This research group evolved from Computer Architecture research group (original CARG). Computer architecture research group was formed in 2008 and focused on the following topics: computer architectures, signal processing architectures, hardware and software accelerators, GPU architectures and programming and algorithmic modifications for more efficient implementation in hardware. In recent years our research has gone in several different directions and therefore we decided to change the name of our group to Computational analysis and acceleration research group (new CARG).
January 2020: Sandeep Kumar Reddy Kadapa joined CARG as a M.Sc. student
November 2019: We have received NSERC Engage Grant with Ericsson titled AI Methods for Automated Software Testing
November 2019: Khurram Shafiq joined CARG as a M.Sc. student
The group is focusing on the intersection between probabilistic machine learning mainly using computational methods, high performance computing with the emphasis on acceleration of the algorithms and applications of computational analysis in medicine, tracking, signal and image processing.
The group is performing research in the following areas:
- Computational analysis includes development of mathematical models for data analysis. Learning in these models normally relies on computational approximate methods and therefore the term: computational analysis. We focus on signal processing, probabilistic machine learning and deep learning models.
- Hardware and software accelerators and algorithmic modifications for more efficient implementation in hardware
- Biomedical, economy and other applications of machine learning and data analysis
An important objective of our group is to conduct research in close collaboration with industry and other academic groups.
Recent talks and presentations
Keynote speech, “Computer Architectures and Algorithms: From Filtering to Deep Learning,” EMCA Developer Conference, Ericsson, Ottawa, May, 2019.