通过电调节的磁道连接点启用的射频螺旋神经网络
Zixi Wang1, Yuqi Duan1, Chengzhi Chen1
1Fert Beijing Institute, School of Integrated Circuit Science and Engineering, Beihang University, Beijing, 100191, China.
Advanced materials (Deerfield Beach, Fla.)
|September 25, 2025
概括
研究人员使用电调磁道连接 (MTJs) 开发了节能的自旋电子神经形态系统. 这项创新大大降低了能源消耗,并提高了先进计算应用的可扩展性.
科学领域:
- 这就是Spintronics.
- 神经形态计算是一种神经形态计算.
- 材料科学 材料科学 材料科学
背景情况:
- 磁道连接 (MTJs) 显示了节能神经形态计算的前景.
- 现有的基于MTJ的系统经常使用磁场,导致高能耗和有限的可扩展性.
- 在MTJ中,有限的可调节带宽限制了突触数量和网络扩展.
研究的目的:
- 通过使用三终端MTJs实验实现可电调的自旋突触和神经元.
- 展示一个可扩展和节能的神经形态计算系统.
- 探索spintronic设备在先进AI应用中的潜力.
主要方法:
- 用了三端MTJ用于旋转突触和神经元.
- 使用旋转轨道扭矩来精确调节突触重量和神经元输出频率.
- 具有完全连接和卷积架构的刺激多层网络.
主要成果:
- 实现了对突触重量和神经元输出频率的精确电气控制.
- 与现有方法相比,能源消耗减少了21倍.
- 在多层网络中证明了高精度 (无人机分类上99.2%,时尚-MNIST上92.0%).
- 卷积设计减少了对振荡器频率通道的需求.
结论:
- 成功展示了可扩展,高频率和节能的全螺旋式神经形态系统.
- 拟议的方法为未来的神经形态计算提供了一个兼容的平台.
- 电气调能力克服了基于MTJ的神经网络的磁场调制的局限性.
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