This is my personal list of resources related to machine learning systems. Feel free to drop me an email if you think there’s something worth mentioning. I will try to update this page frequently to include the most recent stuffs in mlsys.

Resources

• Facebook’s external large-scale work
• NGC Container Doc: great for development, without having to manually install CUDA, pytorch, and other dependencies.
• Awesome-System-for-Machine-Learning: A curated list of research in machine learning systems (MLSys). Paper notes are also provided.
• Mastering LLM Techniques: Inference Optimization: summary of techniques used for LLM deployment
• LLM Visualization

Courses

• Deep Learning Systems: Algorithms and Implementation
• Machine Learning Compilation: offered by Tianqi Chen, intro to ML compiler. Open to all.
• 15-884: Machine Learning Systems: offered by Tianqi Chen at CMU.
• CSE 291F: Advanced Data Analytics and ML Systems: offered by Arun Kumar at UCSD.
• Tinyflow: tutorial code on how to build your own Deep Learning System in 2k Lines.
• CSE 599W: Systems for ML: offered by Tianqi Chen at UW.
• CS8803-SMR: Special Topics: Systems for Machine Learning: offered by Alexey Tumanov at Georgia Tech. [schedule]
• CS 744: Big Data Systems: offered by Aditya...