Tag: LLM inference
Speculative Decoding with Compressed Draft Models for LLMs
Accelerate LLM inference by up to 3x using speculative decoding. Learn how draft models, Medusa, and EAGLE reduce latency without compromising output quality.
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Tensor Parallelism 101: Multi-GPU Inference for Large Language Models
Learn how Tensor Parallelism enables large LLM inference by splitting model weights across GPUs. Discover why NVLink is critical, how to implement it with vLLM or TGI, and when to avoid it.
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Speculative Decoding Explained: Draft-and-Verify for Faster LLMs
Learn how speculative decoding speeds up LLMs using a draft-and-verify pipeline. Discover the math behind rejection sampling, Medusa architecture, and implementation tips for production.
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Confidential Computing for LLM Inference: TEEs and Encryption-in-Use Explained
Learn how confidential computing and TEEs protect LLM inference with encryption-in-use. Compare AWS, Azure, and NVIDIA solutions for secure AI deployment.
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