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This study introduces a novel ternary memory system using voltage-controlled magnetic anisotropy (VCMA) and skyrmions. This energy-efficient system offers a 2X area improvement and is suitable for high-density deep neural networks.

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Area of Science:

  • Spintronics
  • Materials Science
  • Computer Engineering

Background:

  • Multistate memory systems offer higher data density than binary systems.
  • Voltage-controlled magnetic anisotropy (VCMA) provides energy-efficient writing for non-volatile magnetic memory.

Purpose of the Study:

  • To introduce a novel, energy-efficient, non-volatile ternary memory system.
  • To demonstrate the implementation of ternary states using skyrmion-mediated VCMA switching.
  • To evaluate the performance and potential applications of the proposed ternary memory.

Main Methods:

  • Utilized a perpendicular magnetic tunnel junction (p-MTJ) for ternary state implementation.
  • Investigated VCMA-based switching in the presence of room temperature thermal noise.
  • Quantified switching probability, energy consumption, and area efficiency.

Main Results:

  • Achieved 99% switching probability for ternary states {−1, 0, +1} with ~2 fJ energy consumption per switching operation.
  • Demonstrated a 2X improvement in area and ~10^4X improvement in energy efficiency compared to STT-based multistate memories.
  • Validated the feasibility of ternary states using ferromagnetic up, down, and skyrmion configurations.

Conclusions:

  • The proposed VCMA-based skyrmion-mediated ternary memory is highly energy-efficient and offers significant area advantages.
  • This technology holds potential for high-density, energy-efficient in-memory computing, particularly for quantized deep neural networks.
  • The system demonstrates robust performance under thermal noise, making it suitable for practical applications.