Tag: vLLM
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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Scheduling Strategies to Maximize LLM Utilization During Scaling
Smart scheduling can boost LLM throughput by 3.7x and cut costs by 87%. Learn how continuous batching, sequence prediction, and token budgeting unlock GPU efficiency at scale.
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