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The authors accelerated 3D Fourier pseudospectral phase-field modeling within the MEUMAPPS C++ framework by coupling performance-portable distributed GPU execution with high-order implicit-explicit (IMEX) time integration. This overcomes decades-long computational barriers that restricted microstructure kinetics simulations to small domains and unrepresentative timescales, preventing real-time experimental integration. Scaling to 4,096 GPUs on a 12-billion-grid-point system, the approach achieved up to a 501x speedup over CPU baselines and simulated a 7-hour precipitate aging heat treatment in just 5.5 hours.
Large-scale microstructural materials simulations have officially broken the real-time barrier, modeling a 1.5-billion-grid-point alloy precipitate aging process faster than physical heat treatment on exascale-class GPU clusters.
Three-dimensional phase-field simulations are a gold-standard for microstructure prediction for materials, but their computational cost often limits application-relevant calculations to modest domain sizes and timescales. Here, we present a holistic approach for accelerating Fourier pseudospectral phase-field simulations by combining performance-portable GPU computing, large-scale distributed-memory parallelism, and high-order implicit-explicit time integration within the MEUMAPPS C++ framework. We demonstrate this approach with a 1.5-billion-grid-point simulation of the growth and coarsening of 1,920 gamma''precipitates in a Ni-Nb-Fe alloy. The simulated seven-hour heat treatment is completed in 5.5 hours, making the calculation faster than real time and an estimated 217-501x faster than a CPU-only, first-order baseline. This performance makes three-dimensional simulations of thousands of interacting precipitates tractable, enabling quantitative studies ocollective microstructural phenomena, large simulation ensembles, and real-time integration into controlling and interpreting experiments. Benchmarking shows single-node GPU speedups of up to 17.5x relative to comparable CPU resources, near-ideal strong scaling to 4096 GPUs for a 12-billion-grid-point problem, and a further 2.6-2.9x acceleration from fourth-order time integration at scientifically relevant error tolerances. These results establish a performance-portable strategy for exploiting leadership-scale GPU systems that is applicable to a broad class of Fourier pseudospectral simulations beyond phase-field models such as fluid dynamics and crystal plasticity simulations.