Motivation

The Computational Science Initiative at Brookhaven National Laboratory (BNL) will host its fourth GPU Hackathon, dubbed "Brookathon 2020", on August 10–19, 2020. Brookathon 2020 is jointly organized by BNL, NVIDIA Corporation, and Oak Ridge National Laboratory (ORNL). This year's virtual event will consist of two parts: a one-day bootcamp on August 10 with tutorials, followed by 3-day intensive hands-on event on August 17-19. The Hackathon will provide the participants the opportunity to work on their application codes under the hands-on guidance of GPU experts. We especially encourage teams from the High Energy Physics community to participate.

Background

Currently there are several large-scale computing systems in the US that are based on General-Purpose Graphic Processing Units, or GPGPUs, including Summit at ORNL, Sierra at Lawrence Livermore National Lab and the upcoming Perlmutter machine at NERSC. In addition, the first announced exascale computers, Aurora at Argonne National Laboratory (ANL), and Frontier at ORNL, will have GPU-based architectures as well. These GPU-based supercomputers offer tremendous computing power for science and engineering, but writing efficient software to take full advantage of them may be challenging.

Goal

The goal of this 4-day intensive hands-on 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 a potentially scalable application that could benefit from GPU accelerators, or an application running on accelerators that needs optimization. There will be intensive mentoring during the hackathon, 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.

Prerequisites and Team Application Submission

Prior programming experience with GPUs is NOT a requirement, but collectively the team should be familiar with the applications to port or optimize for the GPUs.

Participation in the training event is free of charge. We will use virtual conferencing tools for the event (details will be announced to the accepted teams later). The deadline to submit an application is June 28, 2020. Notification of acceptance will be sent out by July 17, 2020.