FlashAttention is an open-source attention mechanism library designed specifically for Transformer models in deep learning to enhance computational efficiency and memory usage. It optimizes attention calculation using IO-aware methods, reducing memory consumption while maintaining precise computational results. FlashAttention-2 further improves parallelism and workload distribution, while FlashAttention-3 is optimized for Hopper GPUs, supporting FP16 and BF16 data types.