Who we are

We are a creative research group based out of the University of Guelph with an emphasis on researching intelligent tools and algorithms for FPGA design automation. Our work is currrently centered around using state-of-the-art algorithms, particularly machine learning techniques, to enhance the routing and placement processes of automated FPGA and VLSI design.

Current research topics include:

• AI for FPGA CAD
  • Machine Learning for Congestion Estimation/Management
  • Deep Learning for Timing-Driven Placement
  • Reinforcement Learning for adaptive/dynamic flows
• FPGA and GPU Acceleration
• CUDA-accelerated Neural Networks for Electronic Design Automation
• CAD Algorithms and methods

Questions? You can contact us by clicking here!