TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15077 · Aug 20
#c_lang#infiniband#iwarp#kernel_rdma_drivers#linux_kernel#rdma#roce#userspace_libraries You can use RDMA Core, a set of Linux userspace libraries and daemons, to work with RDMA devices for high-speed network communication. It supports many kernel drivers and provides tools and libraries like libibverbs and librdmacm to manage RDMA devices and connections. You can build it easily with cmake and install required packages depending on your Linux distribution. Using RDMA Core lets you set up software RDMA interfaces and verify them with commands like `ibv_devices` or `rdma link`. This helps you achieve faster, low-latency data transfer, which is useful for high-performance computing and networking tasks. https://github.com/linux-rdma/rdma-core
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@R4marketing · Post #806 · 08/13/2021, 08:00 AM
Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy
@testflightynoti · Post #37780 · 05/07/2026, 08:30 PM
#Futubull#Easy#Investment Join the Futubull-Easy Investment beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/LXJdcvBn Shared by Dimitri
@WangZhuanZhan · Post #34299 · 10/23/2024, 12:23 PM
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@wangzhuanzhan · Post #33280 · 09/23/2024, 06:10 AM
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@WangZhuanZhan · Post #34066 · 10/15/2024, 05:50 AM
T-t通t天t大d盗d- 通天大盗 通天大盜 (1987) 直达链接：https://pan.quark.cn/s/c40ba0abe557 #通天大盗#通天大盜 #妙婿向钱冲#Easy Money 链接：https://link3.cc/sf_com #电影#喜剧#香港#80年代
@wangzhuanzhan · Post #32222 · 09/03/2024, 08:49 AM
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@testflightynoti · Post #37748 · 05/07/2026, 08:21 AM
#Easy#Credit#T#i#ch#nh#s Join the Easy Credit - Tài chính số beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/B8XYxOWV Shared by Dimitri
@githubtrending · Post #15433 · 01/23/2026, 02:30 PM
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG