Moving intermediate values can be the bottleneck

Attention needs both arithmetic and movement of intermediate values. Optimizing those transfers can change speed and memory use. Benefits depend on the hardware, sequence lengths, implementation, and surrounding workload.

Kernel improvements are not whole-request speedups

An original deployment benchmark should record software versions and measure the full request. A kernel speedup does not necessarily equal the same improvement in end-to-end user latency.

THE TAKEAWAY

What to remember

Check numerical and workload compatibility.

Sources & further reading

  1. FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness ↗
How this story was made

Written by Kristian Kostov with AI assistance and checked against the linked sources. Company performance claims are attributed to the company. Analysis reflects AiLookout’s interpretation; we have not independently tested the products discussed. Cover photography is illustrative and does not depict the specific announcement or product.

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