This $162,825 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of DLTOOLKIT, a performance profiling infrastructure for scientific deep learning applications. The project aims to create novel profiling capabilities including synergistic tool-framework integration, just-in-time-aware profiling, and tensor-centric analysis. These capabilities will enable domain scientists to optimize the performance of their deep learning workloads across various scientific domains like high-energy physics, meteorology, and material science. The project also includes an educational component to integrate the DLTOOLKIT outcomes into computer science curricula and provide research training, symposia, and internships for students, particularly at the University of California, Merced, which is a minority-serving institution. The award period runs from June 15, 2025 to May 31, 2028.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $162.8k | 6/9/25 |