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.

计算系统可以在整个生命周期中产生重大的环境影响，包括制造，用法和寿命处置。例如，制造工艺通常需要大量的能源并产生大量的碳排放。当计算机到达生命的尽头时，它们就会变成电子废物（电子废物）。电子垃圾，即使管理不当，由于存在危险材料，可能会给人类健康和环境带来风险。减轻这些影响是可持续计算的重大挑战。该项目介绍了创新方法，通过回收退役芯片，将它们整合以延长其寿命，并与新集成的芯片实现近乎最新的性能，从而最大程度地减少计算系统的环境影响。该项目将由匹兹堡大学和圣母大学的调查员团队进行。该项目的影响是双重的：通过将这些有毒的，不可生物降解的设备置于垃圾填埋场之外，可以大大减少制造业的碳排放，并减少与电子废物相关的环境风险。该项目通过教育和宣传活动为社会做出了宝贵的贡献，该活动旨在吸引对环境科学，生物学和人工智能感兴趣的K-12学生（AI）。该项目的主要目标是通过重复使用最近退休的现场可编程的门阵列（FPGA）来实现可持续计算，以与2.5-Dimensy（2.5-Dimensy（2.5）集成（2.5），互连。这种方法旨在显着减少新芯片制造过程产生的碳排放。该项目由四个研究推力组成。推力1专注于开发刷新FPGA体系结构和设计自动化工具流，该工具量身定制，旨在应对将硬件设计靶向非货币FPGA的挑战。推力2通过设计自动化框架进行刷新FPGA硬件分析和原型制作，能够自动选择最佳设计配置，包括芯片间连接拓扑，连接带宽以及基于其衰老条件的FPGA芯片的选择。推力3致力于开发包装中的系统可持续性分析，验证和优化过程，旨在准确地对2.5D集成刷新FPGA造成的环境影响进行准确建模和评估，包括制造，集成和包装。推力4广泛探讨了加速从机器学习到基因组学的广泛应用的最有效方法。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来获得支持的。