FINN（大结局）参考文献

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已于 2024-07-04 11:13:14 修改 · 1.2k 阅读

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#FINN #BNN #FPGA

于 2018-11-24 21:06:29 首次发布

该文主要探讨了FINN项目，它借鉴了一系列关于资源高效AI应用的三元神经网络（Ternary Neural Networks, TNNs）文献。这些文献涉及到了二值神经网络（BNNs）、FPGA加速器设计，以及针对能源效率和计算性能的优化。通过引用多个深度学习模型的压缩、量化和硬件实现的研究，强调了FINN在实现低功耗、高性能的神经网络计算方面的作用。" 129431855,10885597,使用servlet+jdbc实现数据库用户注册,"['servlet', '数据库', 'java']

该项目主要参考以下的文献

[1] H. Alemdar, N. Caldwell, V. Leroy, A. Prost-Boucle, and F. P´etrot. Ternary Neural Networks for Resource-Efficient AI Applications. CoRR, abs/1609.00222, 2016.

[2] R. Andri, L. Cavigelli, D. Rossi, and L. Benini.YodaNN: An ultra-low power convolutional neural network accelerator based on binary weights. CoRR, abs/1606.05487, 2016.

[3] K. Chellapilla, S. Puri, and P. Simard. High performance convolutional neural networks for document processing. In Proc. ICFHR. Suvisoft, 2006.

[4] Y.-H. Chen, J. Emer, and V. Sze. Eyeriss: A spatial architecture for energy-efficient dataflow for convolutional neural networks. In Proc. ACM/IEEE ISCA. IEEE, 2016.

[5] M. Courbariaux and Y. Bengio. Binarynet: Training deep neural networks with weights and activations constrained to +1 or -1. CoRR, abs/1602.02830, 2016.

[6] S. K. Esser, P. A. Merolla, J. V. Arthur, A. S. Cassidy,R. Appuswamy, A. Andreopoulos, D. J. Berg, J. L.McKinstry, T. Me