DESC:Type I: Sustainable Serverless Computing

云计算通过支持从智能手机、数字医疗设备、联网车辆和智能家居系统等联网平台按需访问强大的计算机系统资源，改变了我们的日常生活。无服务器计算是一种新兴的范式，它使这些智能平台能够访问细粒度的功能级云微服务。该模式允许云计算服务提供商更高效地配置其计算资源，从而为开发人员和服务提供商节省成本。这反过来有望使数字智能更容易获得、负担得起，并在我们的日常生活中无处不在。然而，无服务器计算最大的突出挑战之一是支持功能级的性能保证，同时最大限度地减少托管无服务器计算的云数据中心对环境的影响。云数据中心已经是全球碳排放、废水产生和电力使用的主要贡献者，而无服务器计算将加剧全球环境的这些压力。这个项目将涉及变革性的研究，以实现可持续的无服务器计算，三个主要推动力将以综合方式解决：1)将进行无服务器计算的性能和可持续性建模，以捕获数据中心中无服务器工作流的性能，同时首次表征支持无服务器计算的碳足迹和水使用，包括制造、运营、运输、用水和报废的管理费用；2)将开发封装层增强功能，以解决无服务器计算的一些最大性能瓶颈，如高启动、低性能存储和容错；同时最小化与无服务器计算相关的运营和具体碳足迹；3)将基于混合进化学习和多代理强化学习设计编排层增强，以最大限度地减少无服务器计算对环境的影响，同时满足地理上分布的数据中心平台的性能目标。该项目与国家气候发现云(NDC-C)计划的目标一致，因为它涉及基于云的数据建模、分析和优化，用于各种新兴的无服务器计算应用，包括来自多模式数据的天气预测和气候建模，有望推进气候相关研究。该项目还旨在从根本上实现更可持续的云计算基础设施，这些基础设施可以支持NDC-C计划范围内的大规模气候科学和工程工作负载，同时减少执行它们的云计算数据中心对环境的破坏性影响。强调表征和共同优化无服务器计算的性能和环境影响，将促进低成本云计算的扩散，使其更具成本效益和无缝集成到可以丰富我们日常生活的计算驱动的服务中。劳动力发展是该项目的另一个重要的更广泛的影响，高中生、本科生和研究生在高性能计算、优化理论和环境可持续发展等多学科领域进行培训。与工业合作伙伴的密切合作也将确保研究成果的及时传播和整合到现实世界的可持续气候友好型计算倡议中。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。

Cloud computing has transformed our everyday lives by enabling on-demand access to powerful computer system resources from Internet-connected platforms including smartphones, digital health devices, connected vehicles, and smart home systems. Serverless computing is an emerging paradigm that enables fine granularity function-level cloud microservices to be accessible by these smart platforms. The paradigm allows cloud computing service providers to more efficiently provision their compute resources, which translates into cost savings for both developers and service providers. This in turn is expected to make digital intelligence more accessible, affordable, and pervasive in our everyday lives. However, one of the biggest outstanding challenges with serverless computing is to support function-level performance guarantees while minimizing the environmental impact of cloud datacenters that host serverless computing. Cloud datacenters are already a major contributor to global carbon emissions, wastewater generation, and electricity use, and serverless computing will exacerbate these pressures on the global environment. This project will involve transformative research to realize sustainable serverless computing with three major thrusts that will be addressed in an integrated manner: 1) Performance and sustainability modeling for serverless computing will be conducted to capture the performance of serverless workflows in datacenters while also characterizing carbon footprint and water use for supporting serverless computing for the first time, including the overheads from manufacturing, operation, transportation, water-use, and end-of-life decommissioning; 2) Encapsulation layer enhancements will be developed to address some of the biggest performance bottlenecks with serverless computing, such as high startup latency, low performance storage, and fault tolerance; while simultaneously minimizing operational and embodied carbon footprint associated with serverless computing; and 3) Orchestration layer enhancements will be devised based on hybrid evolutionary-learning and multi-agent reinforcement learning to minimize the environmental impact of serverless computing while meeting performance goals across geographically-distributed datacenter platforms.This project is aligned with the goals of the National Discovery Cloud for Climate (NDC-C) program as it involves cloud-based data modeling, analysis, and optimization for a variety of emerging serverless computing applications, including weather predictions from multi-modal data and climate modeling, that promise to advance climate-related research. The project also aims to realize fundamentally more sustainable cloud computing infrastructures that can support large-scale climate science and engineering workloads in the scope of the NDC-C program while reducing the damaging environmental impacts of cloud computing datacenters that execute them. The emphasis on characterizing and co-optimizing the performance and environmental impacts of serverless computing will improve the proliferation of low-cost cloud computing, making it more cost-effective and seamless to integrate into computing-driven services that can enrich our everyday lives. Workforce development is another important broader impact of this project, with high school students, undergraduate and graduate students being trained in the multi-disciplinary domains of high-performance computing, optimization theory, and environmental sustainability. Close collaboration with industrial partners will also ensure timely dissemination and integration of research outcomes into real-world sustainable climate-friendly computing initiatives.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.