Distributed Training for Efficient Machine Learning - Part II - Lecture 18
Offered By: MIT HAN Lab via YouTube
Course Description
Overview
Dive into the second part of distributed training in this 55-minute lecture from MIT's 6.5940 course on Efficient Machine Learning. Led by Professor Song Han, explore advanced concepts and techniques for scaling machine learning models across multiple devices. Gain insights into parallel processing strategies, communication protocols, and optimization methods that enable training large-scale models efficiently. Access accompanying slides at efficientml.ai to enhance your understanding of distributed training architectures and their implementation in real-world scenarios.
Syllabus
EfficientML.ai Lecture 18: Distributed Training (Part II) (MIT 6.5940, Fall 2023, Zoom)
Taught by
MIT HAN Lab
Related Courses
Computer ArchitecturePrinceton University via Coursera High Performance Computer Architecture
Georgia Institute of Technology via Udacity Computation Structures - Part 1: Digital Circuits
Massachusetts Institute of Technology via edX Computer Architecture
Indian Institute of Technology Madras via Swayam Computer Systems Design for Energy Efficiency
Chalmers University of Technology via edX