Stanford University Starts NVIDIA CUDA Classes, Named Center of Excellence

NVIDIA's CUDA technology is something that prospective programmers have to first learn about before they can exploit, so NVIDIA entered a tight relationship with Stanford University.

NVIDIA has made itself known for many things over the years, the most recent being high-end mobile graphics solutions and mobile platforms.

Meanwhile, its CUDA technology is something that it has been doing its best to promote amongst programmers and researchers.

In fact, the Santa Clara, California-based company resolved to have courses be taught at certain universities, meant to school students in its use and that of NVIDIA GPUs.

Apparently, the most recent successful step in this direction was Stanford University setting up classes of this sort, earning the title of CUDA Center of Excellence in the process.

What the institution will teach is multiple full courses, partner-sponsored courses and short courses into the CUDA architecture and parallel computing.

As part of the project, the Institute for Computational & Mathematical Engineering (ICME) at the Stanford School of Engineering will collaborate with the Departments of Computer Science (CS), Mechanical Engineering, Flow Physics Division and the Center for Computational Earth and Environmental Sciences (CEES).

"It's vitally important that our faculty be at the forefront of computing technology so that we can continue developing state-of-the-art computational algorithms that drive innovation in the sciences and engineering," said Margot Gerritsen, director, Institute for Computational & Mathematical Engineering, and associate professor, Department of Energy Resources Engineering, at Stanford University.

"This award allows us to broadly expand parallel computing education and research programs to large numbers of researchers and students from a wide variety of disciplines."

Those who attend the course should gain all the knowledge and skills needed for conducting research into seismic activity, probability estimation, uncertainty quantification and “development of mesh-based solvers for partial differential equations,” used in various simulations.