Parallel implementation of the sparse grid combination technique in high dimensions presents many complexity challenges. We enumerate these challenges, classifying them respectively as computational, algorithmic, and software complexity. We discuss strategies for overcoming the individual complexity barriers. We describe our architecture for a software framework that will allow its users to build complex multiple grid solver applications
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...
In this paper, we investigate the good parallel computing properties of sparse-grid solution techniq...
Parallel implementation of the sparse grid combination technique in high dimensions presents many co...
AbstractThe sparse grid combination technique provides a framework to solve high-dimensional numeric...
The sparse grid combination technique provides a frame-work to solve high dimensional numerical prob...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and hav...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
119 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.The design and implementation...
This paper presents a new software framework for solving large and sparse linear systems on current ...
textabstractThe good parallel computing properties of sparse-grid solution techniques are investigat...
This paper presents a new software framework for solving large and sparse linear systems on current ...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...
In this paper, we investigate the good parallel computing properties of sparse-grid solution techniq...
Parallel implementation of the sparse grid combination technique in high dimensions presents many co...
AbstractThe sparse grid combination technique provides a framework to solve high-dimensional numeric...
The sparse grid combination technique provides a frame-work to solve high dimensional numerical prob...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and hav...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
119 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.The design and implementation...
This paper presents a new software framework for solving large and sparse linear systems on current ...
textabstractThe good parallel computing properties of sparse-grid solution techniques are investigat...
This paper presents a new software framework for solving large and sparse linear systems on current ...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Abstract Efficiently solving large sparse linear systems on loosely coupled net-works of computers i...
In this paper, we investigate the good parallel computing properties of sparse-grid solution techniq...