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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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Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229415🟢 Letter 📜 Local structure and ionic transport in acceptor-doped layered perovskite BaLa2In2O7 👩‍🎓 Nataliia A. Tarasova (https://orcid.org/0000-0001-7800-0172) 🏛 Institute of High Temperature Electrochemistry UB RAS, http://www.ihte.uran.ru 📚#layered_perovskite#ionic#conductivity#acceptor_doping#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.15 https://journals.urfu.ru/index.php/chimtech/article/view/6272

Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229405🟢 📜 Phosphorus-doped protonic conductors based on BaLanInnO3n+1 (n = 1, 2): applying oxyanion doping strategy to the layered perovskite structure 👩‍🎓👨‍🎓 N. Tarasova (https://orcid.org/0000-0001-7800-0172), A. Galisheva (https://orcid.org/0000-0003-4346-5644) 🏛 Institute of High Temperature Electrochemistry, http://www.ihte.uran.ru 📚#layered#perovskite#oxyanion#doping#proton#conductivity#BaLaInO4#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.05 https://journals.urfu.ru/index.php/chimtech/article/view/5979