In this paper we will discuss some approaches to fault-tolerance for solving partial differential equations. In particular we will discuss how one can combine the solution from multiple grids using ideas related to the sparse grid combination technique and multivariate extrapolation. By utilising the redundancy between the solutions on different grids we will demonstrate how this approach can be adapted for fault-tolerance. Much of this will be achieved by assuming error expansions and examining the extrapolation of these when various solutions from different grids are combined
Ultra-large–scale simulations via solving partial differential equations (PDEs) require very large c...
SIGLEAvailable from TIB Hannover: RN 7878(9121) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - T...
We investigate a new way of choosing combination coefficients for the sparse grid combination techni...
AbstractA key issue confronting petascale and exascale computing is the growth in probability of sof...
One of the challenges for efficiently and effectively using petascale and exascale computers is the ...
A key issue confronting petascale and exascale computing is the growth in probability of soft and ha...
One of the challenges for efficiently and effectively using petascale and exascale computers is the ...
In previous works, approaches for fault tolerant computation of PDEs were described which utilise fl...
This paper continues to develop a fault tolerant extension of the sparse grid combination technique ...
This paper continues to develop a fault tolerant extension of the sparse grid combination technique ...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
Functionals related to a solution of a problem, usually modelled by partial differential equations, ...
The data volume of Partial Differential Equation (PDE) based ultra-large-scale scientific simul...
A number of experimental implementations of the multigrid algorithm for the solution of systems of p...
A key issue confronting petascale and exascale computing is the growth in probability of soft and ha...
Ultra-large–scale simulations via solving partial differential equations (PDEs) require very large c...
SIGLEAvailable from TIB Hannover: RN 7878(9121) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - T...
We investigate a new way of choosing combination coefficients for the sparse grid combination techni...
AbstractA key issue confronting petascale and exascale computing is the growth in probability of sof...
One of the challenges for efficiently and effectively using petascale and exascale computers is the ...
A key issue confronting petascale and exascale computing is the growth in probability of soft and ha...
One of the challenges for efficiently and effectively using petascale and exascale computers is the ...
In previous works, approaches for fault tolerant computation of PDEs were described which utilise fl...
This paper continues to develop a fault tolerant extension of the sparse grid combination technique ...
This paper continues to develop a fault tolerant extension of the sparse grid combination technique ...
Sparse grids are a recently introduced new technique for discretizing partial differential equations...
Functionals related to a solution of a problem, usually modelled by partial differential equations, ...
The data volume of Partial Differential Equation (PDE) based ultra-large-scale scientific simul...
A number of experimental implementations of the multigrid algorithm for the solution of systems of p...
A key issue confronting petascale and exascale computing is the growth in probability of soft and ha...
Ultra-large–scale simulations via solving partial differential equations (PDEs) require very large c...
SIGLEAvailable from TIB Hannover: RN 7878(9121) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - T...
We investigate a new way of choosing combination coefficients for the sparse grid combination techni...