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On-chip memory optimization for high-level synthesis of multi-dimensional data on FPGA., , and . ASP-DAC, page 243-248. ACM, (2019)Sign-magnitude SC: getting 10X accuracy for free in stochastic computing for deep neural networks., , , and . DAC, page 158:1-158:6. ACM, (2018)IR-QNN Framework: An IR Drop-Aware Offline Training of Quantized Crossbar Arrays., , , , , and . IEEE Access, (2020)Automated Log-Scale Quantization for Low-Cost Deep Neural Networks., , , and . CVPR, page 742-751. Computer Vision Foundation / IEEE, (2021)Fast and Low-Cost Mitigation of ReRAM Variability for Deep Learning Applications., , , , and . ICCD, page 269-276. IEEE, (2021)Accurate Prediction of ReRAM Crossbar Performance Under I-V Nonlinearity and IR Drop., , , , and . ICCD, page 9-16. IEEE, (2022)Learning to Predict IR Drop with Effective Training for ReRAM-based Neural Network Hardware., , , , , and . DAC, page 1-6. IEEE, (2020)Cost- and Dataset-free Stuck-at Fault Mitigation for ReRAM-based Deep Learning Accelerators., , , , , and . DATE, page 1733-1738. IEEE, (2021)Multi-Fidelity Nonideality Simulation and Evaluation Framework for Resistive Neuromorphic Computing., , , and . IEEECONF, page 1152-1156. IEEE, (2022)Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing., , , and . DAC, page 7. ACM, (2019)