Self-Adjusting Networks for Optimized Datacenter Topology Design
Offered By: Scalable Parallel Computing Lab, SPCL @ ETH Zurich via YouTube
Course Description
Overview
Explore a 40-minute conference talk by Stefan Schmid on self-adjusting networks, presented at SPCL_Bcast on October 27, 2022. Delve into the challenges of modern datacenter topology designs, including static, dynamic demand-oblivious, and dynamic demand-aware switches. Discover the concept of self-adjusting networks that optimize and match their traffic workload. Learn about information-theoretic metrics for quantifying communication traffic structure and achievable performance in demand-matching datacenter networks. Examine network design principles, identify open research challenges, and understand how self-adjusting networks and demand-aware graphs relate to classic optimization problems in theoretical computer science. The talk begins with a brief speaker introduction, followed by the main presentation.
Syllabus
Speaker Introduction
Talk
Taught by
Scalable Parallel Computing Lab, SPCL @ ETH Zurich
Related Courses
Information TheoryThe Chinese University of Hong Kong via Coursera Fundamentals of Electrical Engineering
Rice University via Coursera Computational Neuroscience
University of Washington via Coursera Introduction to Complexity
Santa Fe Institute via Complexity Explorer Tutorials for Complex Systems
Santa Fe Institute via Complexity Explorer