Isorropia is a package for combinatorial scientific computing, with focus on partitioning and load balancing, but also supports coloring and ordering of sparse matrices. Its main purpose is to assist with redistributing objects such as matrices and graphs in a parallel execution setting, to allow for more efficient computations. Isorropia partitions matrices by rows, and produces good maps for Epetra matrices (graphs). Isorropia should be called after the matrix (graph) is filled, so the sparsity pattern is known.
Keywords for this software
References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
- Cerveny, Jakub; Dobrev, Veselin; Kolev, Tzanio: Nonconforming mesh refinement for high-order finite elements (2019)
- Schornbaum, Florian; Rüde, Ulrich: Extreme-scale block-structured adaptive mesh refinement (2018)
- Baiges, Joan; Bayona, Camilo: RefficientLib: an efficient load-rebalanced adaptive mesh refinement algorithm for high-performance computational physics meshes (2017)
- Ibanez, Daniel A.; Seol, E. Seegyoung; Smith, Cameron W.; Shephard, Mark S.: PUMI: parallel unstructured mesh infrastructure (2016)
- Kalantzis, Vassilis; Li, Ruipeng; Saad, Yousef: Spectral Schur complement techniques for symmetric eigenvalue problems (2016)
- Marras, Simone; Kelly, James F.; Moragues, Margarida; Müller, Andreas; Kopera, Michal A.; Vázquez, Mariano; Giraldo, Francis X.; Houzeaux, Guillaume; Jorba, Oriol: A review of element-based Galerkin methods for numerical weather prediction: finite elements, spectral elements, and discontinuous Galerkin (2016)
- Mirzadeh, Mohammad; Guittet, Arthur; Burstedde, Carsten; Gibou, Frederic: Parallel level-set methods on adaptive tree-based grids (2016)
- Nivarti, Girish V.; Salehi, M. Mahdi; Bushe, W. Kendal: A mesh partitioning algorithm for preserving spatial locality in arbitrary geometries (2015)