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Embracing Diversity: Enhanced DSP Blocks for Low-Precision Deep Learning on FPGAs.

, , and . FPL, page 35-42. IEEE Computer Society, (2018)

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Real-time pedestrian detection on a xilinx zynq using the HOG algorithm., , and . ReConFig, page 1-8. IEEE, (2015)You Cannot Improve What You Do not Measure: FPGA vs. ASIC Efficiency Gaps for Convolutional Neural Network Inference., , and . ACM Trans. Reconfigurable Technol. Syst., 11 (3): 20:1-20:23 (2018)FPGA Logic Block Architectures for Efficient Deep Learning Inference., , , and . ACM Trans. Reconfigurable Technol. Syst., 13 (3): 12:1-12:34 (2020)Evaluating and Enhancing Intel® Stratix® 10 FPGAs for Persistent Real-Time AI., , , , , , , , , and 6 other author(s). FPGA, page 119. ACM, (2019)Embracing Diversity: Enhanced DSP Blocks for Low-Precision Deep Learning on FPGAs., , and . FPL, page 35-42. IEEE Computer Society, (2018)Math Doesn't Have to be Hard: Logic Block Architectures to Enhance Low-Precision Multiply-Accumulate on FPGAs., , , and . FPGA, page 94-103. ACM, (2019)Recurrent Neural Networks With Column-Wise Matrix-Vector Multiplication on FPGAs., , , , , , , , , and . IEEE Trans. Very Large Scale Integr. Syst., 30 (2): 227-237 (2022)Why Compete When You Can Work Together: FPGA-ASIC Integration for Persistent RNNs., , , , , , , , , and 6 other author(s). FCCM, page 199-207. IEEE, (2019)