论文标题

用于内存计算的域壁挂式隧道连接旋转轨道扭矩设备和电路

Domain Wall-Magnetic Tunnel Junction Spin Orbit Torque Devices and Circuits for In-Memory Computing

论文作者

Alamdar, Mahshid, Leonard, Thomas, Cui, Can, Rimal, Bishweshwor P., Xue, Lin, Akinola, Otitoaleke G., Xiao, T. Patrick, Friedman, Joseph S., Bennett, Christopher H., Marinella, Matthew J., Incorvia, Jean Anne C.

论文摘要

传统计算存在紧迫的问题,尤其是用于完成数据密集型和实时任务,这激发了内存计算设备的开发,以存储信息并执行计算。磁性隧道连接(MTJ)内存元件可通过操纵域壁(DW)(磁域之间的过渡区域)来用于计算。但是,这些设备遇到了挑战:DW的自旋传输扭矩(STT)切换需要高电流,并且在DW轨道顶部创建MTJ支柱所需的多个蚀刻步骤导致隧道磁路线固定(TMR)降低。这些问题对设备和电路的实验研究有限。在这里,我们研究了三端结构域壁 - 磁性隧道连接(DW-MTJ)内存计算设备的原型与使用自旋传递扭矩相比,电阻 - 区域产物RA =31Ω-μm^2,接近未公平膜的RA,开关电流密度较低。两个设备电路显示设备之间的位传播。通过控制DW初始位置,开关电压中的设备初始化变化被证明将其减少到7%,我们显示的对应于DW-MTJ完整加法器模拟中的96%精度。这些结果在使用MTJ和DWS进行内存和神经形态计算应用方面取得了长足的进步。

There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing devices to both store information and perform computation. Magnetic tunnel junction (MTJ) memory elements can be used for computation by manipulating a domain wall (DW), a transition region between magnetic domains. But, these devices have suffered from challenges: spin transfer torque (STT) switching of a DW requires high current, and the multiple etch steps needed to create an MTJ pillar on top of a DW track has led to reduced tunnel magnetoresistance (TMR). These issues have limited experimental study of devices and circuits. Here, we study prototypes of three-terminal domain wall-magnetic tunnel junction (DW-MTJ) in-memory computing devices that can address data processing bottlenecks and resolve these challenges by using perpendicular magnetic anisotropy (PMA), spin-orbit torque (SOT) switching, and an optimized lithography process to produce average device tunnel magnetoresistance TMR = 164%, resistance-area product RA = 31 Ω-μm^2, close to the RA of the unpatterned film, and lower switching current density compared to using spin transfer torque. A two-device circuit shows bit propagation between devices. Device initialization variation in switching voltage is shown to be curtailed to 7% by controlling the DW initial position, which we show corresponds to 96% accuracy in a DW-MTJ full adder simulation. These results make strides in using MTJs and DWs for in-memory and neuromorphic computing applications.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源