Peng Jiang and his collaborators at Illinois Institute of Technology (Rujia Wang - now at Microsoft, Kyle Hale, and Xian-He Sun) won a $1M award from National Science Foundation (NSF) to investigate novel architectures and programming models for next-generation systems integrating near-data processing.

The project, entitled Towards A Unified Memory-centric Computing System with Cross-layer Support, aims to address the memory performance bottleneck for data-centric applications. The PIs propose an integrated, full-stack, cross-layer system to enable Unified Memory-centric Computing. The outcome of the project will enable experiments and deployment of data-centric applications at larger scales, facilitating research in the AI area and improving the availability of large-scale data mining and machine learning systems for solving real-world problems.

Peng Jiang is an Assistant Professor in the Department of Computer Science at the University of Iowa. His research interests are in the areas of Parallel Programming, Compiler Optimization, and High-Performance Machine Learning.

Dr. Jiang is also the Principal Investigator for a recently-awarded NSF grant entitled A Fine-Grained Hierarchical Memory Management System for Applications with Dynamic Memory Demand on GPUs. That project aims to develop a new memory management system to facilitate the development of dynamic-memory applications on GPUs. The outcome of this project will unlock the power of GPUs for a wide variety of applications with complex and dynamic memory usage, including bioinformatics, scientific computing, and machine learning. This three-year project has been awarded $519,999.