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FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks.

, , , , , , , and . ACM Trans. Reconfigurable Technol. Syst., 11 (3): 16:1-16:23 (2018)

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Reconfigurable future for HPC.. HPCS, page 130-131. IEEE, (2016)Achieving 10Gbps Line-rate Key-value Stores with FPGAs., , , , , and . HotCloud, USENIX Association, (2013)Customizing Low-Precision Deep Neural Networks for FPGAs., , , , , and . FPL, page 97-100. IEEE Computer Society, (2018)Starburst: Building next-generation internet devices., , , , , and . Bell Labs Technical Journal, 6 (2): 6-17 (2001)OSNT: open source network tester., , , , , , , , , and 2 other author(s). IEEE Network, 28 (5): 6-12 (2014)Inference of quantized neural networks on heterogeneous all-programmable devices., , , and . DATE, page 833-838. IEEE, (2018)FINN: A Framework for Fast, Scalable Binarized Neural Network Inference., , , , , , and . FPGA, page 65-74. ACM, (2017)Scaling Out to a Single-Node 80Gbps Memcached Server with 40Terabytes of Memory., , , and . HotStorage, USENIX Association, (2015)A Hash Table for Line-Rate Data Processing., , , and . TRETS, 8 (2): 13:1-13:15 (2015)FINN: A Framework for Fast, Scalable Binarized Neural Network Inference., , , , , , and . CoRR, (2016)