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New paradigm of FPGA-based computational intelligence from surveying the implementation of DNN accelerators.

Y. You, Y. Chang, W. Wu, B. Guo, H. Luo, X. Liu, B. Liu, K. Zhao, S. He, L. Li, and D. Guo. Des. Autom. Embed. Syst., 26 (1): 1-27 (2022)

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Compiler Assisted Instruction Relocation for Performance Improvement of Cache Hit Rate and System Reliability.B. Chen, L. Li, Y. Li, H. Luo, and D. Guo. SERE (Companion), page 243-246. IEEE, (2014)Learning Word Representations with Cross-Sentence Dependencyfor End-to-End Co-reference Resolution.H. Luo, and J. Glass. EMNLP, page 4829-4833. Association for Computational Linguistics, (2018)New paradigm of FPGA-based computational intelligence from surveying the implementation of DNN accelerators.Y. You, Y. Chang, W. Wu, B. Guo, H. Luo, X. Liu, B. Liu, K. Zhao, S. He, L. Li and 1 other author(s). Des. Autom. Embed. Syst., 26 (1): 1-27 (2022)Race-Condition-Aware and Hardware-Oriented Task Partitioning and Scheduling Using Entropy Maximization.S. Li, Y. Zhang, H. Luo, Y. Chen, C. Lu, and D. Guo. IEEE Trans. Parallel Distrib. Syst., 29 (7): 1589-1604 (2018)Online Learning of Interpretable Word Embeddings.H. Luo, Z. Liu, H. Luan, and M. Sun. EMNLP, page 1687-1692. The Association for Computational Linguistics, (2015)Improving Neural Language Models by Segmenting, Attending, and Predicting the Future.H. Luo, L. Jiang, Y. Belinkov, and J. Glass. ACL (1), page 1483-1493. Association for Computational Linguistics, (2019)Hybrid circuit-switched network for on-chip communication in large-scale chip-multiprocessors.H. Luo, S. Wei, D. Chen, and D. Guo. J. Parallel Distrib. Comput., 74 (9): 2818-2830 (2014)Bidirectional Backpropagation: Towards Biologically Plausible Error Signal Transmission in Neural Networks.H. Luo, J. Fu, and J. Glass. CoRR, (2017)DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks.J. Fu, H. Luo, J. Feng, K. Low, and T. Chua. IJCAI, page 1469-1475. IJCAI/AAAI Press, (2016)

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New paradigm of FPGA-based computational intelligence from surveying the implementation of DNN accelerators.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML New paradigm of FPGA-based computational intelligence from surveying the implementation of DNN accelerators.

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New paradigm of FPGA-based computational intelligence from surveying the implementation of DNN accelerators.