Collaborative Research: SHF: Small: Reimagining Communication Bottlenecks in GNN Accelerat — NSF Award to William Marsh Rice Unive
The digital revolution has generated a vast volume of interconnected data, often represented as graphs, which is pertinent to numerous critical real-world applications. This has led to the increasing prevalence of Graph Neural Networks (GNNs), a technique that extends the benefits of Artificial Intelligence (AI) to gra
| Award title | Collaborative Research: SHF: Small: Reimagining Communication Bottlenecks in GNN Accelerat |
|---|---|
| Award ID | 2610649 |
| Awardee | William Marsh Rice University |
| City | HOUSTON |
| State | TX |
| Amount obligated | $264,299 |
| Principal investigator | Tong Geng |
| Program | Software & Hardware Foundation |
| Start date | 01/01/2026 |
| Abstract | The digital revolution has generated a vast volume of interconnected data, often represented as graphs, which is pertinent to numerous critical real-world applications. This has led to the increasing prevalence of Graph Neural Networks (GNNs), a technique that extends the benefits of Artificial Intelligence (AI) to graph-based applications. GNNs hold promising potential to significantly impact society, from accelerating drug discovery and preventing supply chain disruptions, to averting cascadin |
| Source | NSF Awards |
$799/mo
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