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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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models (e.g., CNNs, diffusion models, etc) Proficiency in Python Experience with HPC (CPU or GPU, with GPUs preferred) Related Skills and Other Requirements Ability to collaborate on the application of AI
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Mathematica and Python with an interest in GPU programming. These required and desired skills should be demonstrated by presenting an existing body of code and/or peer-reviewed publications. Additional
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with a previous background on GPU computing are especially encouraged to apply. However, other research profiles, within the realm of computation physics, especially with a background in strongly
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications and machine learning. Integrate and benchmark the GINGKO library, a sparse solver
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
further GPU porting. The exploration of C++ programming models for performance portability, such as Kokkos or StarPU, will form a second part. A comparative study will evaluate the different implementations
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for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations. This advancement will enable
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, Probabilistic Inference, Algebraic Topology and Wavelet analysis theory. Familiar with Matlab/Python/C++ programming. Experience with Pytorch and multi-GPU model deployment. Experience in analyzing complex