SHF: Small: Scaling the Compute Efficiency of General-Purpose Processors

SHF：小型：扩展通用处理器的计算效率

• 批准号: 1217917
• 负责人: Scott Mahlke
• 金额: $ 45万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1217917&HistoricalAwards=false
• 关键词: SHF; Small; Scaling; Compute; Efficiency

The growth of the microprocessor industry has led to progress in diversified computing applications, such as health care, education, security, and communications. However, energy consumption has emerged as a barrier to the continued success of the American semiconductor industry. The inability to scale chip voltages at the historic rate has created a difficult design dilemma referred to as dark silicon: more transistors can fit on a chip, but a growing fraction will not be able to be used due to power dissipation limits. To scale performance in this landscape, fundamental increases in the computational efficiency of processors is required to get much more performance for much less energy. To scale computational efficiency, this work develops an architectural approach referred to as Composite Cores. The proposed architecture brings the notion of heterogeneity from between different cores in a processor to within a core. Each composite core will consist of several energy efficient engines that have been customized to particular execution scenarios found in general-purpose applications. A dynamic management system will perform fine-grain mapping of application segments to the most efficient engine. Hardware mechanisms to ensure delay-free migration of program state provide smooth transitions from engine to engine. By dynamically partitioning an application across a set of customized engines, a large portion of the efficiency gains afforded by hardware accelerators on regular codes can be realized on general-purpose applications. The broader impact of this work is that green computing is recognized as one of the most important challenges in the semiconductor industry and more broadly in Computer Science. Composite cores enable general-purpose processors to reach new levels of energy efficiency while not sacrificing the ability to execute arbitrary code.

微处理器产业的发展带动了多种计算应用的发展，如医疗保健、教育、安全和通信。然而，能源消耗已经成为美国半导体工业持续成功的障碍。无法按历史速度缩放芯片电压已经造成了一个被称为暗硅的困难设计困境：芯片上可以容纳更多的晶体管，但由于功耗限制，越来越多的晶体管将无法使用。为了在这种情况下扩展性能，需要从根本上提高处理器的计算效率，以更少的能量获得更高的性能。为了提高计算效率，这项工作开发了一种称为复合核心的架构方法。所提出的体系结构将异构的概念从处理器的不同核心之间引入到核心内部。每个复合核心将由几个节能引擎组成，这些引擎针对通用应用程序中的特定执行场景进行了定制。动态管理系统将执行应用程序段到最有效引擎的细粒度映射。确保程序状态无延迟迁移的硬件机制提供了从引擎到引擎的平滑转换。通过跨一组定制引擎动态划分应用程序，可以在通用应用程序上实现常规代码上硬件加速器提供的大部分效率增益。这项工作的更广泛的影响是，绿色计算被认为是半导体工业乃至更广泛的计算机科学中最重要的挑战之一。复合核使通用处理器能够在不牺牲执行任意代码的能力的情况下达到新的能效水平。