Lowering dynamic power of a stream-based CNN hardware accelerator
Custom hardware accelerators of Convolutional Neural Networks (CNN) provide a promising solution to meet real-time constraints for a wide range of applications on low-cost embedded devices. In this work, we aim to lower the dynamic power of a stream-based CNN hardware accelerator by reducing the com...
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Main Authors: | Piyasena, Duvindu, Wickramasinghe, Rukshan, Paul, Debdeep, Lam, Siew-Kei, Wu, Meiqing |
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Other Authors: | School of Computer Science and Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/147509 |
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Institution: | Nanyang Technological University |
Language: | English |
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