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，微处理器利用摩尔定律（连续一代更小的晶体管）和它们消耗更少的能量来制造性能更好的芯片。由于基本限制，不再可能经济有效地制造更小的晶体管或显着降低其功耗。这个研究项目开发了未来的微处理器，这些微处理器的组织方式不同，使用有限的晶体管更有效地提供更好的芯片。这个研究项目的主要思想是探索一种方法，使芯片的某些部分适合某些任务，从而使每个组件非常小且节能。程序的执行从一个这样的组件移动到另一个组件，每个组件都针对程序的该阶段进行调优。课程的改进将为学生提供设计硬件的重要经验。这项研究将有助于以新颖的方式引导微处理器设计，以维持性能改进，并有助于保持信息技术的领先地位。本研究采取的具体方法是一种独特而新颖的专业化形式：行为专业化加速（BSA）。这是一种利用程序行为及其与硬件微体系结构的相互关系的范例。它与工作负载域无关。专门化程序行为是有利的，因为较少的加速器可以针对大量不同的代码，而且这些行为通常可以由编译器分析，这意味着它们的使用对程序员来说是透明的。特别是，该研究将开发一种包括ExoCore结构和Endocore结构的芯片组织。ExoCore结构是一个处理器核心组织，它使用行为专门化来透明地改进通用工作负载的执行。Endocore结构采用不同的行为专门化，并尝试使用单一硬件体系结构和定义良好的软件接口来支持计算密集型领域。本研究开发了机制，ExoCore和EndoCore系列设计的FPGA原型，其配套的编译器，以及详细的性能评估。