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Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks

Wooseok Choi, Thomas van Bodegraven, Jelle Verest, Olivier Maher, Donato Francesco Falcone, Antonio La Porta, Daniel Jubin, Bert Jan Offrein, Siegfried Karg, Valeria Bragaglia, Aida Todri-Sanial

TL;DR

The paper tackles the ONN scalability problem, where coupling connections scale as $O(N^2)$ with network size. It introduces a BEOL-integrated ReRAM crossbar that provides dense, programmable coupling for CMOS ring-oscillator neurons, enabling in-memory, phase-encoded computation. The experimental demonstration with a conductive-metal-oxide ReRAM (CMO/HfOx) in a $5×5$ 1T1R array validates analog programming, robust retention, and a $2×2$ associative memory network that retrieves patterns via phase locking. The results suggest a viable path toward large-scale, on-chip ONNs with online learning capabilities.

Abstract

We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. A ReRAM crossbar array chip, integrated into the Back End of Line (BEOL) of CMOS technology, is leveraged to establish dense coupling elements between oscillator neurons, allowing phase-encoded analog information to be processed in-memory. We also realize an ONN architecture design with the coupling ReRAM array. To validate the architecture experimentally, we present a conductive metal oxide (CMO)/HfOx ReRAM array chip integrated with a 2-by-2 ring oscillator-based network. The system successfully retrieves patterns through correct binary phase locking. This proof of concept underscores the potential of ReRAM technology for large-scale, integrated ONNs.

Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks

TL;DR

The paper tackles the ONN scalability problem, where coupling connections scale as with network size. It introduces a BEOL-integrated ReRAM crossbar that provides dense, programmable coupling for CMOS ring-oscillator neurons, enabling in-memory, phase-encoded computation. The experimental demonstration with a conductive-metal-oxide ReRAM (CMO/HfOx) in a 1T1R array validates analog programming, robust retention, and a associative memory network that retrieves patterns via phase locking. The results suggest a viable path toward large-scale, on-chip ONNs with online learning capabilities.

Abstract

We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. A ReRAM crossbar array chip, integrated into the Back End of Line (BEOL) of CMOS technology, is leveraged to establish dense coupling elements between oscillator neurons, allowing phase-encoded analog information to be processed in-memory. We also realize an ONN architecture design with the coupling ReRAM array. To validate the architecture experimentally, we present a conductive metal oxide (CMO)/HfOx ReRAM array chip integrated with a 2-by-2 ring oscillator-based network. The system successfully retrieves patterns through correct binary phase locking. This proof of concept underscores the potential of ReRAM technology for large-scale, integrated ONNs.

Paper Structure

This paper contains 8 sections, 7 figures.

Figures (7)

  • Figure 1: (a) Quadratic increase in coupling connections with network size growth. (b) Two coupling methods: conventional passive components vs. ReRAM devices.
  • Figure 2: (a) The fabrication of CMO/HfO$_{\rm x}$ ReRAM chip, including (b) 1T1R arrays. (c) The distribution of initial forming voltages and (d) the following resistive switching of ReRAM devices on the wire-bonded $5\times5$ array. (e) The analog programming capability with 60 ns fast pulses is also demonstrated.
  • Figure 3: (a) 2-by2 ONN and (b) its architecture implementation with ReRAM crossbar array. The experimental retention data of the implemented coupling resistance are shown in (c).
  • Figure 4: Examples of resulting phase locking depending on (a) positive and (b) negative coupling between two CMOS ring oscillators (9-stage).
  • Figure 5: Operation flow of the experiments and assembled ONN hardware system.
  • ...and 2 more figures