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.

在b谷歌和Facebook等公司的现代软件开发实践中，编译（将源程序转换为可执行程序的过程）已经成为一个重要的、耗时的、资源密集型的过程。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、高性能的、高度并行的硬件，因此软件开发受到仍然缓慢的编译过程的阻碍。这个项目旨在开发新技术来加快编译过程。智力上的优点是设计新的编译器内部、算法和调度器，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，编译过程实际上是现代软件和现代生活的每一个方面的基础：加速编译使任何类型的软件都能更快地开发出来，为用户提供新的特性，并更快地消除潜在的灾难性错误。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，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，采用密集的表示。我们正在设计一些技术，允许程序员在高层次上编写编译器传递，同时自动将它们转换为使用密集表示。其次，pi正在设计新的算法来优化编译程序。这些是内部编译器算法的转换，以提高局部性（通过组合在程序的相似部分上操作的传递）和增强并行性（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执行现代构建系统的并行和分布式硬件上。

项目成果

Priority Scheduling for Interactive Applications

交互式应用程序的优先级调度

• DOI: 10.1145/3350755.3400236
• 发表时间: 2020
• 期刊: Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures
• 作者: Singer, Kyle;Goldstein, Noah;Muller, Stefan K.;Agrawal, Kunal;Lee, I-Ting Angelina;Acar, Umut A.
• 通讯作者: Acar, Umut A.

Tight Bounds for Parallel Paging and Green Paging

• DOI: 10.1137/1.9781611976465.180
• 发表时间: 2021-01
• 作者: Kunal Agrawal;M. A. Bender;Rathish Das;William Kuszmaul;E. Peserico;Michele Scquizzato

An Efficient Scheduler for Task-Parallel Interactive Applications

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

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
• 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.

Provably Good Randomized Strategies for Data Placement in Distributed Key-Value Stores

• DOI: 10.1145/3572848.3577501
• 发表时间: 2023-02
• 期刊: Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
• 作者: Zhe Wang;Jinhao Zhao;Kunal Agrawal;Heyu Liu;Meng Xu;Jing Li