Iterative solvers based on Krylov subspace methods are widely used for the solution of the problems that appear in large- scale parallel scienti c simulations. These solvers, when parallelized, often su er from global synchronization overheads due to the collective communication operations. Block CG variants have the advantage of reduced communication overheads at the expense of increased computation per iteration. The aim of this project is the scalable parallelization of two such block CG variants, Orthomin and Orthodir, proposed by FET-HPC project NLAFET to enable the use of these methods on future exascale systems through reducing number of the synchronization points. We investigate 1D- and 2D-partitioning of the sparse coecient matrix ...
Parallel iterative solvers are widely used in solving large sparse linear systems of equations on la...
In this work, we analyze the scalability of inexact two-level balancing domain decomposition by cons...
We present a parallelizable SSOR preconditioning scheme for Krylov subspace iterative solvers which ...
International audienceThe hybrid scheme block row-projection method implemented in the ABCD Solver i...
Parallel computing a b s t r a c t A block tridiagonal matrix is factored with minimal fill-in using...
Krylov methods are widely used for solving large sparse linear systems of equations.On distributed a...
. The efficient solution of irregular sparse linear systems on a distributed memory parallel compute...
Krylov solvers are key kernels in many large-scale science and engineering applications for solving ...
International audienceKrylov methods are widely used for solving large sparse linear systems of equa...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Iterative methods for solving large sparse systems of linear equations are widely used in many HPC a...
Parallel algorithms for solving sparse symmetric matrix systems that might result from the cell-cent...
. We study the parallel implementations of a block iterative method in heterogeneous computing envir...
We consider Krylov subspace methods for solving a linear system of equations on parallel computer wi...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
Parallel iterative solvers are widely used in solving large sparse linear systems of equations on la...
In this work, we analyze the scalability of inexact two-level balancing domain decomposition by cons...
We present a parallelizable SSOR preconditioning scheme for Krylov subspace iterative solvers which ...
International audienceThe hybrid scheme block row-projection method implemented in the ABCD Solver i...
Parallel computing a b s t r a c t A block tridiagonal matrix is factored with minimal fill-in using...
Krylov methods are widely used for solving large sparse linear systems of equations.On distributed a...
. The efficient solution of irregular sparse linear systems on a distributed memory parallel compute...
Krylov solvers are key kernels in many large-scale science and engineering applications for solving ...
International audienceKrylov methods are widely used for solving large sparse linear systems of equa...
Numerical methods related to Krylov subspaces are widely used in large sparse numerical linear algeb...
Iterative methods for solving large sparse systems of linear equations are widely used in many HPC a...
Parallel algorithms for solving sparse symmetric matrix systems that might result from the cell-cent...
. We study the parallel implementations of a block iterative method in heterogeneous computing envir...
We consider Krylov subspace methods for solving a linear system of equations on parallel computer wi...
International audienceKrylov methods such as GMRES are efficient iterative methods to solve large sp...
Parallel iterative solvers are widely used in solving large sparse linear systems of equations on la...
In this work, we analyze the scalability of inexact two-level balancing domain decomposition by cons...
We present a parallelizable SSOR preconditioning scheme for Krylov subspace iterative solvers which ...