FlashAttention 4 is a memory-optimized attention kernel designed specifically for NVIDIA Blackwell GPUs that reduces memory bandwidth bottlenecks in transformer models. It uses a warp-specialized 5-stage pipeline, computes exponentials on CUDA cores instead of SFUs, and implements adaptive rescaling to minimize overhead.
Table of contents
IntroductionKey TakeawaysWhy attention kernels still dominate LLM costFlashAttention Evolution at a GlanceWhat’s New in FlashAttention 4Compatibility and current statusHow to Adopt FlashAttention – Decision GuideFAQsConclusionReferencesSort: