From Charge to Spin and Spin to Charge: Stochastic Magnets for Probabilistic Switching
Kerem Y. Çamsarı, Punyashloka Debashis, Vaibhav Ostwal, Ahmed Zeeshan Pervaiz, Tingting Shen, Zhihong Chen, Supriyo Datta, Joerg Appenzeller
Abstract
As the rapid pace of Moore's Law has been slowing down, there has been intense activity to “reinvent the transistor.” An emerging paradigm is to complement the existing complementary metal-oxide-semiconductor (CMOS) technology with new functionalities, rather than finding a drop-in replacement for it. In this article, we discuss such a complementary approach that we call probabilistic spin logic (PSL) based on the concept of a probabilistic or p-bit. p-bits fluctuate between 0 and 1 and can be imagined in between deterministic bits that are either 0 or 1 and quantum bits that are a superposition of 0 and 1. Interconnected circuits built out of p-bits (p-circuits) can be broadly useful for machine learning and quantum computing in the solution of problems that conventional CMOS may not be particularly suited for. Although such p-bits can be implemented using standard CMOS technology, we will show that the inherent physics of nanomagnets can naturally provide an energy efficient and scalable p-bit implementation through the use of low-barrier magnetic tunnel junctions (MTJs). In this article, we provide a general description of p-bits and p-circuits and discuss their applications. We review experimental progress toward constructing p-bits and p-circuits exploiting the inherent stochasticity of nanomagnets, from a physics/device/circuits perspective. In particular, we identify building blocks for “write” and “read” operations that can be used in different combinations to construct functional p-bits and p-circuits. Finally, we discuss the prospects and challenges of PSL as an emerging, unconventional computing paradigm for a beyond CMOS era.