CAI 4104 - Machine Learning Hardware

Credits: 3

Course Description: This course will focus on the hardware aspects of machine learning systems, including the design and implementation of efficient hardware for the processing of machine learning algorithms. Topics include computer arithmetic units, floating point operations, hardware realization of arithmetic functions to support various computer architectures along with arithmetic algorithms for firmware/software implementation, design principles of accelerator architecture, Inmemory Processing, and understanding key optimization techniques for machine learning algorithms to improve their efficiency on various hardware platforms.
Prerequisites: EEL 3702 - Digital Logic Design and EEL 3112 - Circuits 2 and MAS 3114 - Computational Linear Algebra
Primary Term(s) Offered: Fall, Spring Rotation Year