Lesson 1264 of 1596
Flash Attention: How AI Models Hit Long Context Without Running Out of Memory
Flash Attention rewrites attention to avoid materializing the full attention matrix, enabling long context on standard GPUs.
Creators · AI Foundations · ~17 min read
The premise
Flash Attention is the IO-aware attention algorithm that made long-context training and inference practical. It's a software win that unlocks hardware most people already had.
What AI does well here
- Cut attention memory from quadratic to linear in sequence length
- Speed up training and inference 2-4x on modern GPUs
- Enable longer context windows without architectural changes
What AI cannot do
- Help on hardware without the right tensor cores (early Volta etc.)
- Eliminate attention's quadratic compute, only its memory IO
- Substitute for sparse-attention or linear-attention research for ultra-long context
Key terms in this lesson
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