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Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning., , , , , , and . HPEC, page 1-7. IEEE, (2023)Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices., and . CoRR, (2016)Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices., , and . CoRR, (2017)Emerging Neural Workloads and Their Impact on Hardware., , , , , , , , , and 5 other author(s). DATE, page 1462-1471. IEEE, (2020)Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation., , , , , , , , , and 5 other author(s). CoRR, (2024)Neural Network Training With Asymmetric Crosspoint Elements., , , , , , , and . Frontiers Artif. Intell., (2022)A Flexible and Fast PyTorch Toolkit for Simulating Training and Inference on Analog Crossbar Arrays., , , , , , , , and . AICAS, page 1-4. IEEE, (2021)Reliability Challenges with Materials for Analog Computing., , , , , , , , , and 8 other author(s). IRPS, page 1-10. IEEE, (2019)Analog CMOS-based resistive processing unit for deep neural network training., , , and . MWSCAS, page 422-425. IEEE, (2017)Towards Exact Gradient-based Training on Analog In-memory Computing., , , and . CoRR, (2024)