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Breaking end-to-end latency into explicit stages gives teams a much better chance of improving real performance instead of optimizing the wrong layer. 1. Measurement strategy Use a fixed input set, record timestamps at every stage boundary, and repeat enough runs to separate warm-up behavior from steady-state performance. 2. Common surprises Preprocessing and data movement often dominate more than expected once the model itself is already well optimized on the accelerator.
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