AMG4PSBLAS Linear Algebra Package brings Alya one step closer to Exascale

In this work, we interfaced to the Alya code the development version of a software framework for efficient and reliable solution of the sparse linear systems for computation of the pressure field at each time step. We developed a software module in Alya's kernel to interface the current development version of the PSBLAS package (Parallel Sparse Basic Linear Algebra Subroutines) and the sibling package AMG4PSBLAS. PSBLAS implements parallel basic linear algebra operations and support routines for sparse matrix management tailored for iterative sparse linear solvers on parallel distributedmemory computers, supporting heterogeneity at the node level. It has gone under extension within the EoCoE-II project with the primary goal to face the exascale challenge. AMG4PSBLAS is a package of Algebraic MultiGrid (AMG) preconditioners built on the top of PSBLAS, which inherits all the flexibility and efficiency features of the PSBLAS infrastructure, and implements up-to-date AMG preconditioners exploiting aggregation of unknowns for the setup of the AMG hierarchy. Many preconditioners employing different aggregation schemes, AMG cycles, and parallel smoothers are available and were tested within the simulation carried out with the Alya code. Results show that the new solvers vastly outperform the original Deflated Conjugate Gradient method available in the Alya kernel in terms of scalability and parallel efficiency and represent a very promising software layer to move the Alya code towards exascale.