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...
This $274,765 project grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) establishes a foundation for efficient and intelligent unified memory design to harness the power of advanced GPU accelerators. The key products and services to be delivered include: Developing an abstraction framework called ACCORD to capture the spatial and temporal patterns of massively parallel memory accesses, enabling quantitative...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $600,000 to The University of Central Florida Board of Trustees to develop software-hardware solutions that enable efficient execution of large AI foundation models, like those powering advanced AI applications, on smaller, resource-limited computer systems. The key research thrusts include: 1) designing a sparsity-aware scheduling system to...
This Project Grant award of $210,000 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports an interdisciplinary research effort to develop an efficient, situation-aware artificial intelligence (AI) processing system leveraging advanced 2-terminal spin-orbit torque magnetic random access memory (SOT-MRAM) technology. The project brings together experts across materials science, device fabrication, integrated circuit design,...
This Project Grant award for $557,158.00, funded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070), supports research to devise novel mathematical operators that address the computational bottlenecks of graph-based artificial intelligence (AI) applications. The project aims to unlock sustainable and scalable performance for modern AI-based applications, such as autonomous systems, traffic forecasting, social media, drug...
The U.S. National Science Foundation (NSF) awarded a $120,120 CAREER grant under the Computer and Information Science and Engineering (CISE) program to The Johns Hopkins University. The project, titled "DEEPMATTER: A Scalable and Programmable Embedded Deep Neural Network", will develop novel methodologies for optimizing deep neural network (DNN) models to enable their deployment on embedded systems with limited hardware resources and power budgets. The research aims to create new DNN...
This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, will support research to develop advanced profiling techniques for improving the performance of deep learning models running on Graphics Processing Units (GPUs). The $221,138 award, effective July 1, 2025 through June 30, 2030, will fund the development of three innovative analysis techniques: unified binary code analysis to identify...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program grant of $599,951 awarded to Washington State University aims to develop a novel computing framework for accelerating graph neural network (GNN) computations using processing-in-memory (PIM) architectures. The key objectives are to: 1) establish an interdisciplinary research-based curriculum integrating PIM, machine learning, and data-driven design optimization, 2) motivate and engage...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $292,237 to the University of Illinois to develop novel technologies that empower non-computer science researchers to effectively utilize modern, highly parallel hardware for training advanced AI models for scientific discovery. The key products and services to be delivered include: 1) novel memory-efficient and hardware-friendly...
This $1,200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a collaborative research initiative called "MPI4AI: Enhancing Performance and Productivity of AI Science through Next-Generation High Performance Communication Abstractions." The project aims to improve how massively parallel computers run large-scale artificial intelligence (AI) applications by enhancing the Message...