Performance analysis and modelling engineer Research next generation supercomputer hardware for AI/HPC applications.
What you will do
Research various solutions to enable the next large‑scale high‑performance computing clusters. The role spans over various layers from workload characterization, resource management, system architecture, and microarchitecture.
Develop performance (+power/TCO/emissions) models for future hardware at various levels of detail to identify bottlenecks and propose new solutions that alleviate the bottlenecks.
Capture the relevant workload characteristics of large‑scale applications, as inputs to hardware models.
Analyze performance on existing systems to validate and calibrate hardware models.
Collaborate across the company to guide the direction of HW/SW codesign based on the top HW issues and SW performance limiters generated from the models and characteristics.
Model features and configurations that improve performance, power, total cost of ownership and emissions.
What we do for you We offer you the opportunity to join one of the world’s premier research centers in nanotechnology at its headquarters in Leuven, Belgium. With your talent, passion and expertise, you’ll become part of a team that makes the impossible possible. Together, we shape the technology that will determine the society of tomorrow.
We are committed to being an inclusive employer and proud of our open, multicultural, and informal working environment with ample possibilities to take initiative and show responsibility. We commit to supporting and guiding you in this process; not only with words but also with tangible actions. Through imec.academy, our corporate university, we actively invest in your development to further your technical and personal growth.
We are aware that your valuable contribution makes imec a top player in its field. Your energy and commitment are therefore appreciated by means of a market appropriate salary with many fringe benefits.
Who you are
Master’s or PhD degree in Computer Science, Computer Engineering or a relevant STEM degree, preferably with early career experience.
Experience with performance modeling (such as computer architecture simulation) for multiple types of computer hardware (e.g. CPU/GPU/NPU, or network design).
Experience with performance measurement and analysis through profiling and tracing tools.
Good understanding of large‑scale application (AI/HPC) execution characteristics from the workload perspective.
Good understanding of heterogeneous system architectures, from their memory management to their microarchitecture.
Good understanding of machine learning techniques and their impact on performance.
Strong programming ability in C++ and Python. CUDA knowledge is considered a plus.
Your communication and interpersonal skills enable you to work in a dynamic, distributed team. You actively share experiences and knowledge with colleagues.
We are looking for excellent communication skills in English, as you will work in a multicultural team and closely with our partners.
Seniority level Associate
Employment type Full‑time
Job function Research and Engineering
Industries Research Services, Semiconductor Manufacturing, and Nanotechnology Research
#J-18808-Ljbffr