Workload modeling in AI datacenters
Internship/thesis - Leuven | Just now
Dive into what happens inside these high-performance, (beyond) warehouse scale computers
The industry is investing massively in new datacenters for the AI era. While there is a lot of new buildings, power capacity and computer hardware being built, these investments serve to enable the calculations of many workloads. AI training is a large one, and so is AI inference, but this is across many models, and there is a lot of experimentation happening as well (Most of OpenAI’s 2024 compute went to experiments | Epoch AI).
This internship focuses on introducing, exploring and improving the scheduling of many different workloads inside a large AI datacenter, in the context of a broader performance modeling tool for AI datacenters.
We are looking forward to meeting interested candidates that, ideally, can demonstrate experience or insights in performance modeling and analysis in the context of computer systems and AI.
Master's degree: Master of Engineering Technology, Master of Science, Master of Engineering Science
Required educational background: Computer Science
Duration: 3-12 months
For more information or application, please contact the supervising scientists Timon Evenblij (timon.evenblij@imec.be) and Wenzhe Guo (wenzhe.guo@imec.be).
Imec allowance will be provided for students studying at a non-Belgian university.