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Computer (HPC) with its sizable cluster of CPUs, GPUs, storage arrays and high speed networking as well as our cloud (AWS) based Data Safe Haven, used for researchers working on sensitive data. As Research
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that serve the entire campus community. You will bridge the gap between high-performance hardware and practical user applications, ensuring that our AI infrastructure, from GPU infrastructure to sovereign data
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-performance computing systems, GPU acceleration, and parallel file systems - Ability to communicate fluently in English, both spoken and written Additional qualifications - Knowledge of or interest in
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(URCF) at Drexel University is building a new shared computing platform focused on GPU-accelerated workloads, particularly AI model training. The system includes GPU and CPU compute nodes with Nvidia H200
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, procurement, and deployment of High-Performance Computing (HPC/GPU) clusters and high-capacity data storage infrastructures in strict compliance with Spanish and EU public procurement regulations. Data
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heterogeneous (CPU/GPU) computing models. Collaborate with physicists, computer scientists, mathematicians and engineers across LBNL divisions to define software requirements, implement robust solutions, and
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Job Code 0005 Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The successful applicant will assist in the adaptation of the PPMstar code to run well on GPU-accelerated
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experiments, particularly ATLAS and DUNE. Contribute to the architecture and core development of the Phlex framework, emphasizing scalable, multi-threaded, and heterogeneous (CPU/GPU) computing models
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analysis systems using GPU- and FPGA-supported HPC clusters at large international research facilities such as Effelsberg, SKA, and MeerKAT. The systems developed by the BDG are based on state-of-the-art
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | Italy | about 1 month ago
Description Analysis and development of methodologies to accelerate the computation of numerical optimization through parallelization and the use of GPUs. Where to apply Website http://www.unibo.it Requirements