Collaborative Research: Software Canaries

合作研究：软件金丝雀

• 批准号: 1255857
• 负责人: Rakesh Kumar
• 金额: $ 9万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1255857&HistoricalAwards=false
• 关键词: Collaborative; Research; Software; Canaries

As transistors get smaller, they become increasingly susceptible to variations in their timing characteristics. One way to deal with possible variations is to assume worst-case characteristics during hardware design. Unfortunately, the power and performance costs of worst-case design are becoming prohibitive. Consequently, processor designers have sought more aggressive design styles that permit better-than-worst-case operation. One such approach uses "canary circuits" that indicate when a processor is on the verge of unsafe operation due to variations. This research investigates "software canaries" - software routines that exercise the most susceptible circuits of a processor to determine an aggressive safe operating point. Software canaries enable all the benefits of hardware canary circuits, without the corresponding hardware overhead. More importantly, they may provide additional benefits as they can track aging and temperature - variations that may be indistinguishable to hardware canary circuits. Furthermore, unlike hardware canary circuits, they allow identifying the most aggressive operating point on a per application basis. This research focuses on exploring the benefits of software canaries, developing use cases, developing techniques for building software canaries for different microarchitectures, and developing microarchitecture and system support needed to support software-canary-based execution.The broader impact of the research lies in enabling computing systems with significantly lower energy consumption by selecting aggressive operating points. Other specific impacts include development of open source tools that may be used for further work by other research groups, and a greater discussion of variations and energy efficiency in graduate and undergraduate coursework.

随着晶体管变得越来越小，它们变得越来越容易受到其时序特性变化的影响。处理可能的变化的一种方法是在硬件设计期间假设最坏情况的特性。不幸的是，最坏情况设计的功耗和性能成本越来越高。因此，处理器设计者已经寻求允许比最坏情况更好的操作的更积极的设计风格。一种这样的方法使用“金丝雀电路”，其指示处理器何时由于变化而处于不安全操作的边缘。本研究调查“软件金丝雀”-软件例程，行使最敏感的电路的处理器，以确定一个积极的安全工作点。软件金丝雀实现了硬件金丝雀电路的所有优点，而没有相应的硬件开销。更重要的是，它们可以提供额外的好处，因为它们可以跟踪硬件金丝雀电路可能无法区分的老化和温度变化。此外，与硬件金丝雀电路不同，它们允许在每个应用程序的基础上识别最积极的工作点。该研究的重点是探索软件金丝雀的好处，开发用例，开发技术，为不同的微架构构建软件金丝雀，并开发所需的微架构和系统支持，以支持基于软件金丝雀的execution.The更广泛的影响，研究在于使计算系统具有显着降低能耗通过选择积极的操作点。其他具体影响包括开发可用于其他研究小组进一步工作的开源工具，以及在研究生和本科生课程中更多地讨论变化和能源效率。