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Dot-product engine as computing memory to accelerate machine learning algorithms., , , and . ISQED, page 374-379. IEEE, (2016)Accelerating Discrete Fourier Transforms with dot-product engine., and . ICRC, page 1-5. IEEE Computer Society, (2016)Regular Expression Matching with Memristor TCAMs., , , , , , , , , and 2 other author(s). ICRC, page 1-11. IEEE, (2018)Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning., , , , , , , , , and 10 other author(s). ICRC, page 1-13. IEEE, (2018)Physics-based memristor models., , and . ISCAS, page 217-220. IEEE, (2013)Large Memristor Crossbars for Analog Computing., , , , , , , , , and 9 other author(s). ISCAS, page 1-4. IEEE, (2018)Looking Ahead for Resistive Memory Technology: A broad perspective on ReRAM technology for future storage and computing., , , , and . IEEE Consumer Electronics Magazine, 6 (1): 94-103 (2017)PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM., , , , , , , , , and . CoRR, (2019)Regular Expression Matching with Memristor TCAMs for Network Security., , , , , , , , , and 2 other author(s). NANOARCH, page 65-71. ACM, (2018)Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication., , , , , , , , , and . DAC, page 19:1-19:6. ACM, (2016)