CSR: Medium: Understanding and Automatically Adjusting Performance Sensitive Software Configurations

CSR：中：了解并自动调整性能敏感的软件配置

• 批准号: 1764039
• 负责人: Henry Hoffmann
• 金额: $ 114.91万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1764039&HistoricalAwards=false
• 关键词: CSR; Medium; Understanding; Automatically; Adjusting

Every day, people interact with complex software systems on their mobile devices and in the cloud. Experts develop this software, but they cannot account for all possible uses, so they make the software configurable using redefinable parameters. Most of these parameters affect software's performance. These performance-related configuration parameters are growing exponentially. Unfortunately, so is the difficulty of setting them. Performance-related misconfigurations are a leading cause of system failures (e.g., web services crashing) and lag (e.g., delayed response to user requests). This project will develop AutoConf to automatically set performance-related configuration parameters and eliminate these sources of failure in critical software infrastructure.To better understand and manage performance-related configurations, AutoConf has four major research objectives. The first is studying existing configuration parameters to understand why and when they lead to failures. The second is designing a new interface where users set high-level goals in terms of desired performance rather than setting specific parameter values. The third is developing techniques that automatically and dynamically configure software to meet these goals. The final objective is constructing tools that ensure the interface's proper usage to produce the desired behavior.If successful, AutoConf will change the way users deploy software. Instead of setting 100s of configuration parameters, they will state their goals. AutoConf will automatically adjust performance-related configurations to ensure the goals are met, resulting in faster and more robust software deployment. Additionally, the AutoConf project will create many research opportunities that will be used to broaden participation in computer science.Documentation and software releases will be posted at http://autoconf.cs.uchicago.edu/.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.

人们每天都会在移动设备和云端与复杂的软件系统进行交互。 专家开发了该软件，但他们无法考虑所有可能的用途，因此他们使用可重新定义的参数来配置该软件。大多数这些参数都会影响软件的性能。这些与性能相关的配置参数呈指数级增长。 不幸的是，设置它们的难度也很大。 与性能相关的错误配置是系统故障（例如，Web 服务崩溃）和滞后（例如，对用户请求的响应延迟）的主要原因。 该项目将开发 AutoConf，以自动设置与性能相关的配置参数，并消除关键软件基础设施中的这些故障源。为了更好地理解和管理与性能相关的配置，AutoConf 有四个主要研究目标。 第一个是研究现有的配置参数，以了解它们导致故障的原因和时间。 第二个是设计一个新的界面，用户可以根据所需的性能设置高级目标，而不是设置特定的参数值。 第三是开发自动、动态配置软件以满足这些目标的技术。 最终目标是构建确保界面正确使用以产生所需行为的工具。如果成功，AutoConf 将改变用户部署软件的方式。 他们不会设置数百个配置参数，而是会陈述他们的目标。 AutoConf 将自动调整与性能相关的配置，以确保实现目标，从而实现更快、更稳健的软件部署。此外，AutoConf 项目将创造许多研究机会，用于扩大计算机科学领域的参与。文档和软件版本将发布在 http://autoconf.cs.uchicago.edu/ 上。该奖项反映了 NSF 的法定使命，并已通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods

因果推理的动力系统理论及其在综合控制方法中的应用

• 发表时间: 2020
• 期刊: Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics
• 作者: Ding, Yi;Toulis, Panos
• 通讯作者: Toulis, Panos

GOAL: Supporting General and Dynamic Adaptation in Computing Systems

• DOI: 10.1145/3563835.3567655
• 发表时间: 2022-11
• 期刊: Proceedings of the 2022 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software
• 作者: Ahsan Pervaiz;Yao-Hsiang Yang;Adam Duracz;F. Bartha;R. Sai;Connor Imes;Robert Cartwright;K. Palem;Shan Lu;Henry Hoffmann

Generalizable and interpretable learning for configuration extrapolation

• DOI: 10.1145/3468264.3468603
• 发表时间: 2021-08
• 期刊: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
• 作者: Yi Ding;Ahsan Pervaiz;Michael Carbin;H. Hoffmann

Generative and Multi-phase Learning for Computer Systems Optimization

• DOI: 10.1145/3307650.3326633
• 发表时间: 2019-06
• 期刊: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA)
• 作者: Yi Ding;Nikita Mishra;H. Hoffmann

Cancellation in Systems: An Empirical Study of Task Cancellation Patterns and Failures

系统中的取消：任务取消模式和失败的实证研究

• 发表时间: 2022
• 期刊: Proceedings of the 16th USENIX Symposium on Operating Systems
• 作者: Sethi, Utsav;Pan, Haochen;Lu, Shan;Musuvathi, Madanlal;Nath, Suman
• 通讯作者: Nath, Suman