Energy-Aware Physical Synthesis of Deep Neural Networks for Edge-AI Applications in Robotics and VLSI Systems
Energy-aware physical synthesis is essential for deploying deep neural networks (DNNs) in edge-AI applications for robotics and VLSI systems, where stringent power, area, and latency constraints prevail. Beyond algorithm-and software-level optimizations such as network compression and compiler techn...
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| Other Authors: | , , , , , |
| Format: | article |
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2025
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| Online Access: | http://hdl.handle.net/11675/14472 https: |
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