Joe Eaton

Joe Eaton holds a Ph.D. in Computational and Applied Mathematics from the University of Texas at Austin's TICAM program. His fascination with CFD and fluid mechanics led to two Mechanical Engineering degrees (Rice University and Stanford University) before he decided it was really all about the math. Joe's Ph.D. work was on AMG applied to reservoir simulation problems, mixed with high performance chemistry simulation and parallel computing. He joined NVIDIA in 2013 to lead the AmgX product team.

Posts by Joe Eaton

Accelerated Computing

Parallel Direct Solvers with cuSOLVER: Batched QR

[Note: Lung Sheng Chien from NVIDIA also contributed to this post.] A key bottleneck for most science and engineering simulations is the solution of sparse… 15 MIN READ

AmgX V1.0: Enabling Reservoir Simulation with Classical AMG

Back in January I wrote a post about the public beta availability of AmgX, a linear solver library for large-scale industrial applications. Since then… 7 MIN READ
Accelerated Computing

AmgX: Multi-Grid Accelerated Linear Solvers for Industrial Applications

Many industries use Computational Fluid Dynamics (CFD) to predict fluid flow forces on products during the design phase, using only numerical methods. 7 MIN READ