FlashAttention

A fast and memory-efficient implementation of the accurate attention mechanism

CommonProductProgrammingDeep LearningTransformer

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.

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