Collaborative Research: Elements: DLToolkit: A Novel Performance Profiling and Analysis In — NSF Award to George Mason University
Deep Learning (DL) has improved scientific applications across various scientific domains, including high-energy physics, meteorology, agriculture, and material science. This project introduces DLToolkit, a performance profiling infrastructure tailored for domain scientists to analyze and optimize science-driven DL app
| Award title | Collaborative Research: Elements: DLToolkit: A Novel Performance Profiling and Analysis In |
|---|---|
| Award ID | 2411134 |
| Awardee | George Mason University |
| City | FAIRFAX |
| State | VA |
| Amount obligated | $274,265 |
| Principal investigator | Keren Zhou |
| Program | Software Institutes |
| Start date | 06/15/2025 |
| Abstract | Deep Learning (DL) has improved scientific applications across various scientific domains, including high-energy physics, meteorology, agriculture, and material science. This project introduces DLToolkit, a performance profiling infrastructure tailored for domain scientists to analyze and optimize science-driven DL applications. This project also contributes to education and supports broader usage; the outcomes of this project will be integrated into the Computer Science (CS) curriculum, and bot |
| Source | NSF Awards |
$799/mo
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