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2020 – today
- 2024
[c11]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:
Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization. MLCAD 2024: 28:1-28:10- [i3]Prashanth Vijayaraghavan, Luyao Shi, Stefano Ambrogio, Charles Mackin, Apoorva Nitsure, David Beymer, Ehsan Degan:
VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation. CoRR abs/2406.04379 (2024) - 2023
- [j5]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:
An analog-AI chip for energy-efficient speech recognition and transcription. Nat. 620(7975): 768-775 (2023) - [c10]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:
Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). IRPS 2023: 1-10 - [c9]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:
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). ISCAS 2023: 1-5 - [c8]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:
Phase Change Memory-based Hardware Accelerators for Deep Neural Networks (invited). VLSI Technology and Circuits 2023: 1-2 - [i2]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:
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators. CoRR abs/2302.08469 (2023) - [i1]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:
Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference. CoRR abs/2307.09357 (2023) - 2022
- [j4]Manuel Le Gallo, S. R. Nandakumar, Lazar Ciric, Irem Boybat, Riduan Khaddam-Aljameh, Charles Mackin, Abu Sebastian:
Precision of bit slicing with in-memory computing based on analog phase-change memory crossbars. Neuromorph. Comput. Eng. 2(1): 14009 (2022) - [c7]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
- [j3]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) - [c6]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 - [c5]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
- [c4]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 - [c3]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 - [c2]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
- [j2]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) - 2018
- [b1]Charles Mackin:
Graphene chemical and biological sensors: modeling, systems, and applications. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [j1]Charles Mackin, Elaine McVay, Tomás Palacios:
Frequency Response of Graphene Electrolyte-Gated Field-Effect Transistors. Sensors 18(2): 494 (2018) - 2013
- [c1]Gage Hills, Jie Zhang, Charles Mackin, Max M. Shulaker, Hai Wei, H.-S. Philip Wong, Subhasish Mitra:
Rapid exploration of processing and design guidelines to overcome carbon nanotube variations. DAC 2013: 105:1-105:10
Coauthor Index
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