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analyse du flot optique, en exploitant des métriques et des régularisations adaptatives pertinentes, et des algorithmes itératifs parallèles adaptés aux GPU. Les paramètres de la méthode seront choisis pour
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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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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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The recruited engineer will be co-supervised by MdS and Joliot to implement this new approach. To achieve a portable, efficient code that fully exploits GPUs, the core of the code will be developed
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heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations. This advancement will enable high-fidelity
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equipped with GPUs. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-159/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | about 2 months ago
they can be used in the h-matrice library as well as in any other software library; to know for each algo its range of effectiveness, in terms of input data (size), target machine (CPU, GPU), precision
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music synthesis system that is trained only on commercially usable data? Can we train a high-quality music synthesis system on a single GPU? 1.3. Considered methods, targeted results and impacts
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machine learning. We have in-house GPU servers for MD and machine learning, along with access to French national supercomputing resources. SAXS and SANS experiments will be conducted at ESRF. We are seeking
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particular focus will be the development and benchmarking of AI- or ML-based clustering algorithms, as well as their integration for heterogeneous architectures, such as GPUs and FPGAs. If interested to do so