FlashAttention is a revolutionary algorithm that has transformed Transformer architectures by expediting the attention mechanism on GPUs, leading to significant advancements in Transformer training and inference. FlashAttention-3, the latest iteration, boasts up to 1.5-2x increased speed compared to its predecessor and allows for processing with lower precision numbers while maintaining accuracy, optimizing overall efficiency. Leveraging cutting-edge hardware features on Hopper GPUs, new techniques like asynchronous processing and incoherent processing have been introduced to further enhance performance. These innovations unlock the potential for longer context in large language models, paving the way for future advancements in AI technology.
https://www.together.ai/blog/flashattention-3