Flash Attention is an IO-aware implementation of exact attention that tiles the computation to minimize GPU memory reads and writes, making standard attention 2–4× faster without any approximation. It achieves this by keeping intermediate attention matrices in fast SRAM rather than writing them to slower HBM, and is now a default building block in most transformer training and inference stacks.