Project Grant 2209563
Award Date
8/15/22
Completion Date
7/31/25
Dollars Obligated
$1.2M
Federal Agency
Office of Advanced Cyberinfrastructure
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Los Angeles, CA 90089, USA
Similar Awards
This $599,999 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports the development of scalable and accurate solutions for temporal graph machine learning (TGML). The project aims to create a robust cyber infrastructure toolkit that enables efficient training and inference of TGML models, allowing researchers and practitioners to analyze large-scale temporal graphs with improved accuracy and scalability. The...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) supports a collaborative research effort to accelerate the execution of large-scale graph problems on distributed computing systems. The $2,656,268 award, active from August 1, 2023 to July 31, 2028, aims to develop new algorithms, software frameworks, and hardware accelerators to efficiently process large graph datasets in domains like computational...
This three-year, $532,241 Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of scalable algorithms, systems, and infrastructures for graph neural network training. The University of Massachusetts will develop a novel "split parallelism" training paradigm to transparently scale graph neural network training to large-scale graphs...
This NSF Project Grant award from the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $150,000.00 in funding to the University of California, Los Angeles (UCLA) from September 1, 2024 to August 31, 2027. The project aims to develop new methods for analyzing, generating, and optimizing graph-structured data, with potential applications in areas such as social network analysis and molecular design. The key research focus areas include: (1) creating more...
This $1,091,988 federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new framework to systematically design and optimize high-performance graph analytics algorithms. The researchers at the University of California, Davis (UC Davis) will create an open-source software platform that allows for automated exploration of implementation choices for graph computations using a...
The National Science Foundation awarded a $499,979 project grant to the George Washington University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research towards developing high-performance machine learning techniques on graphs from October 1, 2021 to September 30, 2024. The Computer and Information Science and Engineering program aims to advance computing and informatics research and education. This award will further those goals by...
The University of Southern California was awarded a two-year, $175,000 Project Grant from the National Science Foundation Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support research into improving the scalability of deep learning methods on high-performance computing systems through an I/O-centric approach. The Computer and Information Science and Engineering program aims to advance...
This Project Grant award, provided by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), seeks to accelerate the execution of large graph problems on large, distributed machines. The $327,975 award to the Trustees of Indiana University, doing business as Indiana University, will fund a collaborative research effort across three interdependent main thrusts: new algorithms for graph...
This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) supports research to develop novel mathematical models and efficient algorithms for deep learning on large-scale graph-structured data. The $249,999 award, spanning September 2024 to August 2027, aims to produce innovations in areas like graph convolutional networks, graph matching, and graph clustering. The research will involve graduate...
This $330,000 Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) supports collaborative research at the Massachusetts Institute of Technology (MIT) to accelerate the execution of large graph problems on large, distributed computing systems. The project aims to develop new algorithms, software frameworks, and specialized hardware to enable more efficient processing of graph...