Project Grant 2520269
- The National Science Foundation awarded a $709,723 Project Grant under the Engineering program (CFDA 47.041) to the Georgia Tech Research Corporation for the "COLLABORATIVE RESEARCH: ASCENT: OPTIMAL THERMAL MANAGEMENT FOR CONTINUED SCALING OF 3D HETEROGENEOUS SYSTEMS" project. This research aims to address the critical thermal management challenges hindering the widespread adoption of advanced artificial intelligence (AI) and computing systems. The project will integrate expertise in...
- The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University, Division (doing business as Orspa), for the project "COLLABORATIVE RESEARCH: SHF: MEDIUM: TINY CHIPLETS FOR BIG AI: A RECONFIGURABLE-ON-PACKAGE SYSTEM". This 4-year project (7/1/2024 - 6/30/2028) aims to pioneer a computing system for massive AI workloads, including new architectural and design automation...
- This Project Grant award, funded by the U.S. National Science Foundation (NSF) under the Engineering program (CFDA 47.041), supports a collaborative research project between Duke University and ETH Zürich to explore the thermal implications of scaling and structure of metal contacts to two-dimensional (2D) semiconductor materials. The $400,000 award, effective September 1, 2024 through August 31, 2027, aims to: 1) develop an apparatus for nanoscale thermal mapping of 2D contact structures; 2)...
- This Project Grant award, granted by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084), provides $550,000 in funding to Carnegie Mellon University for the development of high-performance, nanostructured thermal pads to enhance heat dissipation in electronics. The key products or services to be delivered under this award include scalable and cost-effective manufacturing strategies to mass produce the nanostructured thermal pads,...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $600,000 to Arizona State University (ASU) for a project titled "Type I: Water- and Carbon-Aware Design of Chiplet-Based Systems with Reconfigurability for AI in Datacenters." The goal is to develop new methods and tools for designing computer chips with a reduced environmental footprint, particularly in terms of...
- This $350,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports the "COLLABORATIVE RESEARCH: ASCENT: HETEROGENEOUSLY INTEGRATED ELECTRONIC PHOTONIC AI ACCELERATORS (HIEPAA)" project led by the University of California, San Diego (UCSD). The project aims to develop energy-efficient artificial intelligence (AI) hardware by integrating thin-film lithium niobate, a high-performance electro-optic material, with silicon photonic chip...
- This $300,000 EAGER Project Grant from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will support the development of lock-in infrared thermography for characterizing the thermal resistance of interconnects in 3D integrated circuits. The objective is to advance thermal property measurement science and engineering, and deliver improved metrology tools that can meet the needs of the microelectronics industry. Key aspects include developing an analytical model for heat...
- This Cooperative Agreement award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $1,214,897.00 to support the development of a novel central processing unit (CPU) cooler that will enhance the performance of existing and next-generation CPUs. The project, led by Taumat LLC, aims to treat CPUs as dynamic systems and develop a paradigm shift in CPU thermal management. The key innovations include the scalable production of...
- This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop strategies for efficiently leveraging idle resources in high-performance computing (HPC) systems to accelerate large-scale artificial intelligence (AI) workloads. The key objectives are to: 1) analyze patterns of idle resources in HPC environments, 2) develop methods to safely and rapidly harvest these idle resources, and...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $298,658 to Clarkson University to develop TASCHIPS, an open-source, high-performance simulation tool for thermal analysis of modern microprocessors. The project aims to enable fast and accurate prediction of chip temperature distributions, allowing researchers and engineers to design more reliable, sustainable, and...
