The solution of linear systems is often the most computational consuming kernel in large complex numerical simulations. In this talk, we will describe a parallel algebraic hierarchical linear solver for sparse linear systems. The numerical scheme based on a partition of the adjacency graph of a sparse matrix, that leads to the solution of a Schur complement system, will be presented as well as the related preconditioning technique. Parallel numerical experiments of the hybrid direct/iterative technique will be described on 3D examples from both academic and industrial relevance. Prospective for implementations on many- cores heterogeneous systems on runtime systems will be discussed.