Open AccessHybrid parallelisation scheme for the application of distributed near‐field sparse approximate inverse preconditioners on high‐performance computing clusters
Author(s) -
Delgado Carlos,
García Eliseo,
Somolinos Álvaro,
Cátedra Manuel Felipe
Publication year - 2020
Publication title -
iet microwaves, antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.555
H-Index - 69
eISSN - 1751-8733
pISSN - 1751-8725
DOI - 10.1049/iet-map.2019.0789
Subject(s) - computer science , scalability , preconditioner , message passing interface , distributed computing , scheme (mathematics) , memory footprint , parallel computing , message passing , computational science , field (mathematics) , supercomputer , inverse , distributed memory , computer engineering , theoretical computer science , algorithm , shared memory , iterative method , mathematics , mathematical analysis , geometry , database , pure mathematics , operating system
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.