CREST: Deployment-Realistic Hardware-in-the-Loop NAS for Embedded Sensing Systems
Deploying neural networks on low-power microcontrollers (MCUs) requires selecting model architectures under tight memory, latency, and energy constraints. Existing workflows often simplify this process along one or more axes: static proxy costs such as FLOPs or parameters, treating one MCU as representative, and continuous-inference tests instead of deployed sensing schedules. These assumptions can mis-rank Pareto-front candidates, miss infeasible deployments, and obscure schedule-dependent energy. We present CREST (Cross-platform Runtime Evaluation and Search Tool), a deployment-realistic hardware-in-the-loop (HIL) neural architecture search (NAS) framework for MCU sensing systems. CREST...
| Authors | Joseph Q. Zales, Pragya Sharma, Mani Srivastava |
|---|---|
| Primary category | eess.SY |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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