Charles Mackin

According to our database, Charles Mackin authored at least 20 papers between 2013 and 2024.

Collaborative distances:

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

2024

VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation.

Prashanth Vijayaraghavan, Luyao Shi, Stefano Ambrogio, Charles Mackin, Apoorva Nitsure, David Beymer, Ehsan Degan

CoRR, 2024

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization.

Prashanth Vijayaraghavan, Apoorva Nitsure, Charles Mackin, Luyao Shi, Stefano Ambrogio, Arvind Haran, Viresh Paruthi, Ali El-Zein, Dan Coops, David Beymer, Tyler Baldwin, Ehsan Degan

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

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

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference.

Manuel Le Gallo, Corey Lammie, Julian Büchel, Fabio Carta, Omobayode Fagbohungbe, Charles Mackin, Hsinyu Tsai, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui, Malte J. Rasch

CoRR, 2023

Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators.

Malte J. Rasch, Charles Mackin, Manuel Le Gallo, An Chen, Andrea Fasoli, Frédéric Odermatt, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan

CoRR, 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

Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited).

Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, Stanislaw Wozniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai, Geoffrey W. Burr

Proceedings of the IEEE International Reliability Physics Symposium, 2023

2022

Precision of bit slicing with in-memory computing based on analog phase-change memory crossbars.

Manuel Le Gallo, S. R. Nandakumar, Lazar Ciric, Irem Boybat, Riduan Khaddam-Aljameh, Charles Mackin, Abu Sebastian

Neuromorph. Comput. Eng., 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

2018

Graphene chemical and biological sensors: modeling, systems, and applications.

Charles Mackin

PhD thesis, 2018

Frequency Response of Graphene Electrolyte-Gated Field-Effect Transistors.

Charles Mackin, Elaine McVay, Tomás Palacios

Sensors, 2018

2013

Rapid exploration of processing and design guidelines to overcome carbon nanotube variations.

Gage Hills, Jie Zhang, Charles Mackin, Max M. Shulaker, Hai Wei, H.-S. Philip Wong, Subhasish Mitra

Proceedings of the 50th Annual Design Automation Conference 2013, 2013