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2020 – today
- 2022
[c15]Atsuya Okazaki
, Pritish Narayanan, Stefano Ambrogio, Kohji Hosokawa, Hsinyu Tsai, Akiyo Nomura, Takeo Yasuda, Charles Mackin, Alexander M. Friz, Masatoshi Ishii, Yasuteru Kohda, Katie Spoon, An Chen, Andrea Fasoli, Malte J. Rasch, Geoffrey W. Burr:
Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers. ISCAS 2022: 3319-3323- 2021
- [j7]Katie Spoon, Hsinyu Tsai, An Chen, Malte J. Rasch, Stefano Ambrogio, Charles Mackin, Andrea Fasoli, Alexander M. Friz, Pritish Narayanan, Milos Stanisavljevic, Geoffrey W. Burr:
Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices. Frontiers Comput. Neurosci. 15: 675741 (2021) - [c14]Robert L. Bruce, Syed Ghazi Sarwat, Irem Boybat, Cheng-Wei Cheng, Wanki Kim, S. R. Nandakumar, Charles Mackin, Timothy Philip, Zuoguang Liu, Kevin Brew, Nanbo Gong, Injo Ok, Praneet Adusumilli, Katie Spoon, Stefano Ambrogio, Benedikt Kersting, Thomas Bohnstingl, Manuel Le Gallo, Andrew Simon, Ning Li, Iqbal Saraf, Jin-Ping Han, Lynne M. Gignac, John M. Papalia, Tenko Yamashita, Nicole Saulnier, Geoffrey W. Burr, Hsinyu Tsai, Abu Sebastian, Vijay Narayanan, Matthew BrightSky:
Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation. IRPS 2021: 1-6 - [c13]Kohji Hosokawa, Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, Charles Mackin, Andrea Fasoli, Alexander M. Friz, An Chen, Jose Luquin, Katherine Spoon, Geoffrey W. Burr, Scott C. Lewis:
Circuit Techniques for Efficient Acceleration of Deep Neural Network Inference with Analog-AI (Invited). ISCAS 2021: 1-5 - 2020
- [c12]Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, An Chen, Andrea Fasoli, Alexander M. Friz, Geoffrey W. Burr:
Accelerating Deep Neural Networks with Analog Memory Devices. AICAS 2020: 149-152 - [c11]Charles Mackin, Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, Katie Spoon, Andrea Fasoli, An Chen, Alexander M. Friz, Robert M. Shelby, Geoffrey W. Burr:
Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges. IRPS 2020: 1-10 - [c10]Andrea Fasoli, Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, Alexander M. Friz, An Chen, Geoffrey W. Burr:
Optimization of Analog Accelerators for Deep Neural Networks Inference. ISCAS 2020: 1-5
2010 – 2019
- 2019
- [j6]Massimo Giordano, Giorgio Cristiano, Koji Ishibashi, Stefano Ambrogio, Hsinyu Tsai, Geoffrey W. Burr, Pritish Narayanan:
Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 367-376 (2019) - [j5]Hung-Yang Chang, Pritish Narayanan, Scott C. Lewis, Nathan C. P. Farinha, Kohji Hosokawa, Charles Mackin, Hsinyu Tsai, Stefano Ambrogio, An Chen, Geoffrey W. Burr:
AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed. IBM J. Res. Dev. 63(6): 8:1-8:14 (2019) - [c9]Stefano Bianchi, I. Muñoz-Martín, Giacomo Pedretti, O. Melnic, Stefano Ambrogio, Daniele Ielmini:
Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses. VLSI Circuits 2019: 1-2 - 2018
- [j4]Giacomo Pedretti, Valerio Milo, Stefano Ambrogio, Roberto Carboni, Stefano Bianchi, Alessandro Calderoni, Nirmal Ramaswamy, Alessandro S. Spinelli, Daniele Ielmini:
Stochastic Learning in Neuromorphic Hardware via Spike Timing Dependent Plasticity With RRAM Synapses. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 77-85 (2018) - [j3]Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Robert M. Shelby, Irem Boybat, Carmelo di Nolfo, Severin Sidler, Massimo Giordano, Martina Bodini, Nathan C. P. Farinha, Benjamin Killeen, Christina Cheng, Yassine Jaoudi, Geoffrey W. Burr:
Equivalent-accuracy accelerated neural-network training using analogue memory. Nat. 558(7708): 60-67 (2018) - [j2]Valerio Milo, Giacomo Pedretti, Roberto Carboni, Alessandro Calderoni, Nirmal Ramaswamy, Stefano Ambrogio, Daniele Ielmini:
A 4-Transistors/1-Resistor Hybrid Synapse Based on Resistive Switching Memory (RRAM) Capable of Spike-Rate-Dependent Plasticity (SRDP). IEEE Trans. Very Large Scale Integr. Syst. 26(12): 2806-2815 (2018) - 2017
- [c8]Irem Boybat, Carmelo di Nolfo, Stefano Ambrogio, Martina Bodini, Nathan C. P. Farinha, Robert M. Shelby, Pritish Narayanan, Severin Sidler, Hsinyu Tsai, Yusuf Leblebici, Geoffrey W. Burr:
Improved Deep Neural Network Hardware-Accelerators Based on Non-Volatile-Memory: The Local Gains Technique. ICRC 2017: 1-8 - [c7]Geoffrey W. Burr, Pritish Narayanan, Robert M. Shelby, Stefano Ambrogio, Hsinyu Tsai, Scott L. Lewis, Kohji Hosokawa:
Neuromorphic devices and architectures for next-generation cognitive computing. ISCAS 2017: 1-4 - [c6]Pritish Narayanan, Lucas L. Sanches, Alessandro Fumarola, Robert M. Shelby, Stefano Ambrogio, Jun-Woo Jang, Hyunsang Hwang, Yusuf Leblebici, Geoffrey W. Burr:
Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays. ISCAS 2017: 1-4 - 2016
- [b1]Stefano Ambrogio:
Modeling of reliability and neuromorphic application of resistive switching devices. Polytechnic University of Milan, Italy, 2016 - [c5]Daniele Ielmini, Stefano Ambrogio, Valerio Milo, Simone Balatti, Zhongqiang Wang:
Neuromorphic computing with hybrid memristive/CMOS synapses for real-time learning. ISCAS 2016: 1386-1389 - 2015
- [j1]Simone Balatti, Stefano Ambrogio, Zhongqiang Wang, Daniele Ielmini:
True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(2): 214-221 (2015) - [c4]Simone Balatti, Stefano Ambrogio, Zhongqiang Wang, Scott Sills, Alessandro Calderoni, Nirmal Ramaswamy, Daniele Ielmini:
Understanding pulsed-cycling variability and endurance in HfOx RRAM. IRPS 2015: 5 - [c3]Stefano Ambrogio, Simone Balatti, Zhongqiang Wang, Yu-Sheng Chen, Heng-Yuan Lee, Frederick T. Chen, Daniele Ielmini:
Data retention statistics and modelling in HfO2 resistive switching memories. IRPS 2015: 7 - 2014
- [c2]Stefano Ambrogio, Simone Balatti, Daniele Ielmini, D. C. Gilmer:
Analytical modelling and leakage optimization in complementary resistive switch (CRS) crossbar arrays. ESSDERC 2014: 242-245 - [c1]Stefano Ambrogio, Simone Balatti, Antonio Cubeta, Daniele Ielmini:
Statistical modeling of program and read variability in resistive switching devices. ISCAS 2014: 2029-2032
Coauthor Index
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