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small cluster computers, high-end GPU nodes and specially configured workstations on which experiments are conducted. You will be working in a team of junior and senior system administrators. Naturally
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physics interpretations or seismic rupture studies. We have excellent HPC facilities including GPUs, ideally suited for machine learning applications. You will play an essential role in education by
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System Network Engineer to join our department, with a specific knack for networking. The infrastructure combines accelerated computing and GPUs clusters, open-source platforms-as-a-service, and fast
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calculated using our Software Energy Lab, which has multiple test machines with GPUs and, in the future, AI accelerators. Development teams currently lack guidance on how to create sustainable systems. You
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measuring the environmental impact. This impact can be measured and calculated using our Software Energy Lab, which has multiple test machines with GPUs and, in the future, AI accelerators. Development teams
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computational power (e.g. development of graphics processor unit (GPU)-based computing) have gone hand in hand with the development of innovative algorithms like deep learning. In addition, the increased
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machines, to shared GPU servers, the Delft AI Cluster that is shared across departments, as well as DelftBlue, which is one of the top 250 supercomputers in the world. Your supervisors will be Dr. Holger
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access to the compute resources of TU Delft, ranging from personal machines, to shared GPU servers, the Delft AI Cluster that is shared across departments, as well as DelftBlue, which is one of the top 250
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for future evolution and functional extension (related to e.g. machine-learning, batch and parallel processing, GPU processing); support large-scale data infrastructure challenges up to petabyte scale; support