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projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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machine learning techniques, and GPU programming. The simulation results will be compared to observational data obtained using facilities worldwide including ESO and NOT. Who we are looking for A successful
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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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(Xilinx Vitis/Vivado, Intel Quartus, HLS tools) HPC environments or GPU-accelerated computing On-detector firmware or data acquisition systems Familiarity with HEP data formats and reconstruction
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has access to a high-performance computational cluster dedicated to artificial intelligence research and developments using traditional multi-CPU systems, but also GPUs. Where to apply E-mail drimakat
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frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will