Case Study — Measurement15 July 20265 min read

Where the Time Actually Went

A computer vision model on embedded hardware was slower than expected. A deep-dive pipeline audit surfaced the real bottlenecks, which were not where the team had been optimizing.

The Question

A computer vision model on embedded hardware was slower than the team expected. Why?

The Constraint

Embedded target, existing PyTorch/C++ inference pipeline.

What We Measured

A deep-dive audit of the inference pipeline, profiled stage by stage on the target hardware.

The Finding

The real bottlenecks, which were not where the team had been optimizing.

What It Changed

Optimization effort redirected to the stages that actually dominated runtime.

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