LLM Inference Repository
The open-source collection 100 Days of LLM Inference offers a hands-on pathway for engineers and researchers who want to master large-language-model inference. Structured as a series of daily notebooks, the repository walks readers from low-level CUDA kernel implementations all the way to production-grade serving stacks.
Topics span the full inference stack: starting with custom CUDA kernels, then exploring high-performance serving frameworks such as vLLM, SGLang, and TensorRT-LLM. Later sections dive into model compression techniques like quantization, advanced generation strategies such as speculative decoding, and finally multi-cloud autoscaling patterns for scalable deployments.
Every notebook is executable out-of-the-box and has been validated on a dual-GPU testbed, ensuring that the examples run reliably on real hardware. This practical verification makes the repo a solid reference for anyone looking to see how LLMs are truly deployed and tuned for performance.
References
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Phần kết luận
For developers seeking a comprehensive, tested guide to LLM inference optimization, the LLM Inference Repository 100 Days of LLM Inference is a highly recommended resource. Its step-by-step notebooks and coverage of both low-level and high-level techniques provide a clear view of real-world deployment workflows.
