This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $564,958 to Carnegie Mellon University from December 1, 2024 to November 30, 2027. The project aims to advance fundamental knowledge and innovate resource allocation algorithms to address the challenges posed by high variability and uncertainty in both demand and service in modern computing systems, especially those supporting machine learning applications. The research will explore two main thrusts: 1) using coding-theoretic techniques to design more flexible servers to handle multiple job types and heterogeneous demands, and 2) developing online-learning-based job scheduling strategies that dynamically estimate service capabilities. This work seeks to improve the performance and energy efficiency of data centers, thereby reducing their carbon footprint while maintaining flexibility, affordability, and scalability in computing services. The project will also promote interdisciplinary collaboration and educational initiatives, including mentorship opportunities for underrepresented groups in STEM and curriculum development in data science and machine learning.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $565.0k | 11/20/24 |