Proceedings of the IEEE*, vol. 107, no. 1, 8565896, pp. 73-89. https://doi.org/10.1109/JPROC.2018.2878854

**Computing with Networks of Oscillatory Dynamical Systems.** / Raychowdhury, Arijit; Parihar, Abhinav; Smith, Gus Henry; Narayanan, Vijaykrishnan; Csaba, Gyorgy; Jerry, Matthew; Porod, Wolfgang; Datta, Suman.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Computing with Networks of Oscillatory Dynamical Systems

AU - Raychowdhury, Arijit

AU - Parihar, Abhinav

AU - Smith, Gus Henry

AU - Narayanan, Vijaykrishnan

AU - Csaba, Gyorgy

AU - Jerry, Matthew

AU - Porod, Wolfgang

AU - Datta, Suman

PY - 2019/1/1

Y1 - 2019/1/1

N2 - As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of 'let physics do the computing' can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.

AB - As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of 'let physics do the computing' can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.

UR - http://www.scopus.com/inward/record.url?scp=85058126870&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058126870&partnerID=8YFLogxK

U2 - 10.1109/JPROC.2018.2878854

DO - 10.1109/JPROC.2018.2878854

M3 - Article

VL - 107

SP - 73

EP - 89

JO - Proceedings of the IEEE

JF - Proceedings of the IEEE

SN - 0018-9219

IS - 1

M1 - 8565896

ER -