Memory-based scheduling for a parallel multifrontal solver.

(eng) The memory usage of sparse direct solvers can be the bottleneck to solve large-scale problems. This paper describes dynamic scheduling strategies that aim at reducing the memory usage of a parallel direct solver. Combined to static modifications of the tasks dependency graph, experiments show that such techniques have a good potential to improve the memory usage of a parallel multifrontal solver, MUMPS