The Strong Sensitivity of the Characteristics of Binary Stochastic Neurons Employing Low Barrier Nanomagnets to Small Geometrical Variations

TL;DR

This paper demonstrates that binary stochastic neurons based on low-energy nanomagnets are highly sensitive to small geometric variations, affecting their activation functions and response times, which impacts device consistency and integration.

Contribution

It reveals the extreme sensitivity of nanomagnet-based BSNs to geometric variations and explores how shape encoding affects energy and response time trade-offs.

Findings

1% diameter change alters response time by ~4 times.

10% diameter change doubles the pinning current.

Elliptical cross-sections reduce energy dissipation but increase response time.

Abstract

Binary stochastic neurons (BSNs) are excellent activators for machine learning. An ideal platform for implementing them are low- or zero-energy-barrier nanomagnets (LBMs) possessing in-plane anisotropy (e.g. circular or slightly elliptical disks) whose fluctuating magnetization encodes a probabilistic (p-) bit. Here, we show that such a BSN's activation function, the pinning current (which pins the output to a particular binary state), and the response time - all exhibit strong sensitivity to very slight geometric variations in the LBM's cross section. A mere 1% change in the diameter of a circular nanomagnet in any arbitrary direction can alter the response time by a factor of ~4 at room temperature and a 10% change can alter the pinning current by a factor of ~2. All this causes large device-to-device variation which is detrimental to integration. We also show that the energy dissipation is lowered but the response time is increased by replacing a circular cross-section with a slightly elliptical one and then encoding the p-bit in the magnetization component along the major axis. Encoding the p-bit in the magnetization component along the minor axis has the opposite effect. The energy-delay-product, however, is relatively independent of whether the cross-section is a circle or an ellipse and which magnetization component encodes the p-bit in the case of the ellipse.