Multi-level direct K-way hypergraph partitioning with multiple constraints and fixed vertices
Journal of Parallel and Distributed Computing
A parallel preconditioning strategy for efficient transistor-level circuit simulation
Proceedings of the 2009 International Conference on Computer-Aided Design
Efficient successor retrieval operations for aggregate query processing on clustered road networks
Information Sciences: an International Journal
A Matrix Partitioning Interface to PaToH in MATLAB
Parallel Computing
On Two-Dimensional Sparse Matrix Partitioning: Models, Methods, and a Recipe
SIAM Journal on Scientific Computing
Partitioning Hypergraphs in Scientific Computing Applications through Vertex Separators on Graphs
SIAM Journal on Scientific Computing
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This paper addresses the parallelization of the preconditioned iterative methods that use explicit preconditioners such as approximate inverses. Parallelizing a full step of these methods requires the coefficient and preconditioner matrices to be well partitioned. We first show that different methods impose different partitioning requirements for the matrices. Then we develop hypergraph models to meet those requirements. In particular, we develop models that enable us to obtain partitionings on the coefficient and preconditioner matrices simultaneously. Experiments on a set of unsymmetric sparse matrices show that the proposed models yield effective partitioning results. A parallel implementation of the right preconditioned BiCGStab method on a PC cluster verifies that the theoretical gains obtained by the models hold in practice.