FlashAttention: avoid writing the giant scratchpad

Picture it

Think of standard attention as drawing a massive, sprawling grid on a chalkboard to compare every word in a book to every other word. You waste enormous time walking back and forth to fill in the squares. FlashAttention, instead, operates like a clever sliding window, evaluating small chunks on a fast, handheld notepad and updating a running tally. By never materializing the giant grid on the slow chalkboard, it shaves off massive amounts of wasted travel time.

What to understand

• IO-aware tiling, online softmax, and recomputation
• Exact dense attention versus sparse/approximate attention

Follow the references

1. 1 · Paper

   Dao et al. · FlashAttention ↗

   Follow the memory-hierarchy diagram and tiled algorithm. Focus on which arrays are never stored in HBM.

2. 2 · Tutorials

   Triton · GPU programming tutorials ↗

   Inspect the fused-attention tutorial after the paper’s dataflow is clear.

Make it concrete

Benchmark attention over increasing sequence lengths with a reference and supported fused backend. Compare peak memory, runtime, and numerical error.