152K-computer-node parallel scalable implicit solver for dynamic nonlinear earthquake simulation.

We have used data learning and low-precision computation to develop an implicit solver that demonstrates high performance up to 152,352 computer nodes (609,408 MPI processes × 12 OpenMP threads = 7,312,896 parallel computation) and conducted an unprecedented ultra-large-scale analysis of ultra-high-fidelity fault-structure systems using nonlinear dynamic finite element analysis on three-dimensional low-order unstructured elements. The developed solver achieved 25.45-fold speedup from the state of the art solver on Fugaku and attained weak scaling efficiency of 93.7% from 9.391 billion DOF@578 computer nodes to 1.201 trillion DOF@73,984 computer nodes on performance measurement problems. Moreover, a realistic 324 billion DOF application example, which is difficult to obtain performance for, was computed in high performance. Since the developed solver is based on a highly generalizable algorithm, it is expected to contribute not only to earthquake simulation on Fugaku but also to the enhancement of similar applications in other fields and on other supercomputers.