Project Grant 2523804
- This Project Grant award of $275,000.00 from the National Science Foundation's Computer and Information Science and Engineering (CISE) program aims to develop modular hardware accelerators that enable secure and efficient deployment of fine-tuned foundation models on consumer devices. The award, made on September 1, 2025, supports research by George Mason University to address challenges in local deployment of large, computationally-intensive foundation models, which power a wide range of AI...
- 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 in funding to the University of Central Florida 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 project aims to improve the efficiency, scalability, and resource utilization of...
- This $266,667 Project Grant award from the National Science Foundation's Division of Computing and Communication Foundations supports research on improving the development process for hardware accelerators and their associated software. The project, titled "Collaborative Research: SHF: Medium: High-Performance, Verified Accelerator Programming", aims to extend the concept of end-to-end formal verification to cover hardware accelerators, specifically tensor processing units (TPUs), used...
- This $533,000 Project Grant, awarded by the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program, supports collaborative research by the Massachusetts Institute of Technology (MIT) to develop end-to-end formal verification techniques for hardware accelerators, specifically tensor processing units (TPUs). The key objectives are to dramatically reduce the costs of developing and iterating on...
- The National Science Foundation (NSF) awarded a $249,724 Computer and Information Science and Engineering (CFDA 47.070) project grant to the University of California, Irvine (UCI) to develop an efficient compilation and synthesis flow from high-level programs to domain-specific reconfigurable heterogeneous acceleration systems. This project aims to create a framework that combines hardened digital accelerators, reconfigurable digital logic, and general-purpose processors to address the diversity...
- This Project Grant award of $450,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop novel approaches to electronic design automation (EDA) for creating high-performance and efficient computer hardware. The research introduces a strategy that combines formal techniques with learning-based optimization to enable differentiable hardware synthesis, particularly suited for heterogeneous computing. This new...
- 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...
- The National Science Foundation (NSF) awarded a $340,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Missouri System to develop sustainability-aware design methods for approximate deep neural network (DNN) accelerators. The key objectives of this 3-year project are: Investigating efficient neural architecture search techniques for reliable and sustainable approximate DNN accelerator designs. Developing fault mitigation and...
- This $250,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at Northeastern University to improve the security of machine learning models in multi-tenant cloud field programmable gate array (FPGA) environments. The three-year award aims to advance understanding of vulnerabilities in cloud-FPGAs shared by multiple tenants, where a malicious actor could potentially manipulate another tenant's machine learning...
- The National Science Foundation (NSF) has awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Delaware. The 3-year grant, awarded on October 1, 2025, will support research to develop a proactive and intelligent framework for securing system-on-chips (SoCs) against power side-channel and fault injection attacks. The project will leverage reinforcement learning and game theory to model evolving attacker-defender...
The National Science Foundation (NSF) awarded a $325,000 Project Grant under the CISE Crosscutting Small: SATC: SAGE program to Howard University. The grant supports the development of modular hardware accelerators that will enable secure and efficient deployment of fine-tuned foundation models in consumer devices. The project aims to address the challenges of deploying large, computationally intensive foundation models on resource-constrained platforms while protecting them from security risks like intellectual property theft and malicious tampering. Key objectives include building a heterogeneous system with a GPU and custom accelerator, devising advanced acceleration methodologies, and implementing active locking mechanisms to protect the fine-tuned models. The project will culminate in the production of a secure and modular accelerator realized on a physical platform, advancing interdisciplinary research to enhance the security and resilience of the U.S. AI semiconductor supply chain.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $325.0k | 7/28/25 |