Aditya Ramamoorthy earns NSF funding for practical coded matrix computation project

Award Winner: Aditya Ramamoorthy

Award Title: Collaborative Research: CCSS: Practical Coded Matrix Computation

Award Category: Project Funding Award

Award Description: 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 suffer from the problem of stragglers (slow or failed workers), especially when they are deployed within cloud computing platforms; this can cause an undesirable increase in the overall job execution time. The overall goal of this project is to research techniques for mitigating the effect of stragglers in the specific context of distributed matrix computations. This project will also provide training for students in the usage of cloud platforms. In addition, the project also involves outreach activities to local schools for mathematics tutoring and the creation of K-12 computer science modules. This is project is collaborative between Iowa State University and the University of Akron (in Ohio).

Award website: Here

Co-PIs: None

Funding Source: NSF

Award Amount: $160,465