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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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data analysis, simulation, and machine learning, integrating resources across multiple facilities. NERSC's next major supercomputer, Doudna, will combine next generation GPUs, networking and storage
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communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest or experience in distributed training on large scientific datasets
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methodology Assist with code optimization and integration into Department of Energy (DOE's) applications running on the exascale computer systems with GPU accelerators We are looking for: PhD or equivalent