ECE 5545 (CS 5775) is a master's level course that takes a hardware-centric view of machine learning systems, from constrained embedded microcontrollers to large distributed multi-GPU systems. These are our learning objectives:
Please read the syllabus.
Understand how machine learning algorithms run on computer systems. This includes both the hardware and the software that maps computations onto the computer chips.
Apply key optimization techniques such as pruning, quantization and distillation to machine learning algorithms to improve their efficiency on different hardware platforms.
Analyze the performance and efficiency of different hardware platforms with and without optimizations, and understand the impact of efficiency optimizations on the accuracy of a machine learning algorithm.
Design both the hardware and software components of a machine learning computer system, including a compiler to map/optimize neural networks to different hardware.