EE 508 Hardware Foundations of Machine Learning

Units: 4
Terms Offered: Sp

Introduction to ML accelerators; memory access kernels; parallelization approaches to the design of scalable ML systems; distributed ML; privacy in machine learning.
Recommended Preparation: Matrix algebraic algorithms on the level of EE 141; Gradient descent, PyTorch, Tensorflow or similar parallel programming experience on the level of EE 451; Memory systems of CPUs and GPUs on the level of EE 457
Instruction Mode: Lecture, Discussion
Grading Option: Letter