This talk will be much broader and span many scientific disciplines (and necessarily, due to time constraints, less technical depth). It should be a more "university-wide" accessible talk with a little something for everyone.
With processor clock speeds plateauing in the 3-GHz range in the mid-2000s (due to the excessive heat being generated by higher clock speeds), the computing industry was forced to embrace parallel computing as a way to continue to improve performance. By the mid-2010s, parallel computing was ubiquitous (e.g., iPhone 6s) while the overall rate of performance improvement of a computing core had slowed from doubling every 1.5 years (1985-2005) to doubling only every 20 years (2015-today). Similarly, over this past decade, our digital universe of big data has grown from 1.2 zettabytes (i.e., sextillion bytes) to nearly 40.0 zettabytes, indicating a doubling of data size every 2 years. Thus, the rate of growth in big data is far outstripping the rate at which computing can (brute-force) compute on the data. As a consequence, we have turned to the co-design of architecture, software, and in particular, algorithms to more efficiently and intelligently compute on the data via algorithmic re-factoring and machine learning, respectively.
Wu Feng is a Professor of Computer Science at Virginia Tech (VT), where he directs the Synergy Lab and serves as a VT site co-director for the National Science Foundation Center for Space, High-performance, and Resilient Computing (SHREC). In addition, he holds appointments in the Department of Electrical & Computer Engineering, Health Sciences, and Biomedical Engineering and Science.
Dr. Feng has published 300+ peer-reviewed technical publications in high-performance networking and computing, high-speed systems monitoring and measurement, low-power and power-aware computing, computer science pedagogy for K-12, and bioinformatics, including the publication of "The Green Computing Book: Tackling Energy Efficiency at Large Scale" and a worldwide Microsoft commercial about his research on biocomputing in the cloud.
Dr. Feng holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign, a M.S. in Computer Engineering, and B.S. degrees in Electrical & Computer Engineering and Music from Penn State University. In addition to being a Distinguished Scientist of the ACM and Senior Member of the IEEE Computer Society, Dr. Feng has been named to HPCwire's Top People to Watch twice, once in 2004 and again in 2011.