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 ...
We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulati...
The numerical simulations of real-world engineering problems create models with several millions or ...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
Many scientific applications require the solution of large and sparse linear systems of equations us...
AbstractCurrent trends in high performance computing (HPC) are advancing towards the use of graphics...
Many scientific applications require the solution of large and sparse linear systems of equations us...
Fully implicit petroleum reservoir simulations result in huge, often very ill-conditioned linear sys...
Algebraic multigrid (AMG) methods for directly solving coupled systems of partial differential equat...
AbstractThe performance of algebraic multigrid (AMG) algorithms, implemented in 4-byte floating poin...
Algebraic multigrid (AMG) is one of the most effective iterative methods for the solution of large, ...
Algebraic multigrid solvers and preconditioners are level of the art solution techniques for many t...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
The research conducted in this thesis provides a robust implementation of a preconditioned iterative...
Abstract. Linear systems are required to solve in many scientific applications and the solution of t...
The development of high performance, massively parallel computers and the increasing demands of comp...
We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulati...
The numerical simulations of real-world engineering problems create models with several millions or ...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
Many scientific applications require the solution of large and sparse linear systems of equations us...
AbstractCurrent trends in high performance computing (HPC) are advancing towards the use of graphics...
Many scientific applications require the solution of large and sparse linear systems of equations us...
Fully implicit petroleum reservoir simulations result in huge, often very ill-conditioned linear sys...
Algebraic multigrid (AMG) methods for directly solving coupled systems of partial differential equat...
AbstractThe performance of algebraic multigrid (AMG) algorithms, implemented in 4-byte floating poin...
Algebraic multigrid (AMG) is one of the most effective iterative methods for the solution of large, ...
Algebraic multigrid solvers and preconditioners are level of the art solution techniques for many t...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
The research conducted in this thesis provides a robust implementation of a preconditioned iterative...
Abstract. Linear systems are required to solve in many scientific applications and the solution of t...
The development of high performance, massively parallel computers and the increasing demands of comp...
We develop scalable algorithms and object-oriented code frameworks for terascale scientific simulati...
The numerical simulations of real-world engineering problems create models with several millions or ...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...