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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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djangoproject

@djangoproject · Post #261 · 02/16/2017, 06:56 AM

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http://www.giantflyingsaucer.com/blog/?p=5557 In spring 2014 Python 3.4 shipped a provisional package (#asyncio) which according to the docs “provides infrastructure for writing single-threaded #concurrent code using #coroutines, #multiplexing I/O access over #sockets and other resources, running network clients and servers, and other related primitives“. I can’t possibly cover everything in this article but I can introduce some of the things you can do with it. As per my New’s Years resolution I’ll be building these #examples using Python 3.4.2 (Asyncio has been ported back to Python 3.3 now as well).

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