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arXiv 1809.04028cs.ETcond-mat.dis-nn
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概率自旋逻辑的p位

p-Bits for Probabilistic Spin Logic

Kerem Y. Camsari, Brian M. Sutton, Supriyo Datta

摘要:

我们引入概率或p比特的概念,介于数字电子学的标准比特和量子计算的新兴q比特之间。我们表明,低势垒磁铁或LBM的提供了一个自然的物理表示为p位,可以建立从垂直磁铁(PMA)设计为接近面内过渡或从圆形面内磁铁(IMA)。使用LBM作为自由层构建的磁性隧道结(MTJ)可以与标准NMOS晶体管组合,以提供用于大规模概率电路的三端子构建块,其可以被设计为执行有用的功能。有趣的是,这个三端单元看起来就像嵌入式MRAM技术中使用的1 T/MTJ器件,只有一个区别:使用LBM作为MTJ自由层。我们希望p位和p电路的概念将有助于为这项新兴技术开辟新的应用空间。然而,p位不需要涉及MTJ,任何波动电阻器都可以与晶体管组合来实现它,而使用传统CMOS技术的完全数字实现也是可能的。p-bit还在两个活跃但不相交的研究领域(即随机机器学习和量子计算)之间提供了一个概念上的桥梁。首先,存在基于p比特与二进制随机神经元(BSN)的相似性的应用,这是机器学习中的一个众所周知的概念。三端p位可以为BSN提供有效的硬件加速器。第二,有一些应用程序是基于p位的,就像穷人的q位。基于完整SPICE模拟的初步演示表明,包括量子退火在内的几个优化问题适用于p位实现,可以使用现有技术在室温下按比例放大。

英文摘要:

We introduce the concept of a probabilistic or p-bit, intermediate between the standard bits of digital electronics and the emerging q-bits of quantum computing. We show that low barrier magnets or LBM's provide a natural physical representation for p-bits and can be built either from perpendicular magnets (PMA) designed to be close to the in-plane transition or from circular in-plane magnets (IMA). Magnetic tunnel junctions (MTJ) built using LBM's as free layers can be combined with standard NMOS transistors to provide three-terminal building blocks for large scale probabilistic circuits that can be designed to perform useful functions. Interestingly, this three-terminal unit looks just like the 1T/MTJ device used in embedded MRAM technology, with only one difference: the use of an LBM for the MTJ free layer. We hope that the concept of p-bits and p-circuits will help open up new application spaces for this emerging technology. However, a p-bit need not involve an MTJ, any fluctuating resistor could be combined with a transistor to implement it, while completely digital implementations using conventional CMOS technology are also possible. The p-bit also provides a conceptual bridge between two active but disjoint fields of research, namely stochastic machine learning and quantum computing. First, there are the applications that are based on the similarity of a p-bit to the binary stochastic neuron (BSN), a well-known concept in machine learning. Three-terminal p-bits could provide an efficient hardware accelerator for the BSN. Second, there are the applications that are based on the p-bit being like a poor man's q-bit. Initial demonstrations based on full SPICE simulations show that several optimization problems including quantum annealing are amenable to p-bit implementations which can be scaled up at room temperature using existing technology.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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