ECE 5545 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:

  • 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.
Please read the syllabus.

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Mohamed Abdelfattah
mohamed@cornell.edu Instructor

Guandao Yang
gy46@cornell.edu Teaching Assistant

Schedule (Under Construction)