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Source channel @githubtrending · Post #14834 · Jun 17

#cuda DeepEP is a special communication library for Mixture-of-Experts (MoE) models. It helps these models work faster and more efficiently by improving how data is shared between different parts of the system. DeepEP supports low-precision operations and can handle data transfer between different types of connections, like NVLink and RDMA. This makes it very useful for both training and using AI models, especially when speed is important. Users benefit from faster processing times and better performance overall. https://github.com/deepseek-ai/DeepEP

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Опубликована новая статья 🟣 2024 🟣 V. 11 🟣 Issue 2 🟣 Art. 202411207 🟣 Letter 🟣 📜 Features of electronic states in the vicinity of band gap and atomic structure of Ta- and Nb-doped Li7La3Zr2O12 👩‍🎓👨‍🎓 M. I. Vlasov (http://orcid.org/0000-0002-7814-7489), E.A. Surzhikov (http://orcid.org/0009-0005-3466-6374), A.Yu. Germov (http://orcid.org/0000-0001-6091-1250), E.A. Il'ina (http://orcid.org/0000-0003-1759-5234), I.A. Weinstein (http://orcid.org/0000-0002-5573-7128) 🏛 Institute of High Temperature Electrochemistry of the Ural Branch of the Russian Academy of Sciences, https://ihte.ru/?page_id=3106 🏛 Ural Federal University, https://urfu.ru/en 🏛 M.N. Mikheev Institute of Metal Physics of the Ural Branch of the Russian Academy of Sciences, https://www.imp.uran.ru/?q=en 🏛 Institute of Metallurgy of the Ural Branch of the Russian Academy of Sciences, http://www.imet-uran.ru 📚#Li7La3Zr2O12#Ta#Nb#doping#bandgap#oxygen#vacancies 🔗https://doi.org/10.15826/chimtech.2024.11.2.07 https://journals.urfu.ru/index.php/chimtech/article/view/7692