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GPU utilization and allocate computing resources efficiently across users. c) create and manage user accounts for faculty and students; troubleshoot user issues; and design and deliver
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to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering structure preserving Finite Element methods for multiphase flows
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. The researcher will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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of today’s heterogeneous hardware (multicore CPUs, GPUs, SmartNICs, disaggregated datacenters). We explore: SmartNICs & P4 switches for offloading intelligence from hosts Device-to-device communication
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. Training LLMs, large-scale deep learning systems, and/or large foundation models using GPU/TPU parallelization while setting up the environment/system network under various constraints, such as limited
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) Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team
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experiences using creative coding, AI-assisted tools, and GPU-accelerated workflows. You have a proven record of producing industry-recognised animation or interactive projects, and you thrive on guiding
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, immersive, and interactive technologies. Highly proficient in real-time engines, AI-assisted tools, GPU-accelerated platforms, and emerging computational design workflows, you combine creativity with
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that outperforms highly optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance