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The research group Mechanics of Materials and Structures at Ghent University (UGent-MMS) has 4 vacancies for PhD and postdoc research in the field of fibre-reinforced composites. The vacancies
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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artificielle (IA) (CPU, GPU, accélérateurs d'IA, etc.) nécessitent une puissance élevée et des réseaux de distribution d'énergie (PDN) optimisés pour améliorer l'efficacité en puissance et préserver son
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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of GPUs and/or time in either training or inference procedures, which pose considerable challenges to both academia and industry for widespread access and deployment. In particular, the sampling process of
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derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in
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& facility Assistant professor Associate professor Education EngD Finance HRM IT Lecturer Legal staff Management Marketing and communications PhD Policy and staff PostDoc Professor Research, development
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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nature of electroweak symmetry breaking and mass generation in the standard model. We developed state of the art (open source) software working on GPU- and CPU-based supercomputing architectures, and