Low Latency Inference Chapter 1: Up to 1.9x Higher Llama 3.1 Performance with Medusa on NVIDIA HGX H200 with NVLink Switch – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-05-23T19:27:29Z http://www.open-lab.net/blog/feed/ Ashraf Eassa <![CDATA[Low Latency Inference Chapter 1: Up to 1.9x Higher Llama 3.1 Performance with Medusa on NVIDIA HGX H200 with NVLink Switch]]> http://www.open-lab.net/blog/?p=88127 2024-11-29T21:06:37Z 2024-09-05T18:30:00Z As large language models (LLMs) continue to grow in size and complexity, multi-GPU compute is a must-have to deliver the low latency and high throughput that...]]> As large language models (LLMs) continue to grow in size and complexity, multi-GPU compute is a must-have to deliver the low latency and high throughput that...Image of an HGX H200

As large language models (LLMs) continue to grow in size and complexity, multi-GPU compute is a must-have to deliver the low latency and high throughput that real-time generative AI applications demand. Performance depends both on the ability for the combined GPUs to process requests as ��one mighty GPU�� with ultra-fast GPU-to-GPU communication and advanced software able to take full��

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