Stefano Ambrogio

According to our database, Stefano Ambrogio authored at least 26 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

An analog-AI chip for energy-efficient speech recognition and transcription.

Stefano Ambrogio, Pritish Narayanan, Atsuya Okazaki, Andrea Fasoli, Charles Mackin, Kohji Hosokawa, Akiyo Nomura, Takeo Yasuda, An Chen, Alexander M. Friz, Masatoshi Ishii, Jose Luquin, Yasuteru Kohda, Nicole Saulnier, Kevin Brew, Samuel Choi, Injo Ok, Timothy Philip, Victor Chan, Mary Claire Silvestre, Ishtiaq Ahsan, Vijay Narayanan, Hsinyu Tsai, Geoffrey W. Burr

Nat., 2023

Phase Change Memory-based Hardware Accelerators for Deep Neural Networks (invited).

Geoffrey W. Burr, Pritish Narayanan, Stefano Ambrogio, Atsuya Okazaki, Hsinyu Tsai, Kohji Hosokawa, Charles Mackin, Akiyo Nomura, Takeo Yasuda, J. Demarest, Kevin Brew, Victor Chan, Samuel Choi, T. Gordon, T. M. Levin, Alexander M. Friz, Masatoshi Ishii, Yasuteru Kohda, An Chen, Andrea Fasoli, Jose Luquin, Nicole Saulnier, S. Teehan, Ishtiaq Ahsan, Vijay Narayanan

Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023

Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited).

Hsinyu Tsai, Pritish Narayanan, Shubham Jain, Stefano Ambrogio, Kohji Hosokawa, Masatoshi Ishii, Charles Mackin, Ching-Tzu Chen, Atsuya Okazaki, Akiyo Nomura, Irem Boybat, Ramachandran Muralidhar, Martin M. Frank, Takeo Yasuda, Alexander M. Friz, Yasuteru Kohda, An Chen, Andrea Fasoli, Malte J. Rasch, Stanislaw Wozniak, Jose Luquin, Vijay Narayanan, Geoffrey W. Burr

Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

2022

Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers.

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

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices.

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

Frontiers Comput. Neurosci., 2021

Circuit Techniques for Efficient Acceleration of Deep Neural Network Inference with Analog-AI (Invited).

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

Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation.

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

Proceedings of the IEEE International Reliability Physics Symposium, 2021

2020

Optimization of Analog Accelerators for Deep Neural Networks Inference.

Andrea Fasoli, Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, Alexander M. Friz, An Chen, Geoffrey W. Burr

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges.

Charles Mackin, Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, Katie Spoon, Andrea Fasoli, An Chen, Alexander M. Friz, Robert M. Shelby, Geoffrey W. Burr

Proceedings of the 2020 IEEE International Reliability Physics Symposium, 2020

Accelerating Deep Neural Networks with Analog Memory Devices.

Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, An Chen, Andrea Fasoli, Alexander M. Friz, Geoffrey W. Burr

Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2019

AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed.

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

IBM J. Res. Dev., 2019

Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration.

Massimo Giordano, Giorgio Cristiano, Koji Ishibashi, Stefano Ambrogio, Hsinyu Tsai, Geoffrey W. Burr, Pritish Narayanan

IEEE J. Emerg. Sel. Topics Circuits Syst., 2019

Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses.

Stefano Bianchi, I. Muñoz-Martín, Giacomo Pedretti, Octavian Melnic, Stefano Ambrogio, Daniele Ielmini

Proceedings of the 2019 Symposium on VLSI Circuits, Kyoto, Japan, June 9-14, 2019, 2019

2018

A 4-Transistors/1-Resistor Hybrid Synapse Based on Resistive Switching Memory (RRAM) Capable of Spike-Rate-Dependent Plasticity (SRDP).

Valerio Milo, Giacomo Pedretti, Roberto Carboni, Alessandro Calderoni, Nirmal Ramaswamy, Stefano Ambrogio, Daniele Ielmini

IEEE Trans. Very Large Scale Integr. Syst., 2018

Equivalent-accuracy accelerated neural-network training using analogue memory.

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

Nat., 2018

Stochastic Learning in Neuromorphic Hardware via Spike Timing Dependent Plasticity With RRAM Synapses.

Giacomo Pedretti, Valerio Milo, Stefano Ambrogio, Roberto Carboni, Stefano Bianchi, Alessandro Calderoni, Nirmal Ramaswamy, Alessandro S. Spinelli, Daniele Ielmini

IEEE J. Emerg. Sel. Topics Circuits Syst., 2018

2017

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays.

Pritish Narayanan, Lucas L. Sanches, Alessandro Fumarola, Robert M. Shelby, Stefano Ambrogio, Jun-Woo Jang, Hyunsang Hwang, Yusuf Leblebici, Geoffrey W. Burr

Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Neuromorphic devices and architectures for next-generation cognitive computing.

Geoffrey W. Burr, Pritish Narayanan, Robert M. Shelby, Stefano Ambrogio, Hsinyu Tsai, Scott L. Lewis, Kohji Hosokawa

Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Improved Deep Neural Network Hardware-Accelerators Based on Non-Volatile-Memory: The Local Gains Technique.

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

Proceedings of the IEEE International Conference on Rebooting Computing, 2017

2016

Modeling of reliability and neuromorphic application of resistive switching devices.

Stefano Ambrogio

PhD thesis, 2016

Neuromorphic computing with hybrid memristive/CMOS synapses for real-time learning.

Daniele Ielmini, Stefano Ambrogio, Valerio Milo, Simone Balatti, Zhongqiang Wang

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

2015

True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices.

Simone Balatti, Stefano Ambrogio, Zhongqiang Wang, Daniele Ielmini

IEEE J. Emerg. Sel. Topics Circuits Syst., 2015

Understanding pulsed-cycling variability and endurance in HfOx RRAM.

Simone Balatti, Stefano Ambrogio, Zhongqiang Wang, Scott Sills, Alessandro Calderoni, Nirmal Ramaswamy, Daniele Ielmini

Proceedings of the IEEE International Reliability Physics Symposium, 2015

Data retention statistics and modelling in HfO2 resistive switching memories.

Stefano Ambrogio, Simone Balatti, Zhongqiang Wang, Yu-Sheng Chen, Heng-Yuan Lee, Frederick T. Chen, Daniele Ielmini

Proceedings of the IEEE International Reliability Physics Symposium, 2015

2014

Statistical modeling of program and read variability in resistive switching devices.

Stefano Ambrogio, Simone Balatti, Antonio Cubeta, Daniele Ielmini

Proceedings of the IEEE International Symposium on Circuits and Systemss, 2014

Analytical modelling and leakage optimization in complementary resistive switch (CRS) crossbar arrays.

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, D. C. Gilmer

Proceedings of the 44th European Solid State Device Research Conference, 2014