->What is Flash Attention?

FlashAttention is an efficient algorithm designed to speed up the attention mechanism in large language models by reducing memory usage and increasing GPU throughput. Unlike standard attention, which loads entire matrices into memory, FlashAttention computes attention in small chunks directly in GPU SRAM, avoiding memory bottlenecks. This enables faster training and inference, especially for long sequences, and is now widely adopted in models like GPT and LLaMA for improved performance on modern hardware.

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