Mengyuan Li

Mengyuan Li

Ph.D. candidate from CSE department 💻 University of Notre Dame 🇺🇸

Hi! Here is Mengyuan. Welcome!

I am a final-year Ph.D. candidate in the Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA, working with Prof. X. Sharon Hu. I am also the recipient of a university fellowship.

I am currently working on accelerating the emerging memory-intensive applications with the advanced development from the underlying hardware. My current research interests are machine learning, software-hardware co-design, in-memory computing and computing with emerging technologies. I have published several hardware/software codesign works as the first author in top EDA conferences: Design automation conference (DAC), International Conference on Computer-Aided Design (ICCAD), Design automation & test in europe (DATE), Asia, and south pacific DAC (ASPDAC).

Previously, I graduated with highest honor on the B.E. degree in microelectronic science and engineering from Zhejiang University, Zhejiang, China, in 2019.

News

  • Mar 2024: Our work CAMASim: A Comprehensive Simulation Framework for Content-Addressable Memory based Accelerators is now open-sourced! Learn about the simulator!
  • Feb 2024: Our paper C4CAM: A Compiler for CAM-based In-memory Accelerators, the first end-to-end automated complication flow for CAM, is now accepted by ASPLOS 2024! Learn more about the work!
  • May 2023: Joined Apple  as summer intern to enhance large language model performance on Apple Silicon!
  • Jul 2023: Our paper Accelerating Polynomial Modular Multiplication with Crossbar-Based Compute-in-Memory has been accepted by the 42st International Conference on Computer-Aided Design (ICCAD 2023)! link
  • Oct 2022: Our paper Ferroelectric FET Configurable Memory Arrays and Their Applications shows up in the 68th International Electron Devices Meeting (IEDM 2022).
  • Sep 2022: Presented In-memory-computing architecture work in Semiconductor Research Corporation (SRC) TECHCON 2022.
  • Sep 2022: Our paper Cross-Coupled Gated Tunneling Diodes with Unprecedented PVCRs Enabling Compact SRAM Design has been accepted by IEEE Transactions on Electron Devices (TED)! link
  • Jul 2022: Our paper Associative Memory Based Experience Replay for Deep Reinforcement Learning has been accepted by the 41st International Conference on Computer-Aided Design (ICCAD 2022)! link
  • Jun 2022: Joined Amazon Lab126 Neural Network Accelerator group as summer intern. Explored ML models at edge.
  • Jun 2022: Honored as CSE Outstanding Teaching Assitant Award!
  • Feb 2022: Our paper IMARS: An In-memory-computing Architecture for Recommendation System has been accepted by the 59th Design Automation Conference (DAC 2022)! link
  • Feb 2021: Our paper A Quantization Framework for Neural Network Adaption at the Edge has been accpeted by the 24th Design Automation and Test in Europe（DATE 2021)! link
  • Aug 2020: Honored as Young Fellow in 57th Design Automation Conference (DAC 2020)!
  • Jan 2020: Our paper Nonvolatile and Energy-Efficient FeFET-Based Multiplier for Energy-Harvesting Devices has been accepted by 25th Asia and South Pacific Design Automation Conference (ASP-DAC 2020)!
  • Aug 2019: Started Ph.D. study in University of Notre Dame!
  • Jul 2019: Graduated with highest honor from Zhejiang University (China)!

Select Publications

  • H. Farzaneh, J. Lima, M. Li, A. Khan, X. Sharon Hu, J. Castrillon, ‘C4CAM: A Compiler for CAM-based In-Memory Accelerators’. link
  • M. Li, H. Geng, M. Niemier, and X. Sharon Hu, ‘Accelerating Polynoial Modular Multiplication with Crossbar-Based Compute-in-Memory’, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023. link
  • D. Reis, A. F. Laguna, M. Li, M. Niemier, and X. Sharon Hu, ‘Ferroelectric FET Configurable Memory Arrays and Their Applications’ in IEEE International Electron Devices Meeting (IEDM), 2022 (Invited).
  • M. Li, P. Wu, B. Zhou, J. Appenzeller, and X. Sharon Hu, ‘Cross-Gated Tunneling Diodes with Unprecedented PVCRs Enabling Compact SRAM Design-Part II: SRAM Circuit’, IEEE Transaction on Electron Devices (TED), 2022. link
  • M. Li, A. Kazemi, A. F. Laguna, and X. Sharon Hu, ‘Associative Memory Based Experience Replay for Deep Reinforcement Learning’, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2022. link
  • M. Li, A. F. Laguna, D. Reis, X. Yin, M. Niemier, and X. Sharon Hu, ‘IMARS: An In-memory-computing Architecture for Recommendation System’ in IEEE/ACM Design Automation Conference (DAC), 2022. link
  • M. Li, and X. Sharon Hu, ‘A Quantization Framework for Neural Network Adaption at the Edge’ in IEEE/ACM Design, Automation, and Test in Europe (DATE) Conference and Exhibition, 2021. link
  • M. Li, X. Yin, X. Sharon Hu, and C. Zhuo, ‘Nonvolatile and Energy-Efficient FeFET-Based Multiplier for Energy-Harvesting Devices’ in IEEE/ACM Asia and South Pacific Design Automation Conference (ASPDAC), 2020. link