CICI: UCSS: Securing GPU Computing for AI-Driven Scientific Workflows — NSF Award to University of Rochester (NY, $599,943)
Enhancing memory safety in Graphics Processing Units (GPUs) is an essential requirement for secure Artificial Intelligence (AI) technologies. Scientific research increasingly depends on advanced AI technologies to drive breakthroughs, with GPUs serving as fundamental computational resources. Many scientific cyberinfras
| Award title | CICI: UCSS: Securing GPU Computing for AI-Driven Scientific Workflows |
|---|---|
| Award ID | 2530649 |
| Awardee | University of Rochester |
| City | ROCHESTER |
| State | NY |
| Amount obligated | $599,943 |
| Principal investigator | Yanan Guo |
| Program | Cybersecurity Innovation |
| Start date | 12/01/2025 |
| Abstract | Enhancing memory safety in Graphics Processing Units (GPUs) is an essential requirement for secure Artificial Intelligence (AI) technologies. Scientific research increasingly depends on advanced AI technologies to drive breakthroughs, with GPUs serving as fundamental computational resources. Many scientific cyberinfrastructures (CIs) have made substantial investments in GPUs to support such efforts. While GPUs deliver considerable performance benefits, the security of GPU software, and memory sa |
| Source | NSF Awards |
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