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-based HPC services, this role will involve supporting SAS researchers who use Penn’s new PARCC (Penn Advanced Research Computing Center) centralized HPC services, including both CPU and GPU cutting-edge
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plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov solvers
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recently added the new AI NVIDIA GPU SuperPod (https://news.ufl.edu/2020/07/nvidia-partnership/ ) in support of the AI initiative, which aims to expand the role of AI in higher education and research (https
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) and parallel computing, with a focus on cost-efficient and scalable model deployment. Skilled in working with medium-large scale multicore and heterogeneous (CPU + GPU) clusters. Excellent verbal and
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on heterogeneous processor types Optimized GPU computing and exploitation of GPU architectures for HPEC (tensors, multi-GPU instantiations, advances in GPU for AI/ML) Compute-focused optimization of System-on-Chip
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California State University, San Bernardino | San Bernardino, California | United States | 11 days ago
within the California State University (CSU) system. Designed to advance machine learning and AI research, TIDE features a high-performance computing architecture built on GPUs, powerful processors, and
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, including CPU, GPU, storage, file systems, networking, visualization, job schedulers, and scientific applications. Understanding of specific technologies relevant to HPC applications such as AI, training
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data systems, including tools for automatic scaling, deploying, and managing of systems, e.g. Kubernetes ● Experience with Cloud Providers like Google, Azure, AWS ● Experience with GPU and
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, including experience briefing sponsors and senior leadership Desirable Knowledge, Skills, and/or Abilities 1. Familiarity with high-performance computing (HPC) or GPU-based architectures 2. Active U.S
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, planner‑executor loops, or tool‑calling pipelines for complex decision‑making. Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research. Utilizing GPU/TPU