As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the smaller scales of the ...
As we approach the Exascale computing era, disruptive changes in the software landscape are required...
In the last decades, numerical simulation has experienced tremendous improvements driven by massive ...
TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impac...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
In this talk, we will look at the current state of high performance computing and look at the next s...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
David Keyes, Dean of Mathematical and Computer Sciences and Engineering and a Professor of Applied M...
This dissertation studies the sources of poor performance in scientific computing codes based on par...
AbstractWe examine the computational efficiency of linear algebra components in iterative solvers fo...
The Petascale Computing Enabling Technologies (PCET) project addressed challenges arising from curre...
This paper discusses the main performance barriers for solving a large number of independent ordinar...
As we approach the Exascale computing era, disruptive changes in the software landscape are required...
In the last decades, numerical simulation has experienced tremendous improvements driven by massive ...
TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impac...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solv...
In this talk, we will look at the current state of high performance computing and look at the next s...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
David Keyes, Dean of Mathematical and Computer Sciences and Engineering and a Professor of Applied M...
This dissertation studies the sources of poor performance in scientific computing codes based on par...
AbstractWe examine the computational efficiency of linear algebra components in iterative solvers fo...
The Petascale Computing Enabling Technologies (PCET) project addressed challenges arising from curre...
This paper discusses the main performance barriers for solving a large number of independent ordinar...
As we approach the Exascale computing era, disruptive changes in the software landscape are required...
In the last decades, numerical simulation has experienced tremendous improvements driven by massive ...
TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impac...