SHF: Small: Optimizing Compiler and Runtime for Concurrency-Oriented Execution Model

SHF：小型：优化面向并发的执行模型的编译器和运行时

• 批准号: 1421505
• 负责人: Zheng Zhang
• 金额: $ 37.81万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421505&HistoricalAwards=false
• 关键词: SHF; Small; Optimizing; Compiler; Runtime

Title: SHF:Small:Optimizing Compiler and Runtime for Concurrency-Oriented Execution ModelThe "dark silicon" effect, where an increasing fraction of cores will have to be kept powered off (or, "dark"), at every generation of transistor downsizing, has made it difficult to sustain further efficiency gains via the scaling of semiconductor technology. However, the demands of applications and their data on storage and processing capabilities are rapidly growing, thus increasing the gap between the efficiency of the system stack and the needs of modern applications. This research project aims to redesign the system stack based on a novel paradigm that combines throughput-processing architecture and a concurrency-centric compilation framework. The system stack used in this research project consists of architecture specialized for throughput, which trades single-thread instruction level parallelism (ILP) exploitation units for throughput units. The compiler is specialized for concurrency, which minimizes single thread latency by interleaved execution of a tremendous number of concurrent threads.This research project reveals the implications of concurrent execution on throughput processors and how these implications affect compile-time decisions and the corresponding runtime optimization. The intellectual merits are two-fold: 1) it reveals that the existing mainstream CPU compilation techniques are concurrency-oblivious, which leaves both many challenging problems unanswered and many opportunities for performance improvement to be explored, and 2) it tackles these problems by addressing both the resource allocation and instruction/thread scheduling aspects of compile-time decision making, which is where the fundamental difference between the concurrent execution model and the traditional CPU execution model arises. The broader impacts of this project are that the research results will drive innovation in business, education, and computing applications by reinventing the system stack to enhance efficiency and to help achieve the next supercomputing milestone, namely, exascale-computing.

标题：SHF：小：以并发为导向的执行模型“ Dark Silicon”效果，优化编译器和运行时，必须在每一代晶体管缩减尺寸的情况下，必须将越来越多的核心芯的分数保留（或“ Dark”），这使得难以通过半多管技术的缩放来维持进一步的效率。 但是，应用程序的需求及其对存储和处理功能的数据正在迅速增长，从而增加了系统堆栈效率与现代应用程序需求之间的差距。 该研究项目的目的是基于结合吞吐量处理架构和以并发汇编框架的新型范式来重新设计系统堆栈。 该研究项目中使用的系统堆栈由专门用于吞吐量的体系结构组成，该体系结构可用于单线程指令水平并行性（ILP）开发单元用于吞吐量单位。 该编译器专门用于并发，该编译器通过交错执行大量并发线程来最大程度地减少单线延迟。本研究项目揭示了并发执行对吞吐量处理器的含义，以及这些含义如何影响编译时间决策和相应的运行时优化。 The intellectual merits are two-fold: 1) it reveals that the existing mainstream CPU compilation techniques are concurrency-oblivious, which leaves both many challenging problems unanswered and many opportunities for performance improvement to be explored, and 2) it tackles these problems by addressing both the resource allocation and instruction/thread scheduling aspects of compile-time decision making, which is where the fundamental difference between the concurrent execution model and the traditional CPU执行模型出现。该项目的更广泛的影响是，研究结果将通过重新发明系统堆栈以提高效率并帮助实现下一个超级计算的里程碑来推动业务，教育和计算应用程序的创新。