The GPU4U project initiated by AICS and ITEC (PI: J. Wachter & Mathias Lux) is being launched as a pilot within the DHInfra.at infrastructure initiative. DHInfra.at is developing a national Machine Learning infrastructure primarily for Digital Humanities, with CLARIAH partners and DH research projects receiving priority access. GPU4U serves as an exploratory pilot to understand how computational resources might be utilized by a broader student community, while the infrastructure’s core mission remains focused on Digital Humanities research.

Addressing the GPU Access Gap for Students

As part of this pilot exploration, GPU4U is granted access to computational resources for select student projects. The following three use cases will be evaluated as the infrastructure is being set up:

Use Case 1: Supporting Resource-Intensive Student Projects: One workshop per semester where students from various faculties can present project ideas and apply for limited resource allocation. Approximately five selected projects per semester may receive temporary access to the DHInfra cluster (featuring 12x H200 GPUs and multiple L40s) for tasks such as LLM fine-tuning, VR simulations, or other computational workloads.

Use Case 2: Limited LLM Inference Access for Educational Purposes: One GPU may be allocated to provide controlled access to LLM inference (via Ollama and various models) through an API for specific educational use cases. This would enable experimentation with prompting strategies, context size, temperature, and other parameters within structured learning environments. The inference could be integrated into select courses, such as a pilot “Introduction to Databases” course, to explore how such tools might support learning in non-technical disciplines.

Use Case 3: Experimental VR-Based Teaching Support: This use case explores the potential for VR in teaching through streaming solutions, particularly in Game Studies and Engineering contexts, which could reduce dependency on individual high-performance workstations. Implementation would depend on local infrastructure availability, such as VR headset access, and remains subject to further evaluation.

 

PI: Jasmin Wachter (AICS) & Mathias Lux (ITEC)

Further Reading: https://www.dhinfra.at/

https://www.dhinfra.at/2025-09-09-gpu4u-pilot-use-case/