DESC: Type I: Dynamic Optimization for Leaps in Sustainability-Centric Computing System Design

计算系统的制造、运行和处置对环境的影响越来越大。传统上，计算系统的设计是为了最大限度地提高能效和工作绩效，而温室气体排放和电子垃圾等要素则继续呈上升趋势。这些因素取决于计算系统的基本动态，而对时间敏感的反应有可能解决这些问题。该项目使用动态系统优化来解决计算系统的可持续性问题，明确将重点放在设计未来计算系统的关键可持续性指标上。重点是推动对可持续计算系统的科学理解，并影响未来的关键结构，如数据中心。该项目不仅为计算领域提供支持，而且在设计和控制领域也提供了进步。该项目的成果还通过广泛的多媒体资源开发和学生培训来支持科学界和公众的教育。第一个目标是改进和重新制定可持续计算系统的模型，以便在优化中整合，办法是开发一种方法，将数据驱动的替代模型转换为动态分析友好的格式。第二个目标是理解和量化可持续性度量的不同表示对优化问题解决方案可行性的影响。这是通过对可持续发展指标进行分类以自动生成可解优化问题来实现的。第三个目标是使用一个新的框架来开发和评估以可持续发展为中心的计算系统的动态系统优化能力。验证通过数值和实验案例研究相结合的方式进行，从服务器冷却到数据中心设计。通过动态系统优化研究计算系统的潜在贡献是可持续发展指标的大幅、离散跳跃，如排放、废热和电子废物的减少。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。

The manufacturing, operation, and disposal of computing systems are increasingly impacting the environment. Traditionally, computing systems are designed to maximize energy efficiency and job performance, while elements such as greenhouse gas emissions and electronic waste continue to trend upward. These factors are dependent on the underlying dynamics of the computing systems, and time-sensitive reactions have the potential to address these issues. This project tackles the sustainability of computing systems using dynamic system optimization, setting an explicit focus on critical sustainability metrics for designing future computing systems. An emphasis is placed on pushing forward the scientific understanding of sustainable computing systems, and to impact future critical structures such as datacenters. This project serves to support not only the computing field, but also provides advancements in the design and controls fields. The outcomes of the project also support education of scientific communities and the public alike through expansive multimedia resource development and student training.Three aims are defined for this research. The first aim is to improve and reformulate models of sustainable computing systems for integration within optimization, addressed by development of a methodology to convert data-driven surrogate models into dynamic analysis-friendly formats. The second aim is to understand and quantify the impact different representations of sustainability metrics have on optimization problem solution feasibility. This is pursued through categorization of sustainability metrics for automatic generation of solvable optimization problems. The third aim is to develop and evaluate the capabilities of dynamic system optimization for sustainability-centric computing systems, using a novel framework. Validation is performed through a combination of numerical and experimental case studies, ranging from server cooling to datacenter design. The potential contributions of studying computing systems through dynamic system optimization are large, discrete jumps in sustainability metrics, such as reductions in emissions, waste heat, and electronic waste.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.