Alexander M. Friz

According to our database, Alexander M. Friz authored at least 9 papers between 2020 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

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