A framework converts traditional edge tasks to NN models via NAS and schedules them on idle AI chips to improve performance without affecting primary workloads.
Mcu-mixq: A hw/sw co-optimized mixed-precision neural network design framework for mcus.arXiv preprint arXiv:2407.18267, 2024
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Harvesting AI Computation at the Edge via Generic Approximation
A framework converts traditional edge tasks to NN models via NAS and schedules them on idle AI chips to improve performance without affecting primary workloads.