CSC2229: Computer Networks for Machine Learning - Winter 2026

Schedule

This is a tentative course schedule. Handouts and slides will be added to this page as the course progresses. Make sure to refresh the page to see the latest handouts.

# Date Topic Reading Handouts Assignments
1 Jan 6 Course Logistics and Introduction - H01 - Info sheet [pdf]
H02 - Lecture 1 [pdf][pptx]
 
2 Jan 13 Data Center Networks, Network Programming - H03 - Lecture 2 [pdf][pptx] -
3 Jan 20 Networks and ML -    
4 Jan 27 Network Transport and Multi-Path   -  
5 Feb 3 High-Performance Transport   -  
6 Feb 10 Job and Flow Scheduling   - Project proposal due on Feb 13
7 Feb 17 - - -  
8 Feb 24 Reconfigurable Data Center Networks   -  
9 Mar 3 Scaling the solutions   -  
10 Mar 10     - Intermediate report due on Mar 13
11 Mar 17     -  
12 Mar 24 Final project presentations - - -
13 Mar 31 Final project presentations - - Final report due on Apr 3

Course Description

This MSc/PhD-level course delves into the core challenges of interconnection networks, emphasizing the use of machine learning to address these issues. The rapid growth of computing demands, driven by machine learning applications, has introduced significant challenges in areas such as bandwidth, latency, and packet loss. Meeting these demands requires innovative techniques and a fresh approach to traditional networking solutions across various layers, including the link, transport, and application layers.

The course begins with a review of key concepts in computer networking, such as packet-switching systems, data center networks, and software-defined networking. It then explores advanced research challenges and cutting-edge solutions in the field. Topics include:

  • Hyperscale data center networking
  • Switch and controller design
  • Reliability, monitoring, and fault tolerance
  • Network optimization techniques
  • Network-Application Integration, reconfigurable data center networks
  • High-performance transport in data centers, focusing on congestion control, flow control, scheduling, and prioritization

Prerequisites

A previous course on computer networks (CSC2209H or equivalent) is highly recommended. Basic undergraduate courses in algorithms and probability theory are recommended.

Textbook

The course is based on recent research material, and we do not have a textbook.

Grading

  • Paper presentation: 20%
  • Final project: 70%
    • Proposal: 5%
    • Intermediate report: 10%
    • Presentation: 20%
    • Final report: 35%
  • Active participation in class and discussions: 10%

Late Submission Policy

You have a free late submission of two days. You can use these two days on any one of the deliverables (proposal, intermediate report or final report). You need to notify that TA before using your free late submission.

In addition to the free late submission, you can submit each assignment late by up to two days. For each late day beyond the free late submission, 10% of the mark will be deducted (up to 20%). Assignments/project reports will not be accepted after two days.

Teaching Assistant

  • Parsa Pazhooheshy < parsap @ cs . toronto . edu >

Bulletin Board

Please use our class bulletin board (on Piazza) to ask questions or discuss any course-related topics. You can sign up to the bulletin board here:

https://piazza.com/utoronto.ca/winter2026/csc2229

By using the bulletin board, everyone in class can read the replies, and the overall number of repeat questions is reduced. Please check the bulletin board before posting any new questions. If you have any questions that cannot be posted on the bulletin board (e.g. questions about your grades), you can e-mail the TA or the course instructor directly.

Please make sure to check the announcements folder regularly for updates regarding lectures, assignments, etc. or enable notifications on Piazza.

In addition to our bulletin board, we have a mailing list that will be used exclusively for sharing important information. We will use the email address you have used on ACORN to create this list (please make sure that is a valid email address). Please do not use this email to ask questions.

In-Class Presentations

Students will present papers from the “Reading List” throughout the term. Each presentation is expected to be 20 minutes followed by 10 minutes of Q&A and discussions.

Reading List

The list of papers we will read in this course will be added here.

Week 4

[1] Z. Wang et al., “{SRNIC}: A Scalable Architecture for {RDMA} {NICs},” presented at the 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23), 2023, pp. 1–14. Available: https://www.usenix.org/conference/nsdi23/presentation/wang-zilong.

[2] Y. Lu et al., “{Multi-Path} Transport for {RDMA} in Datacenters,” presented at the 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18), 2018, pp. 357–371. Available: https://www.usenix.org/conference/nsdi18/presentation/lu.

[3] K. Prasopoulos et al., “SIRD: A Sender-Informed, Receiver-Driven Datacenter Transport Protocol,” presented at the 22nd USENIX Symposium on Networked Systems Design and Implementation (NSDI 25), 2025, pp. 451–471. Available: https://www.usenix.org/conference/nsdi25/presentation/prasopoulos

Final Project

To be updated.