Santa Fe GPU Hackathon, October 29 – September 2
The Santa Fe GPU Hackathon is currently in planning stages. This hackathon will be held in Santa Fe, NM at the Drury Plaza Hotel and is currently being supported by AMD. We are looking for teams interested in developing and working on portable GPU accelerated applications.
We are always seeking GPU/HPC programming experts to serve as mentors at the hackathons.
Boulder GPU Hackathon, June 4-8
The Boulder GPU Hackathon was a success ! Developer teams from NASA, Los Alamos National Laboratory, Pacific Northwest National Laboratory, National Renewable Energy Laboratory, National Center for Atmospheric Research, NOAA National Severe Storms Laboratory, University of Chicago, University of Maryland, University of Colorado (Boulder), University of Washington, SilcsBio, and General Atomics teamed up with mentors from Nvidia, PGI, Google Cloud Platform, ARM, national laboratories, and universities and successfully accelerated a number of applications with GPUs !
Become a Mentor
We are always looking for experts in High Performance Computing and GPU programming to serve as mentors. Giving back to the community by training others at these events is a rewarding experience. Gain access to multi-GPU compute resources, grow your professional network, and establish your voice in the HPC and GPU programming worlds by signing up to be a hackathon mentor.
If you’d like to continue to hear more about GPU Hackathons and the impact they can have for you and your organization, sign up for our e-mail list.
Learn GPU Programming Quickly
A GPU Hackathon is an organized workshop that teams up programmers at all experience levels with experts to facilitate sharing of knowledge and skills in GPU programming. Teams of software developers can come to a hackathon with existing code they want to accelerate on GPUs. Expert mentors help teams develop a plan to port or optimize their code before the start of the workshop. During the one-week coding sprint, teams work with their mentors to transition code to the GPU and achieve software performance goals. This hands-on approach is increasing the number of new GPU programmers and promotes continued learning within the community that participates in hackathons.