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In this paper, we present, evaluate and analyse the performance of parallel synchronous Jacobi algorithms by different partitioned procedures including band-row splitting, band-row sparsity pattern splitting and substructuring splitting, when solving sparse large linear systems. Numerical experiments performed on a set of academic 3D Laplace equation and on a real gravity matrices arising from the Chicxulub crater are exhibited, and show the impact of splitting on parallel synchronous iterations when solving sparse large linear systems. The numerical results clearly show the interest of substructuring methods compared to band-row splitting strategies.

2016 ieee intl conference on computational science and engineering (cse) and ieee intl conference on embedded and ubiquitous computing (euc) and 15th intl symposium on distributed computing and applications for business engineering (dcabes)

On the Stability and Performance of the Solution of Sparse Linear Systems by Partitioned Procedures