OSS + ELC EU 2026

Edge AI runs on dozens of NPUs — Ethos-U, Hexagon, APUs, DSPs — each with its own closed toolchain and proprietary profiling tools. Application developers have no standard way to answer the basic question: what is my NPU actually doing?

This talk walks through the edge AI software stack — frameworks, delegates, drivers, hardware counters — and shows what it takes to make performance visible. Building on Tomeu Vizoso's Ethos-U PMU kernel work (upstream), we are instrumenting ONNX Runtime and TFLite operators with per-operator CPU PMU data (cycles, cache miss, bandwidth), surfaced via open trace formats, and wiring NPU hardware counter values into ExecuTorch ETDump traces on Zephyr.

The goal: per-operator timing, CPU cache and bandwidth data, and NPU cycle counts in a single open trace — without a proprietary tool.

Contributing to the Linux perf subsystem, this work lays the groundwork for open profiling support on other NPU targets.