News Archive
2022
Prof. Meyer presents at 2022 Edge Intelligence Workshop
Prof. Brett H. Meyer was invited to present at the 2022 Edge Intelligence Workshop (EIW) on September 20. The two day workshop featured a number of prominent researchers working to develop or optimize machine learning algorithms on the resource-constrained devices at the edge of the Internet, accompanied by a wide variety of student posters. Professor Meyer’s talk focused on recent research at the McGill Edge Intelligence Lab on BERT inference latency modeling, and inference and throughput optimization through task pipelining and mapping on the Kirin 970 SoC.
2019
Profs. Gross and Meyer give deep learning tutorial at IEEE EPEPS 2019
Profs. Warren Gross and Brett H. Meyer presented a tutorial on the optimization of hardare and software for deep learning at IEEE EPEPS 2019 in Montreal today. Gross introduced machine learning in general, and deep learning in particular, from a computational perspective. He then summarized recent work on custom architecture for DNN acceleration. Meyer followed up with an introduction to multi-objective hyperparameter optimization, with a focus on deployment to low-cost IoT processors.
Prof. Meyer presents at Dawson Humanities and Public Life Conference
Prof. Brett H. Meyer presented at the Dawson College Humanities and Public Life Conference today, giving a talk entitled ‘The Algorithms Aren’t Alright: Why Machine Learning Still Needs Us.’ In it he introduced machine learning in general, deep learning in particular, and highlighted some of the challenges that arise in the application of deep learning: robustness, explainaibility, and bias.
Poster: Optimizing Keyword Spotting on Microcontrollers
Undergraduate Adithya Lakshminarayanan presented his summer research at the SURE Poster Session today. It explores the different trade-offs inherent in quantizing models for keyword spotting. FP is best for top accuracy, but 8- and 16-bit models each strike interesting trade-offs under tighter constraints.
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