Li Ren, Rezaeiyan Yasser, Böhnert Tim, Schulman Alejandro, Ferreira Ricardo, Farkhani Hooman, Moradi Farshad
Department of Electrical and Computer Engineering, Aarhus University, 8200, Aarhus, Denmark.
INL-International Iberian Nanotechnology Laboratory, 4715-330, Braga, Portugal.
Sci Rep. 2024 May 2;14(1):10043. doi: 10.1038/s41598-024-60929-3.
In this work, we present fabricated magnetic tunnel junctions (MTJs) that can serve as magnetic memories (MMs) or vortex spin-torque nano-oscillators (STNOs) depending on the device geometry. We explore the heating effect on the devices to study how the performance of a neuromorphic computing system (NCS) consisting of MMs and STNOs can be enhanced by temperature. We further applied a neural network for waveform classification applications. The resistance of MMs represents the synaptic weights of the NCS, while temperature acts as an extra degree of freedom in changing the weights and TMR, as their anti-parallel resistance is temperature sensitive, and parallel resistance is temperature independent. Given the advantage of using heat for such a network, we envision using a vertical-cavity surface-emitting laser (VCSEL) to selectively heat MMs and/or STNO when needed. We found that when heating MMs only, STNO only, or both MMs and STNO, from 25 to 75 °C, the output power of the STNO increases by 24.7%, 72%, and 92.3%, respectively. Our study shows that temperature can be used to improve the output power of neural networks, and we intend to pave the way for future implementation of a low-area and high-speed VCSEL-assisted spintronic NCS.
在这项工作中，我们展示了所制备的磁性隧道结（MTJ），其可根据器件几何结构用作磁存储器（MM）或涡旋自旋扭矩纳米振荡器（STNO）。我们探究了器件上的热效应，以研究由MM和STNO组成的神经形态计算系统（NCS）的性能如何通过温度得到增强。我们进一步将神经网络应用于波形分类应用。MM的电阻代表NCS的突触权重，而温度作为改变权重和隧穿磁电阻（TMR）的额外自由度，因为它们的反平行电阻对温度敏感，而平行电阻与温度无关。鉴于在此类网络中利用热量的优势，我们设想在需要时使用垂直腔面发射激光器（VCSEL）来选择性地加热MM和/或STNO。我们发现，当仅加热MM、仅加热STNO或同时加热MM和STNO，温度从25℃升至75℃时，STNO的输出功率分别增加24.7%、72%和92.3%。我们的研究表明，温度可用于提高神经网络的输出功率，并且我们打算为未来实现低面积、高速的VCSEL辅助自旋电子NCS铺平道路。
