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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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@githubtrending · Post #15204 · 10/08/2025, 11:30 AM

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#java#cloud#coap#dashboard#iot#iot_analytics#iot_platform#iot_solutions#java#kafka#lwm2m#microservices#middleware#mqtt#netty#platform#snmp#thingsboard#visualization#websockets#widgets ThingsBoard is an open-source IoT platform that helps manage and analyze data from connected devices. It allows users to collect data, create real-time dashboards, and automate tasks using a powerful rule engine. This platform supports various protocols like MQTT and HTTP, making it easy to connect devices. Users can also define relationships between devices and assets, and trigger alarms based on specific conditions. The benefit is that it simplifies IoT project development, making it scalable and efficient for applications like smart farming, smart offices, and more. https://github.com/thingsboard/thingsboard

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#java #cloud #coap #dashboard #iot #iot_analytics #iot_platform #iot_solutions #kafka #lwm2m #microservices #middleware #mqtt #netty #platform #snmp #thingsboard #visualization #websockets #widgets