Recent progress in analog memory-based accelerators for deep learning von Tsai, Hsinyu, Ambrogio, Stefano, Narayanan, Pritish, Shelby, Robert M, Burr, Geoffrey W

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Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators von Rasch, Malte J., Mackin, Charles, Le Gallo, Manuel, Chen, An, Fasoli, Andrea, Odermatt, Frédéric, Li, Ning, Nandakumar, S. R., Narayanan, Pritish, Tsai, Hsinyu, Burr, Geoffrey W., Sebastian, Abu, Narayanan, Vijay

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Perspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance von Cristiano, Giorgio, Giordano, Massimo, Ambrogio, Stefano, Romero, Louis P., Cheng, Christina, Narayanan, Pritish, Tsai, Hsinyu, Shelby, Robert M., Burr, Geoffrey W.

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Two-Dimensional Pattern Formation Using Graphoepitaxy of PS‑b‑PMMA Block Copolymers for Advanced FinFET Device and Circuit Fabrication von Tsai, Hsinyu, Pitera, Jed W, Miyazoe, Hiroyuki, Bangsaruntip, Sarunya, Engelmann, Sebastian U, Liu, Chi-Chun, Cheng, Joy Y, Bucchignano, James J, Klaus, David P, Joseph, Eric A, Sanders, Daniel P, Colburn, Matthew E, Guillorn, Michael A

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Optimised weight programming for analogue memory-based deep neural networks von Mackin, Charles, Rasch, Malte J., Chen, An, Timcheck, Jonathan, Bruce, Robert L., Li, Ning, Narayanan, Pritish, Ambrogio, Stefano, Le Gallo, Manuel, Nandakumar, S. R., Fasoli, Andrea, Luquin, Jose, Friz, Alexander, Sebastian, Abu, Tsai, Hsinyu, Burr, Geoffrey W.

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Impact of analog memory device failure on in-memory computing inference accuracy von Li, Ning, Tsai, Hsinyu, Narayanan, Vijay, Rasch, Malte

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Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices von Spoon, Katie, Tsai, Hsinyu, Chen, An, Rasch, Malte J., Ambrogio, Stefano, Mackin, Charles, Fasoli, Andrea, Friz, Alexander M., Narayanan, Pritish, Stanisavljevic, Milos, Burr, Geoffrey W.

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Using the IBM analog in-memory hardware acceleration kit for neural network training and inference von Le Gallo, Manuel, Lammie, Corey, Büchel, Julian, Carta, Fabio, Fagbohungbe, Omobayode, Mackin, Charles, Tsai, Hsinyu, Narayanan, Vijay, Sebastian, Abu, El Maghraoui, Kaoutar, Rasch, Malte J.

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Equivalent-accuracy accelerated neural-network training using analogue memory von Ambrogio, Stefano, Narayanan, Pritish, Tsai, Hsinyu, Shelby, Robert M., Boybat, Irem, di Nolfo, Carmelo, Sidler, Severin, Giordano, Massimo, Bodini, Martina, Farinha, Nathan C. P., Killeen, Benjamin, Cheng, Christina, Jaoudi, Yassine, Burr, Geoffrey W.

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Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training von Kariyappa, Sanjay, Tsai, Hsinyu, Spoon, Katie, Ambrogio, Stefano, Narayanan, Pritish, Mackin, Charles, Chen, An, Qureshi, Moinuddin, Burr, Geoffrey W.

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A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh von Jain, Shubham, Tsai, Hsinyu, Chen, Ching-Tzu, Muralidhar, Ramachandran, Boybat, Irem, Frank, Martin M., Wozniak, Stanislaw, Stanisavljevic, Milos, Adusumilli, Praneet, Narayanan, Pritish, Hosokawa, Kohji, Ishii, Masatoshi, Kumar, Arvind, Narayanan, Vijay, Burr, Geoffrey W.

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Directed self-assembly of block copolymers for 7 nanometre FinFET technology and beyond von Liu, Chi-Chun, Franke, Elliott, Mignot, Yann, Xie, Ruilong, Yeung, Chun Wing, Zhang, Jingyun, Chi, Cheng, Zhang, Chen, Farrell, Richard, Lai, Kafai, Tsai, Hsinyu, Felix, Nelson, Corliss, Daniel

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Weight Programming in DNN Analog Hardware Accelerators in the Presence of NVM Variability von Mackin, Charles, Tsai, Hsinyu, Ambrogio, Stefano, Narayanan, Pritish, Chen, An, Burr, Geoffrey W.

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Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration von Giordano, Massimo, Cristiano, Giorgio, Ishibashi, Koji, Ambrogio, Stefano, Tsai, Hsinyu, Burr, Geoffrey W., Narayanan, Pritish

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Nitride etching with hydrofluorocarbons. II. Evaluation of C4H9F for tight pitch Si3N4 patterning applications von Marchack, Nathan, Miyazoe, Hiroyuki, Bruce, Robert L., Tsai, Hsinyu, Nakamura, Masahiro, Suzuki, Takefumi, Ito, Azumi, Matsumoto, Hirokazu, Engelmann, Sebastian U., Joseph, Eric A.

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Training fully connected networks with resistive memories: impact of device failures von Romero, Louis P, Ambrogio, Stefano, Giordano, Massimo, Cristiano, Giorgio, Bodini, Martina, Narayanan, Pritish, Tsai, Hsinyu, Shelby, Robert M, Burr, Geoffrey W

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P-09. 低出力近赤外線レーザー照射が象牙芽細胞分化に及ぼす影響 von TSAI CHIHSUN, TSAI HSINYU, RAO YAXIN, 斎藤隆史

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Drift regularization to counteract variation in drift coefficients for analog accelerators von TSAI, HsinYu, KARIYAPPA, Sanjay

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Drift regularization to counteract variation in drift coefficients for analog accelerators von Sanjay Kariyappa, HsinYu Tsai

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Drift regularization to counteract variation in drift coefficients for analog accelerators von Kariyappa, Sanjay, Tsai, Hsinyu

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