Collaborative Research: CCSS: Practical Coded Matrix Computation — NSF Award to Iowa State University (IA, $160,465)
Large scale matrix computations are at the heart of several modern technologies that are revolutionizing human life. These include, the now ubiquitous deep learning models, large language models, and scientific computing for supporting research in various domains. The sheer size of the data and models in these domains
| Award title | Collaborative Research: CCSS: Practical Coded Matrix Computation |
|---|---|
| Award ID | 2503640 |
| Awardee | Iowa State University |
| City | AMES |
| State | IA |
| Amount obligated | $160,465 |
| Principal investigator | Aditya Ramamoorthy |
| Program | CSCS: Circuits and Systems for |
| Start date | 10/01/2025 |
| Abstract | Large scale matrix computations are at the heart of several modern technologies that are revolutionizing human life. These include, the now ubiquitous deep learning models, large language models, and scientific computing for supporting research in various domains. The sheer size of the data and models in these domains requires such computations to be performed in a distributed manner over large clusters, whereby an overall job is divided into smaller tasks. Unfortunately, these clusters often su |
| Source | NSF Awards |
$799/mo
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