2017 GPU Hackathons
We are excited to announce 2017 GPU Hackathons!
General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. The challenge in utilizing such accelerators has been the difficulty in programming them. Any and all GPU programming paradigms are welcome.
The goal of each hackathon is for current or prospective user groups of large hybrid CPU-GPU systems to send teams of at least 3 developers along with either (1) a (potentially) scalable application that could benefit from GPU accelerators, or (2) an application running on accelerators that need optimization. There will be intensive mentoring during this 5-day hands-on workshop, with the goal that the teams leave with applications running on GPUs, or at least with a clear roadmap of how to get there. Our mentors come from national laboratories, universities and vendors, and besides having extensive experience in programming GPUs, many of them develop the GPU-capable compilers and help define standards such as OpenACC and OpenMP.
But we don’t even know how to program a GPU…
Programming experience with OpenACC is not a requirement. You will learn quickly in the intense 5-day schedule, working on your code 95% of the time with the mentors. In the weeks preceding the hackathon, you will have a chance to attend training to prepare you for the event. Prior GPU experience is not required!
Target audience and format
We are looking for teams of 3-6 developers with a scalable** application to port to or optimize on a GPU accelerator. Collectively the team should know the application intimately. If application is a suite of apps, no more than two per team is allowed and a minimum of 2 people per app must attend.
(** by scalable we really mean node-to-node communication implemented, but don’t be discouraged to apply if your application is less than scalable. We are also looking for breadth of application areas.)
Ok, so how can I attend?
Entry period will stay open for only 2 weeks, per event! See events below for deadlines. Selected teams will be notified approximately a week after deadline closes.
What applications are you targeting?
No application domain specifically. We hope to have open-source community codes in need of porting individual modules. This is a great opportunity for grad students and post-docs.
Will there be prizes?
Besides your code running über fast on a machine like Juron, Piz Daint, Titan and Summit? At the end of the event, you will divulge your amazing transformation into GPU Expert, in front of your admiring fans. We also are working to setup opportunities for your team to present your work at upcoming supercomputing related conferences such as SC, GTC, CUG, ISC. Oh and one more thing…there may be goodies too. Stay tuned! 😉
What will we use to program the GPUs?
For beginners, we recommend starting with OpenACC, but we are open to other GPU programming paradigms for those that have apps that already have some partial GPU port. We also host a number of events on programming hybrid architectures. Please visit the OLCF training events page for more info.
Participation in the training event is free of charge. The meeting room and lunches, as well as access to the supercomputers throughout the event are offered by participating sites. Mentors and learning materials introduced by the instructors are sponsored by participating sites the following partner organizations: Oak Ridge Leadership Computing Facility (OLCF), NASA Langley, Brookhaven National Lab, Jülich Supercomputing Centre, Technisch Universität Dresden (TU-Dresden), Swiss National Supercomputing Centre (CSCS), University of Delaware, Stony Brook University, Cray, NVIDIA, PGI, and IBM.
Who can I contact for more information or questions?
Please contact Fernanda Foertter firstname.lastname@example.org for questions.
Where are these Hackathons being held?
This year we are partnering with multiple centers to bring hackathons to more locations. Three have already been scheduled with more in the works. Please see tabs below for details.