Solving Max-Min Fair Resource Allocations Quickly on Large Graphs
Offered By: USENIX via YouTube
Course Description
Overview
Explore a cutting-edge conference talk on solving max-min fair resource allocation problems efficiently for large-scale graphs. Dive into innovative approaches that improve upon existing solutions, including a method to convert optimization sequences into a single fast optimization and a generalization of waterfilling for multi-path scenarios. Discover how these new algorithms Pareto-dominate previous techniques, delivering faster, fairer, and more efficient allocations. Learn about the theoretical guarantees of some allocators and their practical implementation in Azure's WAN traffic engineering pipeline, resulting in significant speedups while maintaining solution quality. Gain insights into the potential impact of these advancements on WAN traffic engineering and cluster scheduling, particularly for larger problem sizes.
Syllabus
NSDI '24 - Solving Max-Min Fair Resource Allocations Quickly on Large Graphs
Taught by
USENIX
Related Courses
Deep Learning for Natural Language ProcessingUniversity of Oxford via Independent Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
DeepLearning.AI via Coursera Deep Learning Part 1 (IITM)
Indian Institute of Technology Madras via Swayam Deep Learning - Part 1
Indian Institute of Technology, Ropar via Swayam Logistic Regression with Python and Numpy
Coursera Project Network via Coursera