Accelerating three-dimensional seismic wave simulations on ARM using a hybrid half-precision and scalable vector extension approach

SUMMARY Seismic simulation is fundamental for understanding earthquake physics and mitigating seismic hazards, but accurate seismic modelling requires fine computational grids, imposing severe memory and computational challenges. Traditional modelling solvers, relying on single-precision floating-point 32-bit (FP32) and scalar register-based computation, suffer from excessive memory consumption, low-memory access efficiency and limited computational efficiency. Compared with FP32, half-precision floating-point 16-bit (FP16) reduces memory consumption by 50 per cent and improves memory access efficiency; relative to scalar registers, ARM’s Scalable Vector Extension (SVE) registers provide vectorized single-instruction multiple-data capabilities, significantly accelerating computation. However, leveraging the advantages of FP16 and SVE involves challenges such as FP16 overflow/underflow, SVE stencil adaptation, and SVE data misalignment from FP16 storage with FP32 arithmetic. Therefore, this study proposes three approaches on the ARM (Advanced RISC Machine) architecture: FP16-based, SVE-accelerated and FP16-SVE hybrid; each is designed to tackle the respective challenges while exploiting FP16 memory efficiency and SVE computational acceleration. Correspondingly, the three solvers are implemented, validated and benchmarked on both hypothetical models and real-world earthquake scenarios. The results of these solvers show near-perfect agreement with the reference solver, confirming their accuracy across diverse seismic scenarios. Moreover, the FP16-SVE hybrid solver halved memory usage and achieved up to 3$\times$ computational speedup, delivering more than 2.3$\times$ acceleration in the real-world earthquake simulation. The gains in high efficiency of memory and computation highlight the capability of the FP16-SVE hybrid solver to support large-scale, real-time seismic simulations and efficient earthquake hazard assessment on ARM platforms.