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一个可扩展的神经网络模拟器,采用基于MRAM的混合信号电路

Jua Lee^1,2, Jiho Song¹, Hyeon Seong Im¹

¹College of Information and Communication Engineering, Sungkyunkwan University (SKKU), Suwon, Republic of Korea.

Frontiers in neuroscience

|June 24, 2025

概括

这项研究介绍了一种使用磁电抗性随机访问存储器 (MRAM) 模拟大脑功能在上的新框架. 该系统精确模拟神经动力学,为先进的神经形态计算铺平了道路.

科学领域:

神经形态工程的神经形态工程
材料科学材料科学材料科学
计算神经科学是一种神经科学.

背景情况:

生物神经网络激发了先进的计算架构.
了解复杂的神经系统是一个重大的科学挑战.
磁电阻式随机访问存储器 (MRAM) 为非易失性,CMOS兼容的神经形态设备提供了潜力.

研究的目的:

开发一种混合信号框架,用MRAM模拟生物神经网络行为.
为了解决MRAM在模拟计算中的低开/关电阻比的局限性.
为了证明强大的模拟神经处理与MRAM用于可扩展的神经仿真.

主要方法:

多位MRAM突触阵列与模拟电路的集成.
实现当前减去架构以产生多层次的突触电流.
设计具有可调节工作频率的芯片,用于灵活的时间尺度仿真.

主要成果:

成功模拟关键的神经功能:泄漏整合和火 (LIF) 动态,刺激和抑制后突触潜能 (EPSP/IPSP),耐火期和侧向抑制.
展示了强大的模拟神经处理,克服了MRAM的低开/关比限制.
在制造芯片上对生物启发的神经动态进行实验验证.

结论:

拟议的基于MRAM的框架能够准确模拟生物神经动态.
这种方法促进了可扩展和实时模拟神经形态计算.
开发的技术对推进由大脑启发的计算系统具有前景.

关键词:

模拟神经网络是一种模拟神经网络.生物神经网络是生物神经网络.抑制后突触潜力的抑制后突触潜力侧面抑制的阻碍.耐火期是一种耐火期.

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