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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 6 days ago
-pipeline, constituted from the [killMS]( https://github.com/saopicc/killMS ) stage and the [DDFacet]( https://github.com/saopicc/DDFacet ) stage, both developed in particular by Cyril Tasse from the Paris
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, laboratory meetings, as well as at workshops and conferences covering the various aspects of the thesis: high-performance computing, numerical methods, and computational cosmology. An annual meeting of
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Inria, the French national research institute for the digital sciences | Villers-lès-Nancy, Lorraine | France | 6 days ago
has been significant progress in quantum computing, on both the theoretical and practical sides. The first experimental demonstrations of quantum error correction provide evidence that large-scale
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will Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers