ECE 498NS/598NS: Deep Learning in Hardware

Lecture Notes

  • 2019/8/27: Introduction [ PDF ]

  • 2019/8/29: Deep Learning - An Introduction [ PDF ]

  • 2019/9/3: Reducing DNN Complexity via Quantizaion [ PDF ] [ Python Notebook ]

  • 2019/9/5: Quantizaion [ PDF ] [ Python Notebook ]

  • 2019/9/10: Fixed-point DNNs [ PDF ]

  • 2019/9/12: Low Complexity DNNs [ PDF ]

  • 2019/9/17: DNN Training - I [ PDF ]

Lecture Notes from Fall 2017 Offering

  • Introduction [PDF]

  • The LMS Algorithm and Architecture [PDF]

  • Fixed-Point LMS [PDF]

  • Algorithm-to-Architecture Mapping Techniques [PDF]

  • Energy-Delay Trade-offs [PDF]

  • Logistic Regression, ADALINE, and Perceptron [PDF]

  • The Support Vector Machine [PDF]

  • Training via the Stochastic Gradient Descent Algorithm [PDF]

  • Boosting and Random Forest [PDF]

  • Deep Learning [PDF]

  • DianNao Case Study [PDF]

  • Introduction to Shannon-inspired Statistical Computing and Algorithmic Noise Tolerance [PDF]

  • Beyond Algorithmic Noise Tolerance [PDF]

  • Deep In-Memory Computing [PDF]