Chronos: a general purpose classical AMG solver for high performance computing
The numerical simulation of physical systems has become in recent years a fundamental
tool to perform analyses and predictions in several application fields, spanning from industry
to the academy. As far as large-scale simulations are concerned, one of the most
computationally expensive tasks is the solution of linear systems of equations arising from
the discretization of the partial differential equations governing physical processes. This
work presents Chronos, a collection of linear algebra functions specifically designed for the …
tool to perform analyses and predictions in several application fields, spanning from industry
to the academy. As far as large-scale simulations are concerned, one of the most
computationally expensive tasks is the solution of linear systems of equations arising from
the discretization of the partial differential equations governing physical processes. This
work presents Chronos, a collection of linear algebra functions specifically designed for the …
The numerical simulation of physical systems has become in recent years a fundamental tool to perform analyses and predictions in several application fields, spanning from industry to the academy. As far as large-scale simulations are concerned, one of the most computationally expensive tasks is the solution of linear systems of equations arising from the discretization of the partial differential equations governing physical processes. This work presents Chronos, a collection of linear algebra functions specifically designed for the solution of large, sparse linear systems on massively parallel computers. Its emphasis is on modern, effective, and scalable Algebraic Multigrid (AMG) preconditioners for high performance computing (HPC). This work describes the numerical algorithms and the main structures of this software suite, especially from an implementation standpoint. Several numerical results arising from practical mechanics and fluid dynamics applications with hundreds of millions of unknowns are addressed and compared with other state-of-the-art linear solvers, proving Chronos's efficiency and robustness.
Society for Industrial and Applied Mathematics
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