Hybrid Parallelisation Scheme for the Application of Distributed Near-Field Sparse Approximate Inverse Preconditioners on High-Performance Computing Clusters

This work presents an efficient approach for the generation of distributed Sparse Approximate Inverse preconditioners based on the near-field coupling information for the analysis of electromagnetic problems on large computing clusters. This scheme combines the Message Passing Interface and Open Multi-Processing paradigms in order to minimise the CPU time and memory footprint of the preconditioner, making use of specific algorithms tailored to balance the load and reduce the amount ot information shared between nodes. Some representative examples provide insight into the scalability and performance of the described approach addressing large and realistic scenarios.