Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Global
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
#3906 · +3 · 1d ·GitHub
Build your AI agents, chatbots, and RAG applications with HPC-AI Model APIs!
Beam is a fast, open-source runtime for serverless AI workloads. It gives you a Pythonic interface to deploy and scale AI applications with zero infrastructure overhead.
Apache Hadoop
Peer-to-peer LLM inference in the browser: pool your devices to run big open models, for chat and coding agents.
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A platform to build and run apps that are elastic, agile, and resilient. SDK, libraries, and hosted environments.
DeepEP (DeepEveryParallel) is a high-performance communication library for modern machine learning training and inference.
#6168 · +1 · 1d ·GitHub
TIP] > This is a source-grounded course for engineers who need to make architecture decisions under real constraints. Complete the engineering foundation first if you cannot yet trace, debug, disassemble, structure, and review production-shaped services.
Dask is a flexible parallel computing library for analytics. See documentation for more information.
Perform data science on data that remains in someone else's server