Zhiru Zhang, associate professor of electrical and computer engineering, has received a $50,000 award from Facebook Research for his proposal titled “Algorithm-Systems Co-Optimization for Near-Data Graph Learning.”
“We received 132 proposals from 74 universities, which was an increase from last year’s 88 proposals. It was a difficult task to select a few research awards from a large pool of high-quality proposals,” says Maxim Naumov, a Research Scientist working on AI system co-design at Facebook. “We believe that the winners will help advance the state-of-the-art in ML/DL system design.”
“This project aims to improve the efficiency of machine learning on graphs, which are being adopted in a new generation of recommender systems,” Zhang explained. “Graph learning can effectively capture the user's intentions as well as the useful characteristics of the preferred items.”
Today's graph learning systems struggle to scale to large graphs due to their compute- and data-intensive nature. To address this challenge, Zhang's team will investigate new graph learning techniques in the context of near-data computing, especially with near-memory or in-storage acceleration using smart solid state drives.