Progress Report Meeting - May 2020

Event dates:

Friday, May 8, 2020 - 10:00 to Friday, May 22, 2020 - 12:30

Progress Report Meetings

Due to the exceptional pandemic circumstances, the progress report meeting will be held as 3 events, by theme, and online.

  • Friday, May 8th, 2020, 10h - 12h30: Low level, material and trace collection
  • Friday, May 15th, 2020, 10h - 12h30: Distributed application, trace analysis, theia
  • Friday, May 22th, 2020, 10h - 12h30: Machine learning

Participation is by invitation. The target audience is the project participants and guests of the project sponsors.

​https://polymtl.webex.com/meet/michel.dagenais
Meeting Number: 739 543 248
+1-438-797-4001 Canada Toll (Montreal)
+1-647-484-1598 Canada Toll (Toronto)
Access code: 739 543 248

Start time End time Presenter Subject
10:00 10:10 Introduction and presentation
10:10 10:30 Paul Naert Interactive Runtime Verification Using a GDB Based Architecture
10:30 10:50 Anas Balboul NOPROBE: A Fast Multi-Strategy Probing Technique For x86 Dynamic Binary Instrumentation
10:50 11:10 Arnaud Fiorini AMD ROCm GPU profiling in Trace Compass
11:10 11:40 EfficiOS LTTng and Related Projects updates
11:40 11:45 Bohémond Couka, Gabriel Pollo-Guilbert New students presentation
11:45 12:30 Open discussion on the topic: use cases, wishlist, what to improve
Start time End time Presenter Subject
10:00 10:10 Introduction and presentation
10:10 10:30 Adel Belkhiri Performance analysis of DPDK-based applications
10:30 10:40 Daniel Capelo Borges Tracing and debugging of parallel computing frameworks for streaming data
10:40 11:00 Pierre-Frédérick Denys Container-based architecture performance analysis
11:00 11:15 Herve Kabamba Tracing in Theia Compass
11:15 11:45 Ericsson/Poly Update on Trace Compass and Theia
11:45 12:00 Masoumeh Nourollahi, Quoc-Hao Tran, Léa Carlier, Soukaina Moussaoui, Ibrahima Sega Sangare New students & interns presentation
12:00 12:45 Open discussion on the topic: use cases, wishlist, what to improve
Start time End time Presenter Subject
10:00 10:10 Introduction and presentation
10:10 10:30 Irving Muller Duplicate bug report detection through machine learning techniques
10:30 10:50 Iman Kohyarnejad Anomaly detection using Machine learning
10:50 11:10 Quentin Fournier Deep Learning for Anomaly Detectionand Cause Identification
11:10 11:15 David Piché New students presentation
11:15 12:00 Open discussion on the topic: use cases, wishlist, what to improve