NVIDIA believes in extending our academic investment to include support for teaching, research, and advanced education. The GPU Education Center Program recognizes and supports academic institutions with a track record teaching GPU Computing at both undergrad and graduate leve.

Core Benefits

  • Donation of (1) Tesla and (2) GeForce GPUs (PC form factor).
  • Automatic inclusion into the GPU Educators Program for teaching materials.
  • Access to 100 self-paced GPU programming labs from nvidia.qwiklab.com.
  • Special pricing on Tesla GPUs via the Centers Reward Program.
  • GPU Technology Conference discounted passes.
  • Joint announcements and special event invites.
  • Priority consideration for onsite webinars, workshops and guest lectures.
  • Technical liaison as needed.
  • Optional: up to (10) copies of the Programming Massively Parallel Processors 2nd Edition. Must be requested in the proposal to be considered.

Expectations & Qualifications

  • At least (1) grad and (1) undergrad GPU Computing course taught in the last year and plans to continue teaching next year.
  • Graduate courses should include at least 50% GPU Computing.
  • Undergrad courses should include at least 25% GPU Computing.
  • Evidence of any outreach activities outside of courses.
  • Letter of commitment from the dean or department head (on official letterhead) stating the university's intention to continue to include GPU Computing as a substantial portion of recurring course(s).

*if you do not qualify on your own, feel free to either collaborate with professors at your university to qualify collectively or apply for the GPU Educators Program to get started.

Application Process

Please email a 1-3 page PDF or Word (.docx) proposal to GECproposal@nvidia.com. Proposals should include the following information:

  • Contact information that includes mailing address, phone number, and PI contact name. Proposals missing contact information will be automatically rejected.
  • Details of courses that will include GPU Computing and/or CUDA C/C++ (course name, number, URL, approximate number of lectures/assignments/projects/et. through which students are exposed to GPU computing, and/or CUDA C/C++, and any additional relevant information).
  • Description & specifications of PCs in proposed GPU education lab.
  • Matching funds proposal and budget outline for teaching assistant, graduate student or equivalent or any books requested (if applicable).
  • A letter from the Dean or Department Head stating in good faith that the course will include CUDA C/C++ and be a recurring part of the curriculum.

Proposals to become a GPU Education Center can be submitted at any time but will be reviewed and announced on a quarterly basis.   The next review will be mid-April, application deadline is April 8, 2016.

If you have any quesitons about the program or the status of your application, please email us at GECproposal@nvidia.com.

See our Current List of WorldWide GECs.