Overall
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
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Received January 15, 2024
Accepted March 1, 2024
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Performance Benchmark of Cahn–Hilliard Equation Solver with Implementation of Semi-implicit Fourier Spectral Meth
Abstract
The performance scaling issue of phase-fi eld simulation is one that must be overcome to perform realistic large-scale threedimensional
prediction. The CUDA (Compute Unifi ed Device Architecture) parallel acceleration method developed over a
decade ago showed very good performance in terms of calculation speed, but was limited by the small size of memory on the
GPU. Recently, Apple Inc. has announced a GPU–CPU hybrid architecture, Apple silicon (M1 or later), and we examine the
advantages of this architecture for performing realistic large-scale phase-fi eld simulations and compare it to existing CUDA
architecture. When solving the Cahn–Hilliard equation using the FFT (Fast Fourier Transform) with CUDA architecture
developed by Nvidia and Apple silicon architecture developed by Apple Inc., we compared performance across hardware,
as well as other considerations such as form factor and heat dissipation of the workstation.
