OVERCOMING COMPUTE AND MEMORY BOTTLENECKS WITH FLASHATTENTION-4 ON NVIDIA BLACKWELL

Summary from the TLDR AI newsletter

FlashAttention is an input/output aware algorithm that computes the same mathematical result as standard attention, but more efficiently. It uses reduced memory access and near-linear memory to achieve this. These optimizations lead to faster training and inference and enable models to handle longer sequences of tokens. FlashAttention-4, the latest iteration of optimized CUDA kernels, achieves a peak performance of 1,605 TFLOPS/s.