Beyond the Inference Time: A Deep Dive into Real-Time NPU Latency Visualization on Android

Short summary

A technical deep dive into decomposing NPU latency on Android beyond a single inference-time metric. It breaks latency into four stages—CPU preparation, memory transfer (the memory wall), NPU compute via systolic arrays, and result copy-back—then explains how Google's AICore centralizes model management and optimization. The article provides diagnostic guidance for distinguishing compute-bound from memory-bandwidth-bound latency spikes.

• •NPU latency is multi-stage: CPU prep, memory transfer, compute, and result copy-back—not a single number
• •Memory wall (DRAM-to-NPU SRAM data movement) is often the real bottleneck, not raw TFLOPS
• •Google AICore centralizes model ownership at the OS level, enabling dynamic optimization and secure execution

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