Monitoring and Debugging of High Performance Distributed Heterogeneous Cloud Applications

Visit the project page

The research project is decomposed into 4 tracks.

  1. Distributed Applications in the Cloud, Edge and 5G network
  2. Heterogeneous Multi-Core Coprocessors
  3. Machine Learning and performance analysis Tools
  4. New Architecture for Tool integration

Automated monitoring and debugging of large scale manycore heterogeneous systems

Visit the project website

The AMDLS research project is decomposed into 4 tracks.

  1. Data collection through the whole hardware/software stack
  2. Architecture for real-time and scalable system-level and cloud-level monitoring and analysis
  3. Anomaly Detection and diagnosis with Machine Learning
  4. Tracing and debugging support for advanced programming environments

Software Debugging and Monitoring for Heterogeneous Many-Core Telecom Systems (HSDM)

Visit the project website

HSDM project is decomposed into 6 sub-projects which are detailed in this page. Tracks 1 to 5 are part of the base NSERC Cooperative Research and Development project, while track 6 is to be financed by Prompt:

  1. Tracing, Debugging and Profiling Mechanisms and Architecture on Many-Core Systems
  2. Cloud Debugging and Monitoring
  3. Advanced analysis
  4. Parallel and Incremental Analysis
  5. Model-Driven Engineering support
  6. Case Studies

Diagnostics for Real Time Distributed Multi-core Architecture in Avionics

Visit the project website

This project has four research axes:

  1. Tracing and Sampling for Real-Time partially simulated Avionics Systems
  2. Analysis of Real-Time Avionics Systems from Tracing and Sampling data
  3. Trace abstraction and correlation techniques for real-time avionic systems
  4. Visualization of Avionic System Traces

Online surveillance of critical computer systems through advanced host-based detection

Visit the project website

This project has four research axes:

  1. Scalable Observation infrastructure - Low disturbance multi-level observation and production of enhanced data
  2. Scalable Observation infrastructure - Advanced host-based Centralized data store and software pattern identification
  3. Scalable Detection infrastructure - Harmonized Anomaly Detection Techniques
  4. Scalable Detection infrastructure - Knowledge base for the Linux kernel

Integrated tracing, profiling and debugging for tuning large heterogeneous clusters

Visit the project website

This project has four research axes:

  1. Tracing the whole hardware infrastructure, from network processors to application-specific many-core processors
  2. Coordinating multiple sources of monitoring information in the cluster
  3. Cluster level modeling and analysis
  4. Integration of Tracer in Cloud Computing Environment

Tracing and Monitoring Tools for Distributed Multi-Core Systems

Visit the project website

This three-year project is jointly funded by Ericsson, Defence Research and Development Canada et le National Sciences and Engineering Research Council of Canada. Lead by École Polytechnique's DORSAL, it is being done is collaboration with Concordia University, Laval University and the Université of Ottawa. It is composed of seven research axes:

  1. Adaptative fault probing
  2. Multi-level, multi-core distributed traces synchronization
  3. Trace Abstraction, Analysis and Correlation
  4. Automated Fault Identification
  5. Trace Directed Modeling
  6. System Health Monitoring and Reactive measures activation
  7. Tracing and Monitoring Framework Impact Prediction