Machine Learning Systems: Design and Implementation, 2nd Edition

This book provides a comprehensive introduction to the design and implementation of modern machine learning systems. It covers the full technology stack, from programming interfaces and AI accelerators to distributed training, model serving, and large-scale GPU cluster management.

The 2nd edition has been significantly restructured and expanded to reflect the rapid evolution of the ML systems landscape, including new chapters on AI compilers, RL systems, and GPU cluster management.

• 前言
• Basic
  • Chapter 1: Introduction
  • Chapter 2: Programming Interfaces and Computational Graphs
  • Chapter 3: AI Accelerators and Programming
• System
  • Chapter 4: AI Compilers and Runtime Systems
  • Chapter 5: Data Processing Systems
  • Chapter 6: Training Systems
• Applications and More
  • Chapter 7: Model Serving
  • Chapter 8: RL Systems
  • Chapter 9: Large-scale GPU Cluster Management