Massive GPU-Parallelized Micromagnetic Modeling

ORAL

Abstract

In order to comprehensively investigate the multiphysical coupling in spintronic devices, it is essential to accelerate and parallelize microelectronics modeling to address the spatial and temporal disparities inherent in the relevant physics. Leveraging the GPU-accelerated software package we have developed, available at https://github.com/AMReX-Microelectronics, we have created a micromagnetics modeling tool called MagneX. This tool incorporates various crucial magnetic coupling mechanisms, including Zeeman coupling, demagnetization coupling, exchange coupling, Dzyaloshinskii-Moriya interaction (DMI) coupling, and crystalline anisotropy interaction.



We have rigorously validated MagneX's functionality using the mumag standard problem set, as well as problems with analytical solutions. With the capacity to explore complete physical interactions, this innovative approach offers a promising pathway to better understand and develop fully integrated spintronic and electronic systems.

* This work was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, the Microelectronics Co-Design Research Program, under contract no. DE-AC02-05-CH11231 (Codesign of Ultra-Low-Voltage Beyond CMOS Microelectronics) for the development of design tools for low-power microelectronics, and the U.S. Department of Energy's (DOE) Science Undergraduate Laboratory Internship (SULI) program. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This research leveraged the open source AMReX code, https://github .com /AMReX-Codes /amrex. We acknowledge all AMReX contributors. The authors thank Se Kwon Kim, Ramamoorthy Ramesh, Sajid Husain, Peter Meisenheimer, and Isaac Harris for valuable discussions.

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Presenters

  • Julian LePelch

    Lawrence Berkeley National Lab

Authors

  • Zhi (Jackie) Yao

    Lawrence Berkeley National Laboratory

  • Julian LePelch

    Lawrence Berkeley National Lab

  • Andy J Nonaka

    Lawrence Berkeley National Laboratory

  • Prabhat Kumar

    Lawrence Berkeley National Laboratory

  • Revathi Jambunathan

    Lawrence Berkeley National Laboratory