SDSC supports the training of its user community, including students, in all aspects of High-performance computing (HPC). The goal of the training is to prepare new HPC users to run jobs on HPC systems. Students who successfully complete the HPC Training program will receive an SDSC Certificate of Completion in HPC Training and UCSD Co-Curricular Record Credit (for students).
This event will be held remotely.
This webinar gives a brief overview of two profiling tools that will help you make optimal use of Expanse. We will cover NVIDIA’s NSIGHT for identifying GPU performance bottlenecks and AMD’s µProf for understanding the performance of the AMD EPYC CPUs.
This event will be held remotely.
Registration coming soon... This event will help users to make the most effective use of Expanse’s AMD EPYC processors. Topics include an introduction to the EPYC architecture, AMD compilers and math libraries, strategies for mapping processes and tasks to compute cores, Slurm, application tuning and profiling tools.
This event will be held remotely.
** Application Deadline is March 4, 2021** This event begins with a preparation day on May 4 followed by the GPU Hackathon running May 11 - 13. GPU Hackathons provide exciting opportunities for scientists to accelerate their AI research or HPC codes under the guidance of expert mentors from National Labs, Universities and Industry leaders in a collaborative environment. The SDSC Hackathon is a multi-day event designed to help teams of three to six developers accelerate their own codes on GPUs using a programming model, or machine learning framework of their choice. Each team is assigned mentors for the duration of the event.
This event will be held remotely.
ACM PEARC21 will take place virtually from July 19-22, 2021 and will explore the current practice and experience in advanced research computing including workforce development, training, diversity, applications and software, and systems and software. This yearʻs theme is “Evolution Across All Dimensions”.
This event will be held remotely.