Joe Eaton

Joe Eaton is a distinguished engineer for graph and data analytics, and PIC for GNN work at NVIDIA, overseeing devtech, libraries, and containers teams working on producing GNN products and libraries. He also supports and contributes to RAPIDS cuGraph and cuOpt efforts. Joe has a PhD in computational and applied math from UT Austin, a M.E. in mechanical engineering from Stanford and a BSME from Rice University
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Posts by Joe Eaton

Image is the DGL and PyG logos with the words Accelerated by NVIDIA.
Data Science Dec 08, 2023

Available Now: NVIDIA AI Accelerated DGL and PyG Containers for GNNs

From credit card transactions, social networks, and recommendation systems to transportation networks and protein-protein interactions in biology, graphs are... 9 MIN READ
Robotics Dec 08, 2022

Boosting Dynamic Programming Performance Using NVIDIA Hopper GPU DPX Instructions

Dynamic programming (DP) is a well-known algorithmic technique and a mathematical optimization that has been used for several decades to solve groundbreaking... 9 MIN READ
CUDA 7
Simulation / Modeling / Design Apr 28, 2015

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
Simulation / Modeling / Design May 15, 2014

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, AmgX... 7 MIN READ
Simulation / Modeling / Design Jan 08, 2014

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. A famous... 7 MIN READ