Algebraic multigrid (AMG) solvers have proven to be extremely efficient on distributed-memory architectures. However, when executed on modern multicore cluster architectures, we face new challenges that can significantly harm AMG's performance. We discuss our experiences on such an architecture and present a set of techniques that help users to overcome the associated problems, including thread and process pinning and correct memory associations. We have implemented most of the techniques in a MultiCore SUPport library (MCSup), which helps to map OpenMP applications to multicore machines. We present results using both an MPI-only and a hybrid MPI/OpenMP model
We study the performance of a two-level algebraic-multigrid algorithm, with a focus on the impact of...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Algebraic multigrid (AMG) solvers have proven to be extremely efficient on distributed-memory archit...
Algebraic multigrid (AMG) is a popular solver for large-scale scientific computing and an essential ...
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear syst...
Algebraic Multigrid (AMG) solvers are an essential component of many large-scale scientific simulati...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
The scalable implementation of multigrid methods for machines with several thousands of processors i...
The Algebraic Multigrid (AMG) method has over the years developed into an ecient tool for solving un...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
The paper proposes a combination of the subdomain deflation method and local algebraic multigrid as ...
MPI is the predominant model for parallel programming in technical high performance computing. With ...
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear syst...
We study the performance of a two-level algebraic-multigrid algorithm, with a focus on the impact of...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Algebraic multigrid (AMG) solvers have proven to be extremely efficient on distributed-memory archit...
Algebraic multigrid (AMG) is a popular solver for large-scale scientific computing and an essential ...
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear syst...
Algebraic Multigrid (AMG) solvers are an essential component of many large-scale scientific simulati...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
The scalable implementation of multigrid methods for machines with several thousands of processors i...
The Algebraic Multigrid (AMG) method has over the years developed into an ecient tool for solving un...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
The paper proposes a combination of the subdomain deflation method and local algebraic multigrid as ...
MPI is the predominant model for parallel programming in technical high performance computing. With ...
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear syst...
We study the performance of a two-level algebraic-multigrid algorithm, with a focus on the impact of...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Efficient solution of partial differential equations require a match between the algorithm and the t...