LLM Inference on H800: A Disaggregated Architecture Guide
Explore LLM inference optimization on H800 SuperPods. Learn how a disaggregated architecture with SGLang tackles the prefill bottleneck to boost throughput.
yiakwy
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Explore LLM inference optimization on H800 SuperPods. Learn how a disaggregated architecture with SGLang tackles the prefill bottleneck to boost throughput.
yiakwy
Learn how to deploy Kimi K2, a state-of-the-art Mixture-of-Experts (MoE) model, on a massive 128 H200 GPU cluster. This guide covers the key challenges and solutions using OME and SGLang for scalable, high-performance inference, achieving 4800 tokens/second with low latency.
Alex
With its impressive performance and elegant architecture, **SGLang** is rapidly establishing itself in the competitive world of **large language model (LLM) inference**. Could it be the next PyTorch,...
Alex