Subject
Computer Networks and Communications,Hardware and Architecture,Software
Reference47 articles.
1. A. Biondi, A. Balsini, M. Pagani, E. Rossi, M. Marinoni, G. Buttazzo, A framework for supporting real-time applications on dynamic reconfigurable FPGAs, in: Proc. of the IEEE Real-Time Systems Symposium, RTSS 2016, 2016, pp. 1–12.
2. A linux-based support for developing real-time applications on heterogeneous platforms with dynamic fpga reconfiguration;Pagani,2017
3. Spatio-temporal optimization of deep neural networks for reconfigurable FPGA SoCs;Seyoum;IEEE Trans. Comput.,2020
4. Y. Umuroglu, N.J. Fraser, G. Gambardella, M. Blott, P. Leong, M. Jahre, K. Vissers, Finn: A framework for fast, scalable binarized neural network inference, in: Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2017, pp. 65–74.
5. . Xilinx, PYNQ - Python productivity for Zynq, URL http://www.pynq.io/.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献