AbstractThe performance of algebraic multigrid (AMG) algorithms, implemented in 4-byte floating point arithmetic, is investigated on modern cluster architecture with multi-core CPUs. The algorithmic considerations comprise the effect of preconditioning in 4-byte floating point arithmetic on Krylov solvers using standard 8-byte floating point arithmetic. The data of basic linear algebra benchmarks are used to interpret the performance of AMG algorithms employed as linear solvers in computational fluid dynamics simulation tools
The numerical simulation of physical systems has become in recent years a fundamental tool to perfor...
In this survey paper, we compare native double precision solvers with emulated- and mixed- precision...
Abstract: The major portion of computing time in a computational fluid dynamic (CFD) flow solver is ...
Algebraic multigrid (AMG) is a popular solver for large-scale scientific computing and an essential ...
We explore a GPU implementation of a Krylov-accelerated algebraic multigrid (AMG) algorithm with fle...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
AbstractCurrent trends in high performance computing (HPC) are advancing towards the use of graphics...
Algebraic Multigrid (AMG) solvers are an essential component of many large-scale scientific simulati...
Will be published in the proceedings of the multigrid conference, Bristol, UK, September 1983Copy he...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
Algebraic multigrid (AMG) methods for directly solving coupled systems of partial differential equat...
The influence of multi-core central processing units and graphics processing units on several algebr...
Multigrid methods are well suited to large massively parallel computer architectures because they ar...
AMG is a parallel algebraic multigrid solver for linear systems arising from problems o
The numerical simulation of physical systems has become in recent years a fundamental tool to perfor...
In this survey paper, we compare native double precision solvers with emulated- and mixed- precision...
Abstract: The major portion of computing time in a computational fluid dynamic (CFD) flow solver is ...
Algebraic multigrid (AMG) is a popular solver for large-scale scientific computing and an essential ...
We explore a GPU implementation of a Krylov-accelerated algebraic multigrid (AMG) algorithm with fle...
In this work we focus on the application phase of AMG preconditioners, and in particular on the choi...
AbstractCurrent trends in high performance computing (HPC) are advancing towards the use of graphics...
Algebraic Multigrid (AMG) solvers are an essential component of many large-scale scientific simulati...
Will be published in the proceedings of the multigrid conference, Bristol, UK, September 1983Copy he...
The efficient utilization of parallel computational capabilities of modern hardware architecture is ...
Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear s...
Algebraic multigrid (AMG) methods for directly solving coupled systems of partial differential equat...
The influence of multi-core central processing units and graphics processing units on several algebr...
Multigrid methods are well suited to large massively parallel computer architectures because they ar...
AMG is a parallel algebraic multigrid solver for linear systems arising from problems o
The numerical simulation of physical systems has become in recent years a fundamental tool to perfor...
In this survey paper, we compare native double precision solvers with emulated- and mixed- precision...
Abstract: The major portion of computing time in a computational fluid dynamic (CFD) flow solver is ...