HPC Lab

In-house Computing Equipment

One of the specific project goals was to establish an in-house lab for HPC and AI that will complement and strengthen the existing research and development facilities at the university. While the reseacrhers are supported to apply for European HPC resources (EuroHPC), we wanted to provide a hands on experience working with actual computing node hardware here at the UDG.

Image source: Strategic Research Agenda for HPC in Europe (ETP4HPC-SRAS 2022)

We initially procurred and installed two computing nodes equipped with Linux system and hardware drivers for GPUs (nVidia T4). This was the next stage of the in-house lab equipment validation. The new rack cabinet and server equipment can be seen in photos bellow. SLURM platform was installed to manage the access and job management in the lab. During the course of the project, the researchers were provided the access to computing and other resources available through cross-project collaboration (EuroCC, AI4S3, AI-AGE)

In-house HPC Lab computing equipment

As anticipated, the HPC infrastructure was further upgraded through cross-project collaboration to support AI-driven research on biomarkers of aging in medical applications. This initiative will empower our team with cutting-edge resources, allowing us to enhance our capacity for data analysis and predictive modeling. To meet the demands of sophisticated AI computations, with the support of AI-AGE, we are upgrading our existing HPC setup with a powerful computing node. This addition includes a rack computing node equipped with a 48 CPU cores with 128GB RAM, NVIDIA L40 48GB GPUs, and 2x480GB internal SSDs. In addition, the project supported NAS storage of 24TB (multiple disks with RAID) dedicated for dataset management. This infrastructure enhancement is designed to integrate smoothly with our existing equipment, augmenting both our computational and storage capabilities while providing significant value for our investment. The upgrade was implemented in mid 2024.

In-house lab infrastructure upgraded throuh cross-project collaboration with AI-AGE project