A Scalable Sharp-Interface Immersed Boundary Method for Moving Boundary Flow Simulation on Multi-GPU Systems

Abstract

Sharp-interface immersed boundary methods provide a versatile framework for simulating flows with complex moving boundaries, but their irregular data structures, dynamic sparsity, and discontinuous pressure operators present significant challenges for efficient multi-GPU implementation. This work presents a fully GPU-native, multi-GPU acceleration of the sharp-interface immersed boundary solver, ViCar3D. The implementation combines a hybrid OpenACC/CUDA programming model with a matrix decomposition that isolates dynamically changing immersed-boundary operators, GPU-optimized geometric kernels, asynchronous dual-stream sparse matrix--vector execution, and a symmetric-memory-based sparse communication strategy. A GPU-oriented iterative solver employing a preconditioned stabilized bi-conjugate gradient (BiCGStab) method is developed to efficiently treat the pressure Poisson equation on highly stretched Cartesian grids. The resulting framework preserves the accuracy and versatility of the original solver while delivering substantial acceleration and scalability for simulations involving complex moving and deforming immersed boundaries, thereby extending the applicability of sharp-interface immersed boundary methods to extreme-scale computational fluid dynamics.