Efficient

Accelerating Branch-and-Bound Graph Algorithms with GPUs

Izzat El Hajj, Assistant Professor, Computer Science, American University of Beirut (AUB)

Feb 9, 12:00 - 13:00

B9 L2 R2325

parallel computing optimization GPU Algorithms HPC Graph Theory Efficient

This talk presents multiple techniques that we have developed to load balance the search tree traversal on GPUs and mitigate the strain on memory capacity and bandwidth.

From Dialects to Peptides: Scalable and Efficient AI for People

Muhammad Abdul-Mageed, Canada Research Chair, Natural Language Processing and Machine Learning; Associate Professor, School of Information, Department of Linguistics, The University of British Columbia

Feb 2, 12:00 - 13:00

B9 L2 R2325

AI Efficient Efficient Machine Learning

This talk presents a unified AI framework for decoding complex human and biological signals - spanning African and Arabic dialects to proteomics - by prioritizing rigorous measurement, cultural competence, and computational efficiency to ensure global scalability and accessibility.

Efficient Machine Learning across Hardware, Software, and Algorithms

Prof. Mohamed Abdelfattah, Electrical and Computer Engineering Department at Cornell University

Dec 17, 14:00 - 15:30

B2 L5 R5209

Efficient machine learning Hardware software algorithms

Deep neural networks (DNNs) are revolutionizing computing, necessitating an integrated approach across the computing stack to optimize efficiency. In this talk, I will explore the frontier of DNN optimization, spanning algorithms, software, and hardware. We'll start with hardware-aware neural architecture search, demonstrating how tailoring DNN architectures to specific hardware can drastically enhance performance.