Magnetization switching in nanoelements induced by the spin-transfer torque: Study by massively parallel micromagnetic simulations

Elena K Semenova,Dmitry V Berkov

doi:10.1063/1.5096264

Abstract

In this paper we present a detailed numerical study of magnetization switching in shape-anisotropic thin-film nanoelements. These elements are at present of the major interest for the applied solid state magnetism as main components of a new generation of conventional and spin-transfer-torque (STT) magnetic random access memory (MRAM) cells. To conduct this study, we have developed a highly efficient method for massively parallel micromagnetic simulations of the magnetization reversal in small-size nanoelements, which allows to fully exploit the large performance gain available on the GPU architecture (usually achievable only for large systems). We apply our method to the spin-torque-induced magnetization switching in elliptical nanoelements in presence of thermal fluctuations. Being able to compute simultaneously the reversal of up to 1000 such elements, we obtain the dependence of (i) the average switching time and (ii) the distribution density of switching times for individual elements on the element size with a high statistical accuracy. Analysis of these dependencies provides important insights into the physics of magnetization reversal in such systems. Comparison with analogous simulations in the macrospin approximation allows to determine the validity limits of the macrospin model. Our methodology can be applied for the optimization of the MRAM design regarding the information life time and significantly improve the prediction accuracy of write and read error rates of conventional and STT-based MRAM cells.

Highlights

Development of generations of magnetic memory, including conventional and spin-transfer torque magnetic random access memory (MRAM) requires detailed analysis and understanding of complicated switching processes in MRAM cells
In order to overcome this difficulty and to achieve the maximal acceleration offered by graphic processor units (GPU), we suggest a micromagnetic methodology for simultaneous modeling of magnetization reversal in a large number of nanoelements, where different elements are fully independent – they do not interact with each other and thermal fluctuations on different elements are not correlated
We have applied our method to studies of the magnetization reversal in a large ensemble of elliptical nanoelements under the influence of the spin-polarized current

Summary

Introduction

Development of generations of magnetic memory, including conventional and spin-transfer torque MRAM (see, e.g. Refs. 1–4) requires detailed analysis and understanding of complicated switching processes in MRAM cells. 1–4) requires detailed analysis and understanding of complicated switching processes in MRAM cells From this analysis we expect, in particular, thorough theoretical recommendations on how to decrease the write and read error rates (WER and RER) of this memory kind to the very low level acceptable for practical applications. To solve this problem (which is among the most important ones for these emerging technologies), we should be able to analyze a very large number of independent switching events in MRAM cells: this is necessary to gain sufficiently accurate statistics concerning the distribution of switching times at finite temperature in dependence on the cell geometry, external field, current strength etc. The GPU-based software provides high accelerations (compared to CPU) only for large system sizes, because only in this case the computational power of a GPU (which may have > 103 cores and several GBs of RAM) is fully exhausted

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