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Field
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, and the fundamental physics of spintronic oscillators. Their work also explores the use of these oscillators in unconventional computing hardware, including neuromorphic systems, reservoir computing
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languages used: C++ 2014, CUDA, Lua Desirable: - interest in high-performance computing with graphics processors (GPUs) and simulation methods - fluent knowledge of modern C++ and a scripting language
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at the forefront of international research and enabling full exploitation of next-generation observations and Exascale computing. We are seeking a highly motivated Postdoctoral Research Associate to join this
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Computing (HPC) knowledge around cluster builds, software, parallel computing, workload management, and cluster management. Knowledge with CUDA Programming Workflows, GPU programming, and GPU support
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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-performance computing, including parallel or GPU programming (MPI, OpenMP, CUDA, Kokkos, etc.) Familiarity with modern software development practices, including debugging, profiling, and version control
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neural networks to harden object detection and semantic segmentation, as well as maintaining the real-time performance of the hardened AI computing on embedded GPUs (NVIDIA Jetson AGX Orin). RGB camera and
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utilization. GPU Resource Management: Manage GPU resources within the cluster, optimizing utilization for compute-intensive tasks while maintaining a balance between user requirements and system stability
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Strong foundation in CFD, Programming proficiency such as Python, AI/ML techniques, Experience with parallel computing on CPU/GPU cluster, use of CUDA, MPI is a plus. Experience Experience with open-source
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-performance computing facility managed by the University with a general-purpose cluster consisting of 16,616 CPU cores and approximately 100 GPUs, as well as a dedicated AI cluster with 40 A100/H100 GPUs