SHF:SMALL:Pushing the Limits of Transparent Specialization

SHF：SMALL：突破透明专业化的极限

• 批准号: 1618234
• 负责人: Karthikeyan Sankaralingam
• 金额: $ 40万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-15 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618234&HistoricalAwards=false
• 关键词: SHF; SMALL; Pushing; Limits; Transparent

For many years, microprocessors took advantage of how Moore's Law (smaller successive generations of transistors) and the fact that they consumed less power to build better performing chips. Due to fundamental limitations it is no longer possible to cost-effectively make smaller transistors or significantly reduce their power consumption. This research project develops future microprocessors that are organized differently and more effectively using limited transistors to provide better chips. The main idea this research project explores is a way to tailor certain parts of a chip to certain tasks, thereby making each component very small and power-efficient. A program's execution moves from one such component to another, each being tuned for that phase of the program. The curriculum enhancements will provide students significant experience in designing hardware. This research will help steer microprocessor designs in novel ways to sustain performance improvements and help sustain information technology leadership.The specific approach taken by this research is a unique and novel form of specialization called: behavior specialized acceleration (BSA). This is a paradigm that exploits program behaviors and their inter-relationship to hardware microarchitecture. It is workload domain agnostic. Specializing for program behaviors is advantageous both because fewer accelerators can target a large variety of codes, and because these behaviors are typically analyzable by a compiler, meaning their use can be transparent from programmers. In particular the research will develop a chip organization that includes an ExoCore fabric and an Endocore fabric. The ExoCore fabric is a processor core organization that uses behavior specialization to transparently improve the execution of general-purpose workloads. The Endocore fabric employs different behavior specializations and attempts to support computationally-intensive domains using a single hardware architecture and well-defined software interfaces. This research develops mechanisms, an FPGA prototype of a family of ExoCore and EndoCore designs, their accompanying compiler, and detailed performance evaluation.

多年来，微处理器利用了摩尔法律（较小的后代晶体管）的优势，以及他们消耗了更少的功率来建造更好的芯片。由于基本的限制，不再有可能使较小的晶体管或显着降低其功耗。该研究项目开发了未来的微处理器，它们使用有限的晶体管来提供不同，更有效地组织起来，以提供更好的芯片。该研究项目探讨的主要思想是将芯片的某些部分定制到某些任务的一种方法，从而使每个组件都非常小且有效。程序的执行将从一个这样的组件移动到另一个组件，每个组件都为程序的那个阶段进行了调整。课程增强功能将为学生设计硬件的丰富经验。 这项研究将有助于以新颖的方式进行微处理器设计，以维持绩效的改进并帮助维持信息技术的领导力。该研究采用的特定方法是一种独特而新颖的专业形式，称为：行为专业加速度（BSA）。 这是一个范式，可以利用程序行为及其与硬件微体系结构的相互关系。这是工作负载域不可知论。 专门针对程序行为是有利的，因为更少的加速器可以针对多种代码，并且由于这些行为通常可以通过编译器来分析，这意味着它们的使用可以从程序员那里透明。 特别是，该研究将开发一个芯片组织，其中包括exocore织物和一个内糖织物。 Exocore Fabric是一个处理器核心组织，它使用行为专业化来透明地改善通用工作负载的执行。 Endocore Fabric采用不同的行为专业化，并尝试使用单个硬件体系结构和定义明确的软件接口来支持计算密集型域。 这项研究开发了机制，是exocore和内2OCORE设计家族的FPGA原型，其随附的编译器以及详细的绩效评估。