GPU-accelerated Immersed Boundary Method for the efficient simulation of biomedical fluid-structure interactions

Immersed boundary methods have become the most usable and useful tools for simulation of biomedical fluid-structure interaction, e.g., in the aortic valve of human heart. In such problems, complex geometry and motion of the soft tissue impose significant computational cost for bodyfitted- mesh methods. Resorting to a fixed Eulerian grid for the flow simulation along with the immersed boundary method to model the interaction with the soft tissue eliminates the expensive mesh generation and updating costs. Nevertheless, the computational cost for the geometry operations including adaptive search algorithms are still significant. Herein, we implemented the immersed boundary kernels with CUDA to be transferred and executed on thousands of parallel threads on the general purpose GPU. Host-device memory optimisation along with optimal usage of GPU multiprocessors results in a boosted performance in fluid-structure interaction simulation.