15-849 Advanced Topics in Computer Systems: Machine Learning Systems

12 units, Carnegie Mellon University

In this course, we will explore the design of modern ML systems by learning how an ML model written in highlevel languages is decomposed into lowlevel kernels and executed across heterogeneous hardware accelerators e.g., TPUs and GPUs in a distributed fashion. Topics covered in this course include neural networks and backpropagation, programming models for expressing ML models, automatic differentiation, deep learning accelerators, distributed training techniques, computation graph optimizations, automated kernel generation, memory optimizations, etc.

Prerequisites: none listed

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