The National Science Foundation (NSF) recently awarded Peng Jiang one of its highest distinctions in research: a prestigious CAREER Award. Over the course of five years, Dr. Jiang will receive $548,944 to pursue a project entitled Compiler and Runtime Support for Sampled Sparse Computations on Heterogenous Systems.
The project will develop a suite of compiler and runtime tools to simplify the implementation of sampling-based algorithms and improve their performance in computing and big data applications while enhancing their capacity to solve real-world problems at a large scale. In doing so, the project will provide solutions to limitations of sampling-based hardware without sacrificing the accuracy and efficiency of sampling strategies.
According to the NSF’s website, the Faculty Early Career Development (CAREER) Program supports “early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization”. The award recognizes Dr. Jiang’s commitment to expanding the education and opportunities available to students, as undergraduates, including those from underrepresented groups, will have the ability to engage in his project’s system-related research.
Dr. Jiang is also the Principal Investigator of two other NSF grants. In August, the foundation awarded his three-year project, A Fine-Grained Hierarchical Memory Management System for Applications with Dynamic Memory Demand on GPUs, $519,999 to develop a new memory management system to facilitate the development of dynamic-memory applications on GPUs. Dr. Jiang later won $1 million alongside his collaborators at Illinois Institute of Technology (Rujia Wang – now at Microsoft, Kyle Hale, and Xian-He Sun) for their project, Towards A Unified Memory-centric Computing System with Cross-layer Support. The partnership proposes an integrated, full-stack, cross-layer system to enable Unified Memory-centric Computing. As the PI of both projects, Dr. Jiang will increase the applications of GPUs and near-data processing, respectively, to machine learning systems and other fields.
Peng Jiang is an assistant professor in the Department of Computer Science at the University of Iowa. Prior to obtaining his Ph.D. from Ohio State University, Jiang received his M.S. in Computer Science from the Chinese Academy of Science and his B.S. from Xidian University. His research interests include high-performance computing, systems, and machine learning.
Jiang leads the Intelligent Data-Intensive Systems Lab, a team of researchers specializing in high-performance computing, systems, and machine learning. Alongside Guanpeng Li, he also co-leads the IOWA-HPC Lab.