As we approach the Exascale computing era, disruptive changes in the software landscape are required to tackle the challenges posed by manycore CPUs and accelerators. We discuss the development of a new `Exascale enabled' sparse solver repository (the ESSR) that addresses these challenges---from fundamental design considerations and development processes to actual implementations of some prototypical iterative schemes for computing eigenvalues of sparse matrices. Key features of the ESSR include holistic performance engineering, tight integration between software layers and mechanisms to mitigate hardware failures
Out-of-core sparse direct solvers reduce the amount of main memory needed to factorize and solve lar...
The increasing complexity of hardware and software environments in high-performance computing poses ...
In this paper, we present the main algorithmic features in the software package SuperLU DIST, a dis...
As we approach the Exascale computing era, disruptive changes in the software landscape are required...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
The ESSEX project is funded by the German DFG priority programme 1648 Software for Exascale Computin...
As modern supercomputers approach the Exascale, many numerical libraries face scalability issues due...
<p>Presented at SIAM CSE17 Minisymposium: Software Productivity and Sustainability for CSE and Data ...
In the German Research Foundation project ESSEX (Equipping Sparse Solvers for Exascale), we develop ...
Multiphysics simulations are at the core of modern Computer Aided Engineering (CAE) allowing the ana...
In the German Research Foundation (DFG) project ESSEX (Equipping Sparse Solvers for Exascale), we de...
The ESSEX project is funded by the German DFG priority programme 1648 "Software for Exascale Computi...
As on-node parallelism increases and the performance gap between the processor and the memory system...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
We present a benchmark of iterative solvers for sparse matrices. The benchmark contains several comm...
Out-of-core sparse direct solvers reduce the amount of main memory needed to factorize and solve lar...
The increasing complexity of hardware and software environments in high-performance computing poses ...
In this paper, we present the main algorithmic features in the software package SuperLU DIST, a dis...
As we approach the Exascale computing era, disruptive changes in the software landscape are required...
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly...
The ESSEX project is funded by the German DFG priority programme 1648 Software for Exascale Computin...
As modern supercomputers approach the Exascale, many numerical libraries face scalability issues due...
<p>Presented at SIAM CSE17 Minisymposium: Software Productivity and Sustainability for CSE and Data ...
In the German Research Foundation project ESSEX (Equipping Sparse Solvers for Exascale), we develop ...
Multiphysics simulations are at the core of modern Computer Aided Engineering (CAE) allowing the ana...
In the German Research Foundation (DFG) project ESSEX (Equipping Sparse Solvers for Exascale), we de...
The ESSEX project is funded by the German DFG priority programme 1648 "Software for Exascale Computi...
As on-node parallelism increases and the performance gap between the processor and the memory system...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
We present a benchmark of iterative solvers for sparse matrices. The benchmark contains several comm...
Out-of-core sparse direct solvers reduce the amount of main memory needed to factorize and solve lar...
The increasing complexity of hardware and software environments in high-performance computing poses ...
In this paper, we present the main algorithmic features in the software package SuperLU DIST, a dis...