This $200,000 project grant was awarded by the National Science Foundation (NSF) under its Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to The Ohio State University. The project aims to enhance the energy efficiency of training and inference for large language models (LLMs), which are crucial for advanced artificial intelligence applications but are very energy-intensive. The key objectives are to: Identify and characterize idleness in LLM workloads to enable...
The National Science Foundation (NSF) awarded a $1,499,602 Project Grant under its Computer and Information Science and Engineering (CISE) program to The Ohio State University. The grant aims to create and sustain a cohort of Cyberinfrastructure (CI) professionals to empower researchers across diverse fields to effectively leverage machine learning (ML) techniques. Key objectives include enhancing interdisciplinary collaboration, fostering innovation, and developing long-term career paths for...
This $200,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enhance the energy efficiency of large language models (LLMs) used in advanced artificial intelligence applications. The key research goals are to: Identify and characterize idleness in LLM workloads to enable lower-power dynamic voltage and frequency scaling (DVFS) control and undervolting to reduce static energy...
The National Science Foundation (NSF) awarded a $599,995 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) federal grant program to Carnegie Mellon University (CMU). The grant supports a 3-year research project focused on developing sustainable and energy-efficient approaches to large-scale machine learning across domains such as natural language processing, computer vision, and scientific AI applications. The project aims to enhance training efficiency,...
This $400,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports collaborative research at The Ohio State University on principled approaches to deep learning for low-dimensional data structures. The research aims to develop a unified mathematical framework for designing and explaining deep neural networks, particularly in the context of leveraging the inherent low-dimensionality of real-world...
This $564,958 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance fundamental knowledge and innovate resource allocation algorithms for modern computing systems serving machine learning applications. The project focuses on addressing the challenges posed by high variability and uncertainty in both demand and service capabilities in these systems. The research will explore two key thrusts:...
The National Science Foundation (NSF) awarded a $174,200 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) program to the University of North Carolina at Chapel Hill (UNC-CH) to develop new resource allocation policies for optimizing the scheduling of parallelizable machine learning (ML) training workloads on shared hardware clusters. The goal is to enable the rapid and efficient training of highly accurate ML models using limited computing resources. This...
This $343,156 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to improve the efficiency of large language models (LLMs) for artificial intelligence applications. The key objectives are to develop new software partitioning and FPGA-based distributed hardware approaches to optimize LLM inference, as well as platform-aware compression techniques. This co-design research aims to make...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, valued at $600,000, is supporting a project to develop software-hardware solutions that enable advanced AI applications, such as ChatGPT, to run efficiently on smaller, less powerful computer systems. The key products and services to be delivered through this 3-year project (April 2025 - March 2028) include: Innovations to address data transfer bottlenecks...
This $1.2 million Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the University of Pittsburgh to expedite machine learning applications on multi-GPU infrastructure. Specifically, the university will uncover and address architectural bottlenecks in deep neural network executions on multi-GPU systems. Researchers will redesign translation lookaside buffer hierarchies and page table walks to reduce address...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to The Ohio State University. The grant funds a 3-year project focused on developing a holistic management framework to handle bursty machine learning (ML) inference requests in data centers with latency guarantees and reduced capital expenses (CAPEX).
The key components of the project include: 1) Co-locating ML inference and training workloads on the same GPUs to improve utilization and reduce the number of GPUs needed; 2) Designing a task scheduling algorithm to consolidate negatively correlated ML tasks onto shared GPUs for further CAPEX savings; and 3) Leveraging existing energy storage devices in data centers to supply additional power during request bursts, avoiding costly power/cooling infrastructure upgrades. The project aims to benefit ML/AI companies by allowing data centers to handle inference bursts more efficiently and cost-effectively.