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HELP: Hardware-Adaptive Efficient Latency Prediction for NAS via Meta-Learning
[article]
2021
arXiv
pre-print
For deployment, neural architecture search should be hardware-aware, in order to satisfy the device-specific constraints (e.g., memory usage, latency and energy consumption) and enhance the model efficiency. Existing methods on hardware-aware NAS collect a large number of samples (e.g., accuracy and latency) from a target device, either builds a lookup table or a latency estimator. However, such approach is impractical in real-world scenarios as there exist numerous devices with different
arXiv:2106.08630v3
fatcat:oxpeke4twbdvro3tlbrku4nuai