RECENT ADVANCES IN SPARSE DIRECT SOLVERS
Emmanuel Agullo, Patrick Amestoy, Alfredo Buttari, Abdou Guermouche, Guillaume Joslin, Jean-Yves L’Excellent, Xiaoye S. Li, Artem Napov, François-Henry Rouet, Sid-Lakhdar, Wissam M., Shen Wang, Clément Weisbecker, Ichitaro Yamazaki · NCSU Libraries Repository (North Carolina State University Libraries) · 2013
Direct methods for the solution of sparse systems of linear equations of the form A x = b are used in a wide range of numerical simulation applications.Such methods are based on the decomposition of the matrix into a product of triangular factors (e.g., A = L U ), followed by triangular solves.They are known for their numerical accuracy and robustness but are also characterized by a high memory consumption and a large amount of computations.Here we survey some research directions that are being investigated by the sparse direct solver community to alleviate these issues: memory-aware scheduling techniques, low-rank approximations, and distributed/shared memory hybrid programming.