EAGER:Stochastic Thermodynamics of Distributed Computation

EAGER:分布式计算的随机热力学

• 批准号: 2221345
• 负责人: David Wolpert
• 金额: $ 29.99万
• 依托单位: Santa Fe Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221345&HistoricalAwards=false
• 关键词: EAGER; Stochastic; Thermodynamics; Distributed; Computation

Society is witnessing explosive growth in the deployment of distributed computational systems, especially in networked system architectures, and their accompanying software protocols. One of the main performance challenges in these systems is poor energy efficiency; they dissipate too much heat. Similarly, a major goal of chip design has been to minimize the heat dissipation of individual nanoscale components and/or to apply phenomenological laws to reduce the heat dissipation of the global architecture. However, theoretical computer science research has focused on the design of algorithms that minimize time and memory costs per computation. To date there has been little use of first principles of physics to analyze how the global structural organization of computers affects their heat dissipation. Thus, the goal of the proposed research is to develop an understanding of how the physical features of a distributed computational system (e.g., communication rates, network topology, and heterogeneity) affect its performance, specifically the relationship between its heat dissipation, space and time resource costs, robustness, speed, and computational power. Besides the technical work the project will also undertake: (i) outreach via new coursework in the context of this project, (ii) support of mentoring students/postdocs thereby increasing the pool of technically trained workforce, and (iii) public and media outreach for increasing public understanding of science.This exploratory project will aim to start to fill this gap in scientific understanding by exploiting the recently developed tools of stochastic thermodynamics. The PI will use investigate how the following features of the global physical architecture of a computer affect its cost: (1) communication rate and accuracy of information transmission between subsystems, (2) characteristics of the network topology of the architecture, particularly hierarchy and modularity, (3) heterogeneity among the individual subsystems. Specifically, the project will investigate how these design features affect trade-offs between time, memory, and heat costs; desired computational capabilities; and robustness against environmental fluctuations or faulty subsystems. The investigations will involve computer simulations, which will help reveal patterns and trends in these trade-offs, as well as theoretical analyses, which will help uncover the mathematical basis of the observed pattern.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.

社会正在见证分布式计算系统的部署的爆炸性增长，特别是在网络系统架构及其随附的软件协议中。这些系统的主要性能挑战之一是能源效率低。它们散发太多的热量。同样，芯片设计的一个主要目标是最大限度地减少单个纳米级组件的散热和/或应用现象学定律来减少整体架构的散热。然而，理论计算机科学研究主要集中在算法设计上，以最大限度地减少每次计算的时间和内存成本。迄今为止，很少使用物理学第一原理来分析计算机的整体结构组织如何影响其散热。因此，本研究的目标是了解分布式计算系统的物理特征（例如通信速率、网络拓扑和异构性）如何影响其性能，特别是其散热、空间和时间资源成本、鲁棒性、速度和计算能力之间的关系。除了技术工作外，该项目还将开展：（i）在该项目的背景下通过新课程进行推广，（ii）支持指导学生/博士后，从而增加受过技术培训的劳动力队伍，以及（iii）公众和媒体推广，以提高公众对科学的理解。这个探索性项目旨在通过利用最近开发的随机热力学工具来填补科学理解方面的空白。 PI 将研究计算机全局物理架构的以下特征如何影响其成本：(1) 子系统之间的通信速率和信息传输的准确性，(2) 架构的网络拓扑特征，特别是层次结构和模块化，(3) 各个子系统之间的异构性。具体来说，该项目将研究这些设计特征如何影响时间、内存和热量成本之间的权衡；所需的计算能力；以及针对环境波动或故障子系统的鲁棒性。调查将涉及计算机模拟，这将有助于揭示这些权衡的模式和趋势，以及理论分析，这将有助于揭示观察到的模式的数学基础。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。