Collaborative Research: DESC: Type II: Multi-Function Cross-Layer Electro-Optic Fabrics for Reliable and Sustainable Computing Systems

随着日常消费电子产品中计算设备和系统的爆炸式增长，为信息和计算技术（ICT）提供动力所需的能源量接近全球碳排放量的5%。隐含排放来自硬件制造和与基础设施相关的能源，如原材料采购、制造、包装和组装。这与操作能量不同，操作能量来源于硬件的使用。计算的可持续性应以三项普遍接受的原则为基础-重用、减少和回收-硬件组件和系统。从可持续发展的角度来看，我们需要重用或重新利用现有的硬件平台来实现多种功能，以减少包含的排放，回收硬件以延长或延长使用寿命的可靠性，并减少硬件平台所需的操作或使用阶段的能源。因此，未来基于小芯片的硬件平台——具有定义功能的小型集成电路——在设计可持续性时应仔细设计，以平衡功率、性能和可靠性。这个研究项目在电子计算系统、光子技术、计算机体系结构、机器学习和可持续性要求之间建立了非常重要的联系。这项研究将在几个领域培养新的研究方向，包括计算机体系结构、硅光子学、算法和应用，有可能显著改变下一代可持续的基于芯片的异构计算系统的设计。所有的研究成果和模拟结果将通过会议/期刊出版、专业会议和专门的网站与社区分享。该团队致力于并将继续扩大外展活动、教育、培训，并通过必要的努力吸引和培训该领域的少数民族学生，扩大对计算机的参与，作为该项目的一部分。本研究将为计算架构和加速器设计多功能、自修复和跨层优化的电光结构，以提高可靠性、性能和可持续性。该项目的首要目标是通过减少具体能源的影响和延长硬件系统的使用寿命来增强计算系统的可持续性。该团队将全面、系统地探索电子学和硅光子学的结合，在一个集成系统中进行通信和计算，以显著提高未来计算系统的每瓦性能资源利用率、可靠性和可持续性。这项研究将产生(1)具有通信、计算和存储多种功能的新型基于电和光子互连的架构；(2)提高异构计算芯片可靠性的自修复和容错电和光学结构；(3)动态适应应用需求以降低运行能量的硬件和跨层技术。(4)广泛的建模和仿真框架，用于评估所提议架构的具体和操作能量；(5)概念验证测试平台的实现。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

With the explosion of computing devices and systems in everyday consumer electronics, the amount of energy required to power information and computing technologies (ICT) is reaching close to 5% of worldwide carbon emissions. Embodied emissions originate from the manufacturing of hardware and from infrastructure-related energy such as procurement of raw materials, fabrication, packaging, and assembly. This is distinct from operational energy, which stems from using the hardware. Sustainability in computing should be based on three universally accepted tenets – reuse, reduce and recycle – of hardware components and systems. From a sustainability perspective, we need to reuse or repurpose existing hardware platforms for multiple functionalities to reduce embodied emissions, recycle hardware to extend or prolong lifetime reliability, and reduce the operational or use-phase energy required of the hardware platform. Therefore, future hardware platforms based on chiplets, - small, integrated circuits with defined functions - should be carefully designed to balance power, performance, and reliability when designed for sustainability. This research project establishes very important connections between electronic computing systems, photonic technology, computer architecture, machine learning, and sustainability requirements. The research will foster new research directions in several areas, spanning computer architecture, silicon photonics, algorithms, and applications, with the potential to significantly transform the design of next-generation sustainable chiplet-based heterogenous computing systems. All the research findings and simulation results will be shared with the community via conference/journal publication, professional meetings, and a dedicated website. The team is committed and will continue to expand on outreach activities, education, training, and broadening participation in computing as part of the project by making the necessary efforts to attract and train minority students in this field. This research will design multi-functional, self-healing and cross-layer optimized electro-optic fabric for computing architectures and accelerators to improve reliability, performance and sustainability. The overarching goal of the project is to enhance the sustainability of computing systems by reducing the impact of embodied energy and extending the operational lifetime of hardware systems. The team will explore a combination of electronics and silicon photonics comprehensively and systematically for both communication and computation in one integrated system to dramatically improve performance-per-Watt resource utilization, reliability, and sustainability of future computing systems. This research will result in (1) novel electrical and photonic interconnect-based architectures that have multiple functionality for communication, computation and storage, (2) self-healing and fault-tolerant electrical and optical fabric that improve the reliability of the heterogeneous computing chiplets, (3) hardware and cross-layer techniques to dynamically adapt to application demands to reduce operational energy, (4) an extensive modeling and simulation framework for evaluating embodied and operational energy of the proposed architectures, and (5) proof-of-concept testbed implementation.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.