6 citations · 12 across the 7 of their papers we have counts for
9 papers
Mixed-Precision Computing for Scientific Discovery: Formats, Co-Design, and Responsible Approximation
Emmanuel Agullo, Hartwig Anzt, Daniel Bauer +37
Reduced and mixed precision have moved from a niche optimization to a central design axis in scientific computing and engineering, driven by energy constraints, heterogeneous accel…
An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
I. Daužickaitė, M. A. Freitag, S. Gürol +4
Variational data assimilation is a technique for combining measured data with dynamical models. It is a key component of Earth system state estimation and is commonly used in weath…
Mixed precision sketching for least-squares problems and its application in GMRES-based iterative refinement
Erin Carson, Ieva Daužickaitė
Sketching-based preconditioners have been shown to accelerate the solution of dense least-squares problems with coefficient matrices having substantially more rows than columns. Th…
A comparison of mixed precision iterative refinement approaches for least-squares problems
Erin Carson, Ieva Daužickaitė
Various approaches to iterative refinement (IR) for least-squares problems have been proposed in the literature and it may not be clear which approach is suitable for a given probl…
The stability of split-preconditioned FGMRES in four precisions
Erin Carson, Ieva Daužickaitė
We consider the split-preconditioned FGMRES method in a mixed precision framework, in which four potentially different precisions can be used for computations with the coefficient…
Single-pass Nyström approximation in mixed precision
Erin Carson, Ieva Daužickaitė
Low rank matrix approximations appear in a number of scientific computing applications. We consider the Nyström method for approximating a positive semidefinite matrix . In the…
On time-parallel preconditioning for the state formulation of incremental weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
Using a high degree of parallelism is essential to perform data assimilation efficiently. The state formulation of the incremental weak constraint four-dimensional variational data…
Randomised preconditioning for the forcing formulation of weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
There is growing awareness that errors in the model equations cannot be ignored in data assimilation methods such as four-dimensional variational assimilation (4D-Var). If allowed…
Spectral estimates for saddle point matrices arising in weak constraint four-dimensional variational data assimilation
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
We consider the large-sparse symmetric linear systems of equations that arise in the solution of weak constraint four-dimensional variational data assimilation, a method of high in…