Algebraic multigrid (AMG) methods are particularly efficient to solve a wide range of sparse
linear systems, due to their good flexibility and adaptability. Even though modern parallel …

Conjugate gradient (CG) and biconjugate gradient stabilized (BiCGSTAB) are effective
methods used for solving sparse linear systems. We in this paper propose Mille-feuille, a …

Half-precision hardware support is now almost ubiquitous. In contrast to its active use in AI,
half-precision is less commonly employed in scientific and engineering computing. The …

Large-scale simulations require efficient computation across the entire computing hierarchy.
A challenge of the Exascale Computing Project (ECP) was to reconcile highly …

The explosive demand for artificial intelligence (AI) workloads has led to a significant
increase in silicon area dedicated to lower-precision computations on recent high …

We present a performance study of geometric multigrid (GMG) on NVIDIA, AMD, and Intel
GPU-accelerated supercomputers. The approach employs fine-grain data blocking in …