35 citations · 75 across the 17 of their papers we have counts for
22 papers
Monolithic Algebraic Multigrid Preconditioners for the Stokes Equations
Alexey Voronin, Scott MacLachlan, Luke N. Olson +1
We investigate a novel monolithic algebraic multigrid (AMG) preconditioner for the Taylor-Hood () and Scott-Vogelius ($\pmb{\mathbb{P}}_2/\mathbb{P…
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation
Nicolas Nytko, Ali Taghibakhshi, Tareq Uz Zaman +3
Sparse matrix representations are ubiquitous in computational science and machine learning, leading to significant reductions in compute time, in comparison to dense representation…
Characterizing the Performance of Node-Aware Strategies for Irregular Point-to-Point Communication on Heterogeneous Architectures
Shelby Lockhart, Amanda Bienz, William D. Gropp +1
Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computat…
Parallel Energy-Minimization Prolongation for Algebraic Multigrid
Carlo Janna, Andrea Franceschini, Jacob B. Schroder +1
Algebraic multigrid (AMG) is one of the most widely used solution techniques for linear systems of equations arising from discretized partial differential equations. The popularity…
On Computing Coercivity Constants in Linear Variational Problems Through Eigenvalue Analysis
Peter Sentz, Jehanzeb Hameed Chaudhry, Luke N. Olson
In this work, we investigate the convergence of numerical approximations to coercivity constants of variational problems. These constants are essential components of rigorous error…
Performance Analysis and Optimal Node-Aware Communication for Enlarged Conjugate Gradient Methods
Shelby Lockhart, Amanda Bienz, William Gropp +1
Krylov methods are a key way of solving large sparse linear systems of equations, but suffer from poor strong scalabilty on distributed memory machines. This is due to high synchro…