COLLABORATIVE RESEARCH: ASCENT: OPTIMAL THERMAL MANAGEMENT FOR CONTINUED SCALING OF 3D HETEROGENEOUS SYSTEMS -RECENT ADVANCEMENTS IN ARTIFICIAL INTELLIGENCE (AI) DRIVE UNPRECEDENTED INNOVATION BUT FACE THE CRITICAL CHALLENGE OF ESCALATING POWER CONSUMPTION. THE RAPID EXPANSION OF AI LEADS TO UNSUSTAINABLE ENERGY USE FOR COMPUTATION AND COOLING, THREATENING ITS WIDESPREAD ADOPTION. WHILE THREE-DIMENSIONAL HETEROGENEOUS INTEGRATION OFFERS PERFORMANCE AND ENERGY EFFICIENCY GAINS THROUGH MINIATURIZATION FOR DATA-INTENSIVE AI WORKLOADS, THIS MINIATURIZATION SIMULTANEOUSLY INCREASES POWER DENSITY AND REDUCES THERMAL CONDUCTIVITY. THIS CREATES SEVERE LOCALIZED HOTSPOTS THAT SIGNIFICANTLY DEGRADE SYSTEM PERFORMANCE, EFFICIENCY, AND RELIABILITY, NEGATING AN ESTIMATED 40% OF POTENTIAL GAINS FROM EACH TECHNOLOGY GENERATION. THE RESEARCH TEAM ADDRESSES THIS CRUCIAL BARRIER IN AI AND COMPUTING. THE INTELLECTUAL MERITS OF THIS EFFORT LIE IN AN UNPRECEDENTED, CONVERGENT RESEARCH THAT INTEGRATES EXPERTISE IN CIRCUITS AND ARCHITECTURES, OPTIMAL CONTROL, AND THERMAL TRANSPORT AND MODELING. ADVANCES IN CIRCUIT DESIGN, THERMAL MODELING, AND CONTROL THAT ARE ENABLED BY THIS RESEARCH CONVERGE TO REALIZE, FOR THE FIRST TIME, A COMPREHENSIVE FRAMEWORK FOR THERMAL MANAGEMENT. THE BROADER IMPACT OF THIS RESEARCH EXTENDS BEYOND ITS POTENTIAL TO ALLEVIATE THERMAL CHALLENGES, AND THUS PAVING THE WAY FOR CONTINUED TECHNOLOGICAL ADVANCES IN COMPUTING. BY CAPTURING THE INCREASINGLY CRITICAL INTERACTIONS BETWEEN THE COMPUTATIONAL AND PHYSICAL STATE OF THE SYSTEM, THE OPEN-SOURCE CRUCIBLE SIMULATION TOOL REPRESENTS A CRITICAL FRAMEWORK FOR THERMAL MANAGEMENT ACROSS A BROAD RANGE OF SYSTEMS. BOTH THE RELEVANCE AND IMPACT OF THIS TOOL ARE MAGNIFIED THROUGH ACTIVE AND CONTINUOUS ENGAGEMENT WITH THE SEMICONDUCTOR INDUSTRY. THIS RESEARCH ALSO CONTRIBUTES TO BROADER EDUCATIONAL ADVANCEMENT OF UNDERGRADUATE AND GRADUATE COURSES, DISSEMINATION OF RESULTS, AND DEVELOPMENT OF AN OPEN-SOURCE INFRASTRUCTURE FOR RUN-TIME CYBER-PHYSICAL SYSTEM MANAGEMENT FOR NATIONWIDE STUDENT USE. CURRENT DESIGN-TIME AND RUN-TIME TECHNIQUES FOR MITIGATING HOTSPOTS DO NOT SCALE EFFECTIVELY TO LARGER SYSTEMS AND OFFER LIMITED CAPABILITIES FOR SENSING AND ACTUATION TO MAINTAIN THERMAL COMPLIANCE. AS A RESULT, THESE METHODS ARE ILL-SUITED FOR MODERN HETEROGENEOUS THREE-DIMENSIONAL HETEROGENEOUS INTEGRATION SYSTEMS. THERE IS CURRENTLY NO EXISTING MECHANISM THAT CAN ANALYZE OR SIMULATE THESE SYSTEMS IN A CLOSED-LOOP MANNER, PROVIDING ACCURATE DIGITAL-PHYSICAL MODELING THAT PRECISELY REFLECTS THE RUN-TIME IMPACT OF CONTROLLER ACTIONS ON SYSTEM FUNCTION, PERFORMANCE, AND THERMAL PROPERTIES. TO ADDRESS THIS CRITICAL GAP, THE RESEARCH TEAM PROPOSES RUN-TIME OPTIMAL THERMAL MANAGEMENT FOR THREE-DIMENSIONAL HETEROGENEOUS INTEGRATION. THIS APPROACH SEEKS TO MAXIMIZE A GIVEN PERFORMANCE OBJECTIVE WHILE ADHERING TO SYSTEM-WIDE THERMAL CONSTRAINTS. INSTEAD OF MORE TRADITIONAL MILLISECOND-SCALE CONTROL OF VOLTAGE AND FREQUENCY, THIS PROJECT AIMS TO ACHIEVE MICROSECOND-SCALE SENSING, ACTUATION, AND CONTROL CIRCUITRY. THE RESEARCH TEAM WILL ACHIEVE THIS RAPID RESPONSE BY COMBINING A FINE-GRAINED NETWORK OF THERMAL AND LOAD CURRENT SENSORS WITH AN ACCURATE REDUCED-ORDER PREDICTIVE THERMAL MODEL AND HIERARCHICAL MODEL PREDICTIVE CONTROL AT RUNTIME. THIS EFFORT REPRESENTS A NOVEL CONFLUENCE OF TECHNIQUES FROM THERMAL MODELING, CIRCUIT DESIGN, AND CONTROL. THE PROPOSED APPROACH MINIMIZES THE NEED FOR CONSERVATIVE THERMAL MARGINS, THUS UNLOCKING AND RELEASING SIGNIFICANT PERFORMANCE AND EFFICIENCY GAINS WITH EACH NEW TECHNOLOGY GENERATION. A SIGNIFICANT OUTCOME OF THIS RESEARCH WILL BE THE CREATION OF CRUCIBLE, A TOOL-AGNOSTIC SIMULATION FRAMEWORK. CRUCIBLE RELIES ON THE EXISTING CAPABILITIES OF WIDELY AVAILABLE SWITCH-LEVEL SIMULATORS TO JOINTLY MODEL BOTH THE DIGITAL AND PHYSICAL CHARACTERISTICS OF THE CLOSED-LOOP CONTROL SYSTEM AT USER-DEFINED TIMESCALES. CRUCIBLE IS ANTICIPATED TO FACILITATE METHODICAL EXPLORATION INTO RUN-TIME SYSTEM OPTIMIZATION THAT REQUIRES INTEGRATED DIGITAL-PHYSICAL MODELING AND CONTROL. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $60.0k | 8/19/25 |