NVIDIA TensorRT-LLM Multiblock Attention Boosts Throughput by More Than 3x for Long Sequence Lengths on NVIDIA HGX H200

Originally published at: NVIDIA TensorRT-LLM Multiblock Attention Boosts Throughput by More Than 3x for Long Sequence Lengths on NVIDIA HGX H200 | NVIDIA Technical Blog

Generative AI models are advancing rapidly. Every generation of models comes with a larger number of parameters and longer context windows. The Llama 2 series of models introduced in July 2023 had a context length of 4K tokens, and the Llama 3.1 models, introduced only a year later, dramatically expanded that to 128K tokens. While…

Impressive to see how the TensorRT-LLM multiblock attention is significantly improving throughput for long sequence lengths. As AI and machine learning models evolve, performance enhancements like these are crucial, especially for high-demand applications. The NVIDIA HGX H200 looks like a game-changer in optimizing processing power and accelerating tasks that require high computational throughput. It’ll be exciting to see how these advancements impact real-world applications in NLP and other fields. Anyone here working on similar optimizations?