SPX: Collaborative Research: Eat your Wheaties: Multi-Grain Compilers for Parallel Builds at Every Scale

SPX：协作研究：吃你的小麦：用于各种规模并行构建的多粒度编译器

• 批准号: 1725647
• 负责人: Kunal Agrawal
• 金额: $ 20万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1725647&HistoricalAwards=false
• 关键词: SPX; Collaborative; Research; Eat; your

Title: SPX: Collaborative Research: Multi-Grain Compilers for Parallel Builds at Every ScaleModern software development practices at companies such as Google and Facebook have led to compilation -- the process of transforming source programs into executable programs -- becoming a significant, time-consuming, resource-intensive process. Unfortunately, even state of the art compilers and build systems do not do a good job of exploiting emerging, high-performance, highly-parallel hardware, so software development is hampered by the still-slow process of compilation. This project aims to develop new techniques to speed up the process of compilation. The intellectual merits are designing new compiler internals, algorithms, and schedulers to enable compilers to take advantage of modern hardware capabilities. The project's broader significance and importance are that the process of compilation undergirds virtually every aspect of modern software, and hence modern life: speeding up compilation enables any type of software to be developed more quickly, providing new features to users and more quickly squashing potentially catastrophic bugs.The project revolves around three main thrusts. First, the PIs are developing new representations for compiler internals that better fit the memory hierarchy of modern machines, eschewing pointer-based representations for dense representations. We are designing techniques to allow programmers to write their compiler passes at a high level while automatically converting them to use the dense representation. Second, the PIs are designing new algorithms to optimize compiler passes. These are transformations of internal compiler algorithms to promote locality (by combining passes that operate on similar portions of a program) and to enhance parallelism (by eliminating unnecessary synchronization between passes). Finally, the PIs are creating new scheduling techniques to allow the new highly-parallel compiler algorithms to be effectively mapped to the parallel and distributed hardware on which modern build systems execute.

标题：SPX：协作研究：用于各种规模并行构建的多粒度编译器 Google 和 Facebook 等公司的现代软件开发实践已经导致编译（将源程序转换为可执行程序的过程）成为一个重要的、时间性的过程。消耗资源的过程。 不幸的是，即使是最先进的编译器和构建系统也不能很好地利用新兴的高性能、高度并行的硬件，因此仍然缓慢的编译过程阻碍了软件开发。 该项目旨在开发新技术以加快编译过程。智力优势在于设计新的编译器内部结构、算法和调度程序，使编译器能够利用现代硬件功能。该项目更广泛的意义和重要性在于，编译过程几乎支撑着现代软件的各个方面，从而支撑着现代生活：加快编译速度可以使任何类型的软件更快地开发，为用户提供新功能，并更快地消除潜在的灾难性后果。 bug。该项目围绕三个主要目标展开。首先，PI 正在为编译器内部开发新的表示形式，以更好地适应现代机器的内存层次结构，避免基于指针的表示形式而采用密集表示形式。我们正在设计技术，允许程序员在高级别编写编译器通道，同时自动将它们转换为使用密集表示。其次，PI 正在设计新算法来优化编译器通道。这些是内部编译器算法的转换，以促进局部性（通过组合在程序的相似部分上操作的传递）并增强并行性（通过消除传递之间不必要的同步）。最后，PI 正在创建新的调度技术，以允许新的高度并行编译器算法有效地映射到现代构建系统执行的并行和分布式硬件。

项目成果

Efficient Access History for Race Detection

用于种族检测的高效访问历史记录

• 发表时间: 2022-01
• 期刊: Proceedings of the Symposium on Algorithm Engineering and Experiments (ALENEX
• 作者: Xu, Yifan;Zhou, Anchengcheng;Yin, Grace Q.;Agrawal, Kunal;Lee, I;Schardl, Tao B.
• 通讯作者: Schardl, Tao B.

Contention Resolution with Message Deadlines

带有消息截止日期的争用解决方案

• DOI: 10.1145/3350755.3400239
• 发表时间: 2020-01
• 期刊: Contention Resolution with Message Deadlines
• 作者: Agrawal, Kunal;Bender, Michael A.;Fineman, Jeremy T.;Gilbert, Seth;Young, Maxwell
• 通讯作者: Young, Maxwell

How to Manage High-Bandwidth Memory Automatically

如何自动管理高带宽内存

• DOI: 10.1145/3350755.3400233
• 发表时间: 2020-07
• 期刊: Symposium on Parallelism in Algorithms and Architectures
• 作者: Das, Rathish;Agrawal, Kunal;Bender, Michael A.;Berry, Jonathan;Moseley, Benjamin;Phillips, Cynthia A.
• 通讯作者: Phillips, Cynthia A.

An Efficient Scheduler for Task-Parallel Interactive Applications

任务并行交互式应用程序的高效调度程序

• DOI: 10.1145/3558481.3591092
• 发表时间: 2023-06-17
• 期刊: Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures
• 作者: Kyle Singer;Kunal Agrawal;I. Lee
• 通讯作者: I. Lee

Adaptive scheduling of multiprogrammed dynamic-multithreading applications.

多程序动态多线程应用程序的自适应调度。

• 发表时间: 2022-01
• 期刊: Journal of parallel and distributed computing
• 影响因子: 3.8
• 作者: Wang, Zhe;Xu, Chen;Agrawal, Kunal;Li, Jing
• 通讯作者: Li, Jing