FlashAttention
An optimized algorithm that dramatically speeds up transformer models and reduces memory usage by reordering the standard attention computation on the GPU.
Think of It Like This
Like organizing a messy workshop so you can build a project without constantly walking back and forth to the tool shed to grab different supplies.
Standard attention mechanisms suffer from quadratic time and memory complexity, requiring excessive reads and writes to slow GPU high-bandwidth memory (HBM). FlashAttention uses a tiling strategy to compute attention blocks entirely within the fast SRAM. This hardware-aware approach has enabled modern models to process massively long context windows efficiently.