This Project Grant award of $274,265.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the development of a novel performance profiling and analysis infrastructure called DLTOOLKIT. The project, led by George Mason University, aims to create advanced profiling capabilities tailored for domain scientists to analyze and optimize their scientific deep learning (DL) applications. The key products and...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $162,825 to the University of California, Merced to develop DLTOOLKIT, a performance profiling infrastructure for domain scientists to analyze and optimize scientific deep learning applications. The key objectives of this 3-year project are to create novel profiling capabilities, including synergistic tool-framework integration, just-in-time...
The National Science Foundation (NSF) has awarded a $299,999 Project Grant to the College of William & Mary under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: A COMPILATION SYSTEM FOR MAPPING DEEP LEARNING MODELS TO TENSORIZED INSTRUCTIONS (DELITE)," will fund research to develop a compilation system that can optimize deep neural network (DNN) workloads for emerging tensorized instruction...
This $131,959 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research conducted by Rutgers, The State University to develop new deep learning training methods that can efficiently scale to utilize high-performance computing (HPC) systems. The key goals are to: 1) Explore techniques like second-order information approximation, computation-communication tradeoffs, and data compression to enhance the speed...
The National Science Foundation (NSF) awarded a $221,138 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Merced. The grant titled "REFORMING PROFILING TECHNIQUES TO GUIDE SYSTEMIC PERFORMANCE TUNING FOR GPU-ACCELERATED DEEP LEARNING WORKLOADS" aims to advance state-of-the-art profiling techniques to enable systemic performance tuning of deep learning models across multiple abstraction layers, from the...
This $174,999 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support a research project at the University of Central Missouri. The project aims to develop a unified, large language model (LLM)-empowered framework to systematically address software performance challenges. Key objectives include automating performance testing, issue localization, and optimization. The research will integrate...
This Project Grant from the National Science Foundation's $201,262 Computer and Information Science and Engineering program (CFDA 47.070) supports the development of interactive training materials and workshops on deep learning systems and applications in advanced GPU cyberinfrastructure. The University of North Texas will lead the effort in collaboration with Southern Illinois University Carbondale from December 1, 2022 to November 30, 2024. Under the award, the University of North Texas will...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program grant award, with a total funding of $549,999.00, supports the DIAMOND project aimed at democratizing access to cutting-edge deep learning methods for scientific applications. The University of Illinois, as the prime awardee, will develop a web service-enabled platform that abstracts the use of high-performance computing resources, allowing domain scientists to focus on neural network...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) program, titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: A COMPILATION SYSTEM FOR MAPPING DEEP LEARNING MODELS TO TENSORIZED INSTRUCTIONS (DELITE)", provides $299,999 in funding to the University Of Georgia Research Foundation, Inc. over a 3-year period from October 1, 2023 through September 30, 2026. The grant supports the development of a compilation system...
The National Science Foundation (NSF) has awarded a $750,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Wisconsin System for the "COLLABORATIVE RESEARCH: FRAMEWORKS: DIAMOND: DEMOCRATIZING LARGE NEURAL NETWORK MODEL TRAINING FOR SCIENCE" project. This 3-year effort aims to develop the DIAMOND service, which will democratize access to cutting-edge deep learning (DL) methods by abstracting the use of high-performance...