Section: New Results
Sparse linear solvers
Participants : Jocelyne Erhel, David Imberti.
Sparse linear systems arise in computational science and engineering. The goal is to reduce the memory requirements and the computational cost, by means of high performance computing algorithms. We introduce a new variation on s-step GMRES in order to improve its stability, reduce the number of iterations necessary to ensure convergence, and thereby improve parallel performance. In doing so, we develop a new block variant that allows us to express the stability difficulties in s-step GMRES more fully.
Grants and projects: EXA2CT 8.2.1, EoCoE 8.2.2, C2S@EXA 8.1.7