Low Energy Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets With Fabrication Defects
Low Energy Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets With Fabrication Defects
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DOI：
10.1109/lmag.2019.2929484
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发表时间：
2019-01-01
影响因子：
1.2
通讯作者：
Bandyopadhyay, Supriyo
中科院分区：
文献类型：
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作者：
Abeed, Md. Ahsanul;Bandyopadhyay, Supriyo
许多注意力都集中在低能垒纳米磁体（LBM）的设计上，由于热噪声，其磁化随时间随机变化，用于作为机器学习硬件加速器的二进制随机神经元（BSN）。BSN的性能取决于两个重要参数：与LBM中的随机磁化动力学相关联的相关时间τ（c），以及自旋极化钉扎电流I-p，其在选定的时间内在选定的方向上稳定LBM的磁化。我们发现，在LBM中常见的制造缺陷使得这两个参数不可预测，因为它们对缺陷非常敏感。这使得具有真实的LBM的BSN的设计非常具有挑战性。除非LBM在制造时有非常严格的控制，否则使用它们的BSN可能不可靠或产量很低。
Much attention has been focused on the design of low energy barrier nanomagnets (LBMs), whose magnetizations vary randomly in time owing to thermal noise, for use in binary stochastic neurons (BSNs) that serve as hardware accelerators for machine learning. The performance of BSNs depends on two important parameters: the correlation time tau(c) associated with the random magnetization dynamics in an LBM, and the spin-polarized pinning current I-p, which stabilizes the magnetization of an LBM in a chosen direction within a chosen time. We show that common fabrication defects in LBMs make these two parameters unpredictable because they are strongly sensitive to the defects. That makes the design of BSNs with real LBMs very challenging. Unless the LBMs are fabricated with extremely tight control, the BSNs that use them could be unreliable or suffer from poor yield.