HSCoNAS : hardware-software co-design of efficient DNNs via neural architecture search
In this paper, we present a novel multi-objective hardware-aware neural architecture search (NAS) framework, namely HSCoNAS, to automate the design of deep neural networks (DNNs) with high accuracy but low latency upon target hardware. To accomplish this goal, we first propose an effective hardware...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/155784 |