XPS: Full: FP: Collaborative Research: Sphinx: Combining Data and Instruction Level Parallelism through Demand Driven Execution of Imperative Programs

XPS：完整：FP：协作研究：Sphinx：通过命令式程序的需求驱动执行将数据和指令级并行性相结合

• 批准号: 1533846
• 负责人: David Whalley
• 金额: $ 31.5万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1533846&HistoricalAwards=false
• 关键词: XPS; Full; FP; Collaborative; Research

Title: XPS: Full: FP: Collaborative Research: Sphinx: Combining Data and Instruction Level Parallelism through Demand Driven Execution of Imperative ProgramsIt has become increasingly difficult to improve the performance of processors so that they can meet the demands of existing and emerging workloads. Recent emphasis has been towards enhancing the performance through the use of multi-core processors and Graphics Processing Units. However, these processors remain difficult to program and inflexible to adapt to dynamic changes in the available parallelism in a given program. Although the computer architecture and programming language community continues to innovate and make important gains towards better programmability and better designs, it remains that parallel programming is inherently costly and error prone, and automatic parallelization of programs is not always feasible or effective. The intellectual merits of this project are the development of a new program execution paradigm and the establishment of critical compiler and micro-architecture mechanisms so that we can design processors that can be easily programmed using existing programming languages and at the same time surpass the performance of existing parallel computers. The project's broader significance and importance are wide-spread: the deployment of such processors will push the limits of computation in every field of science and commerce.The execution paradigm under consideration is a previously unexplored execution model, the demand-driven execution of imperative programs (DDE). The DDE paradigm rests on a solid theoretical framework and promises to efficiently deliver very high-levels of fine-grain parallelism. This parallelism is extracted from a program written in an imperative language such as C, and it is realized by means of an effective compiler-architecture collaboration mechanism using a common, single-assignment form for the program representation. DDE processors can extract instruction-level parallelism much more efficiently than existing superscalar processors as the paradigm does not require dynamic dependency checking. Such processors can fetch, buffer, and execute many more instructions in parallel than current superscalar processors. Owing to its dependence-driven instruction fetching and execution, the paradigm leads to extremely scalable designs, as the communication is naturally localized and synchronization is inherent in the model. Conventional thread-level parallelism (TLP) is orthogonal to DDE, and thus DDE designs can exploit both ILP and TLP. DDE architectures thus represent promising building blocks for extreme-scale machines.

标题：XPS：FULT：FP：协作研究：狮身人面像：通过需求驱动的命令式程序的执行来结合数据和指令级别的并行性，变得越来越难以提高处理器的性能，以便它们可以满足现有和新兴工作量的需求。最近的重点是通过使用多核处理器和图形处理单元来提高性能。但是，这些处理器仍然难以编程，并且不灵活地适应给定程序中可用的并行性的动态变化。尽管计算机架构和编程语言社区继续创新并为更好的可编程性和更好的设计带来重要的收益，但并行编程本质上是固有的，并且容易出错，并且程序的自动并行化并不总是可行的或有效的。该项目的智力优点是开发新的程序执行范式，以及建立关键编译器和微观构造机制，以便我们可以设计可以使用现有编程语言轻松编程的处理器，同时超过现有平行计算机的性能。该项目的更广泛的意义和重要性是广泛的：此类处理器的部署将在科学和商业领域的每个领域中推动计算限制。执行范式正在考虑的是先前未探索的执行模型，即需求驱动的执行命令计划（DDE）。 DDE范式基于一个坚实的理论框架，并有望有效地提供非常高级的细粒并行性。该并行性是从用命令式语言（例如C）编写的程序中提取的，它是通过使用共同的单个分配形式来实现程序表示形式的有效编译器架构协作机制来实现的。 DDE处理器可以比现有SuperScalar处理器更有效地提取指令级并行性，因为范式不需要动态依赖性检查。此类处理器可以比当前的超级加工机并并行获取，缓冲和执行更多的指令。由于其依赖驱动的指令获取和执行，范式会导致极其可扩展的设计，因为通信是自然局部的，并且同步在模型中是固有的。常规的线程级并行性（TLP）与DDE是正交的，因此DDE设计可以利用ILP和TLP。因此，DDE体系结构代表了极端规模机器的有希望的构建块。

项目成果

Improving Energy Efficiency by Memoizing Data Access Information

• DOI: 10.1109/islped.2019.8824951
• 发表时间: 2019-07
• 期刊: 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)
• 作者: Michael Stokes;Ryan Baird;Zhaoxiang Jin;D. Whalley;Soner Önder

The Domestic Computer Science Graduate Students Are There, We Just Need to Recruit Them

国内计算机研究生已经有了，我们只需要招就可以了

• DOI: 10.1145/3448249
• 发表时间: 2021
• 期刊: Communications of the ACM
• 影响因子: 22.7
• 作者: Whalley, David;Yuan, Xin;Liu, Xiuwen
• 通讯作者: Liu, Xiuwen

Decreasing the Miss Rate and Eliminating the Performance Penalty of a Data Filter Cache

降低丢失率并消除数据过滤器缓存的性能损失

• 发表时间: 2021
• 期刊: ACM transactions on architecture and code optimization
• 影响因子: 1.6
• 作者: Stokes, Michael;Whalley, David;Onder, Soner
• 通讯作者: Onder, Soner