Collaborative Research: DESC: Type II: REFRESH: Revisiting Expanding FPGA Real-estate for Environmentally Sustainability Heterogeneous-Systems

合作研究：DESC：类型 II：REFRESH：重新审视扩展 FPGA 空间以实现环境可持续性异构系统

• 批准号: 2324865
• 负责人: Yiyu Shi
• 金额: $ 50万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324865&HistoricalAwards=false
• 关键词: Collaborative; Research; DESC; Type; II

Computing systems can exert substantial environmental impacts across their entire life cycles, encompassing manufacturing, usage, and end-of-life disposal. For example, manufacturing processes often require significant amounts of energy and produce substantial carbon emissions. When computers reach the end of their life, they become electronic waste (e-waste). E-waste, if not properly managed, can pose risks to human health and the environment due to the presence of hazardous materials. Mitigating these impacts is a significant challenge for sustainable computing. This project introduces innovative approaches to minimize the environmental impact of computing systems by recycling decommissioned chips, integrating them to extend their lifespans, and achieving near state-of-the-art performance with the newly integrated chips. The project will be carried out by a team of investigators from the University of Pittsburgh and the University of Notre Dame. The project's impacts are twofold: significantly reducing carbon emissions from manufacturing and mitigating environmental risks associated with e-waste by keeping these toxic, non-biodegradable devices out of landfills. This project is making valuable contributions to society through education and outreach activities designed to engage K-12 students with an interest in environmental science, biology, and artificial intelligence (AI).The primary goal of this project is to achieve sustainable computing by reusing recently retired field-programmable gate array (FPGA) chips to build REFRESH FPGA devices and employing 2.5-dimensional (2.5D) integration with an underlying interposer for interconnection. This approach aims to significantly reduce carbon emissions incurred from the fabrication process of new chips. The project consists of four research thrusts. Thrust 1 focuses on developing REFRESH FPGA architecture and design automation toolflow, tailored to address the challenge of targeting hardware designs onto non-monolithic FPGAs. Thrust 2 investigates REFRESH FPGA hardware analysis and prototyping through a design automation framework capable of automatically selecting the optimal design configuration including inter-chip connection topology, connection bandwidth, and the selection of FPGA chips based on their aging condition. Thrust 3 is dedicated to developing a system-in-a-package sustainability analysis, validation, and optimization process, aiming to accurately model and assess the environmental impacts stemming from the 2.5D integrated REFRESH FPGAs including fabrication, integration, and packaging. Thrust 4 extensively explores the most effective methodologies for accelerating a wide range of applications from machine learning to genomics.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.

计算系统可以在其整个生命周期中对环境产生重大影响，包括制造、使用和报废处置。例如，制造过程通常需要大量的能源，并产生大量的碳排放。当计算机的寿命到尽头时，它们就变成了电子垃圾(电子垃圾)。电子垃圾如果管理不当，由于存在危险材料，可能会对人类健康和环境构成风险。减轻这些影响是可持续计算面临的重大挑战。该项目引入了创新的方法，通过回收退役芯片，将其整合以延长其使用寿命，并通过新整合的芯片实现接近最先进的性能，从而将计算系统对环境的影响降至最低。该项目将由匹兹堡大学和圣母大学的一组研究人员进行。该项目的影响有两个：显著减少制造业的碳排放，并通过使这些有毒、不可生物降解的设备远离垃圾填埋场来缓解与电子垃圾相关的环境风险。该项目通过旨在吸引对环境科学、生物学和人工智能(AI)感兴趣的K-12学生的教育和推广活动为社会做出宝贵贡献。该项目的主要目标是通过重复使用最近退役的现场可编程门阵列(FPGA)芯片来构建更新的FPGA设备，并采用2.5维(2.5D)集成和底层插入器进行互联，从而实现可持续计算。这种方法旨在显著减少新芯片制造过程中产生的碳排放。该项目由四个研究项目组成。SPECT 1专注于开发更新的现场可编程门阵列架构和设计自动化工具流，旨在应对将硬件设计定位于非单片现场可编程门阵列的挑战。推力2通过设计自动化框架研究更新的FPGA硬件分析和原型，该框架能够自动选择最优的设计配置，包括芯片间连接拓扑、连接带宽和基于老化条件的FPGA芯片选择。Struts 3致力于开发封装系统可持续性分析、验证和优化流程，旨在准确建模和评估2.5D集成更新现场可编程门阵列(包括制造、集成和封装)所产生的环境影响。推力4广泛探索了加速从机器学习到基因组的广泛应用的最有效方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。