Charles Mackin

29 papers A* 1C 4Journal 12Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	CODMAS: A Dialectic Multi-Agent Collaborative Framework for Structured RTL Optimization. EACL (Industry Track) Che-Ming Chang, Prashanth Vijayaraghavan, Ashutosh Jadhav, Charles Mackin, Hsinyu Tsai, Vandana V. Mukherjee, Ehsan Degan
2026	J	`jnl`	CODMAS: A Dialectic Multi-Agent Collaborative Framework for Structured RTL Optimization. CoRR Che-Ming Chang, Prashanth Vijayaraghavan, Ashutosh Jadhav, Charles Mackin, Vandana V. Mukherjee, Hsinyu Tsai, Ehsan Degan
2026	—	`conf`	SYMDIREC: A Neuro-Symbolic Divide-Retrieve-Conquer Framework for Enhanced RTL Synthesis and Summarization. EACL (Industry Track) Prashanth Vijayaraghavan, Apoorva Nitsure, Luyao Shi, Charles Mackin, Ashutosh Jadhav, David Beymer, Ehsan Degan, Vandana V. Mukherjee
2026	J	`jnl`	SYMDIREC: A Neuro-Symbolic Divide-Retrieve-Conquer Framework for Enhanced RTL Synthesis and Summarization. CoRR Prashanth Vijayaraghavan, Apoorva Nitsure, Luyao Shi, Charles Mackin, Ashutosh Jadhav, David Beymer, Ehsan Degan, Vandana V. Mukherjee
2025	—	`conf`	Analog AI Accelerators for Transformer-based Language Models: Hardware, Workload, and Power Performance. IMW H. Tsai, Hadjer Benmeziane, Irem Boybat, Julian Büchel, Pritish Narayanan, Manuel Le Gallo, S. Jain, Athanasios Vasilopoulos, W. Simon, Kohji Hosokawa, M. Ishii, Yasuteru Kohda, A. Chen, Charles Mackin, Kaoutar El Maghraoui, Atsuya Okazaki, Alexander M. Friz, Jose Luquin, Abu Sebastian, V. Narayanan, Geoffrey W. Burr
2025	—	`conf`	Analog-AI Hardware Accelerators for Low-Latency Transformer-Based Language Models (Invited). CICC Geoffrey W. Burr, H. Tsai, Irem Boybat, William Andrew Simon, Julian Büchel, Athanasios Vasilopoulos, Pritish Narayanan, Andrea Fasoli, Kohji Hosokawa, Manuel Le Gallo, M. Ishii, Yasuteru Kohda, Atsuya Okazaki, A. Chen, Charles Mackin, Elena Ferro, Kaoutar El Maghraoui, Hadjer Benmeziane, T. Philicelli, Corey Lammie, Alexander M. Friz, Jose Luquin, S. Jain, Abu Sebastian, V. Narayanan
2025	J	`jnl`	Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization. CoRR 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
2025	—	`conf`	RTLExplain: A Structured Approach to RTL Code Summarization and Question Answering for Medium-to-Large Designs Using LLMs. MLCAD Ting-Hsun Chi, Charles Mackin, Luyao Shi, Prashanth Vijayaraghavan, Hsinyu Tsai, Ehsan Degan
2025	J	`jnl`	Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing. CoRR Jose Luquin, Charles Mackin, Stefano Ambrogio, An Chen, F. Baldi, G. Miralles, Malte J. Rasch, Julian Büchel, M. Lalwani, W. Ponghiran, Paul Solomon, Hsinyu Tsai, Geoffrey W. Burr, Pritish Narayanan
2024	—	`conf`	Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization. MLCAD 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
2024	J	`jnl`	VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation. CoRR Prashanth Vijayaraghavan, Luyao Shi, Stefano Ambrogio, Charles Mackin, Apoorva Nitsure, David Beymer, Ehsan Degan
2023	J	`jnl`	An analog-AI chip for energy-efficient speech recognition and transcription. Nat. 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
2023	C	`conf`	Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). ISCAS 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
2023	J	`jnl`	Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators. CoRR 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
2023	—	`conf`	Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). IRPS 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
2023	—	`conf`	Phase Change Memory-based Hardware Accelerators for Deep Neural Networks (invited). VLSI Technology and Circuits 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
2023	J	`jnl`	Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference. CoRR 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
2022	C	`conf`	Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers. ISCAS 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
2022	J	`jnl`	Precision of bit slicing with in-memory computing based on analog phase-change memory crossbars. Neuromorph. Comput. Eng. Manuel Le Gallo, S. R. Nandakumar, Lazar Ciric, Irem Boybat, Riduan Khaddam-Aljameh, Charles Mackin, Abu Sebastian
2021	C	`conf`	Circuit Techniques for Efficient Acceleration of Deep Neural Network Inference with Analog-AI (Invited). ISCAS 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
2021	—	`conf`	Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation. IRPS 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
2021	J	`jnl`	Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices. Frontiers Comput. Neurosci. 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
2020	—	`conf`	Accelerating Deep Neural Networks with Analog Memory Devices. AICAS Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, An Chen, Andrea Fasoli, Alexander M. Friz, Geoffrey W. Burr
2020	—	`conf`	Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges. IRPS Charles Mackin, Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, Katie Spoon, Andrea Fasoli, An Chen, Alexander M. Friz, Robert M. Shelby, Geoffrey W. Burr
2020	C	`conf`	Optimization of Analog Accelerators for Deep Neural Networks Inference. ISCAS Andrea Fasoli, Stefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, Charles Mackin, Katherine Spoon, Alexander M. Friz, An Chen, Geoffrey W. Burr
2019	J	`jnl`	AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed. IBM J. Res. Dev. 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
2018	J	`jnl`	Frequency Response of Graphene Electrolyte-Gated Field-Effect Transistors. Sensors Charles Mackin, Elaine McVay, Tomás Palacios
2018	—	`—`	Graphene chemical and biological sensors: modeling, systems, and applications. Charles Mackin
2013	A*	`conf`	Rapid exploration of processing and design guidelines to overcome carbon nanotube variations. DAC Gage Hills, Jie Zhang, Charles Mackin, Max M. Shulaker, Hai Wei, H.-S. Philip Wong, Subhasish Mitra