3 citations · 3 across the 3 of their papers we have counts for
4 papers
Unstructured to structured: geometric multigrid on complex geometries via domain remapping
Nicolas Nytko, Scott MacLachlan, J. David Moulton +3
For domains that are easily represented by structured meshes, robust geometric multigrid solvers can quickly provide the numerical solution to many discretized elliptic PDEs. Howev…
Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation
Nicolas Nytko, Andrew Reisner, J. David Moulton +2
Legacy codes are in ubiquitous use in scientific simulations; they are well-tested and there is significant time investment in their use. However, one challenge is the adoption of…
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman +3
Domain decomposition methods (DDMs) are popular solvers for discretized systems of partial differential equations (PDEs), with one-level and multilevel variants. These solvers rely…
Generalizing Lloyd's algorithm for graph clustering
Tareq Zaman, Nicolas Nytko, Ali Taghibakhshi +3
Clustering is a commonplace problem in many areas of data science, with applications in biology and bioinformatics, understanding chemical structure, image segmentation, building r…