How Did I Write My First FlashAttention Kernel in CUDA ?

FlashAttention, an I/O-aware exact attention algorithm, significantly speeds up deep learning models by redesigning attention computation around GPU memory hierarchy. It overcomes the memory bottleneck of standard attention, which involves writing large intermediate matrices to global memory, by keeping computations on-chip in faster SRAM. This is achieved through a tiled approach and an 'online softmax' trick that processes data in a single pass without materializing the full attention matrix.

Read the full article at Towards AI - Medium

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