Seminar: Why Parallel Computing?
Wu Feng
Professor, Computer Science
Director, Synergy Lab
Virginia Tech
Friday, December 6, 2024
2:30 - 3:45PM
3100 Torgersen Hall
Abstract
This talk motivates the need for parallel and distributed computing across the entire software stack from the application and its underlying algorithms to programming ecosystems (including tools) to systems software and runtime systems to architecture. From the applications and algorithms perspective, the talk will briefly touch on research in global climate modeling, computational fluid dynamics, biological sequence search, carcinogenesis, parallel programming with pictures, image processing, biomedical imaging (for COVID-19) and graph processing. The talk will then dive down the software stack to examine "write once, run anywhere" ecosystems for parallel and distributed computing on heterogeneous resources (i.e., CPU, GPU, and FPGA) and related simultaneous co-scheduling of such heterogeneous resources as well as scalability of deep-learning systems via I/O analysis and optimization.
Biography
Wu Feng is a Professor of Computer Science at Virginia Tech (VT), where he directs the Synergy Lab and serves as the VT site co-director for the NSF 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 Mechanics. His research sits at the synergistic intersection of architecture, software, algorithms, and applications for high-performance parallel and distributed computing. He has published 300+ peer-reviewed manuscripts in high-performance computing and networking, green computing, and computational science and engineering. Of particular note are "The Green Computing Book: Tackling Energy Efficiency at Large Scale" as well as the Green500 List and a worldwide Microsoft cloud commercial about his biocomputing research. He holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (1996), a M.S. in Computer Engineering (1990), and B.S. degrees in Electrical & Computer Engineering and Music from Penn State University (1988).