SHF: Medium: Collaborative Research: Chorus: Dynamic Isolation in Shared-Memory Parallelism

SHF：媒介：协作研究：Chorus：共享内存并行中的动态隔离

• 批准号: 1242507
• 负责人: Swarat Chaudhuri
• 金额: $ 50.97万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1242507&HistoricalAwards=false
• 关键词: SHF; Medium; Collaborative; Research; Chorus

Expressing parallel computations over complex shared-memory data structures has always been a vexing issue in parallel programming. On one hand, popular task-based programming models do not provide first-class abstractions for isolation and locality. On the other, Actor-based programming naturally captures locality but is unsuitable for computations on large shared data structures. The present project partially bridges the gap between these two styles of parallelism through Chorus, a new programming model for parallel computations over unstructured, continually changing shared-memory data structures. The key abstraction of Chorus is an object assembly: a local, isolated region in the heap equipped with a thread of control. Assemblies can imperatively modify themselves, merge with other assemblies, and split into smaller assemblies?through these operations over assemblies, Chorus captures unpredictable, dynamic changes to parallelism. This makes Chorus an ideal programming model for many irregular data-parallel applications (e.g., meshing, clustering), which exhibit fine-grained data-parallelism in typical executions but no parallelism in the worst case, and whose parallelization remains an open and difficult challenge.The predicted outcomes of the project include new insights into the semantic foundations of Chorus and new language constructs integrating Chorus with existing abstractions for asynchronous task creation, directed synchronization, and locality. On the system-building end, the project will integrate Chorus with the Habanero Java parallel programming language, and implement a compiler and runtime for the resultant language. The performance and programmability of this language will be thoroughly evaluated using benchmarks largely consisting of emerging irregular workloads.

在复杂的共享内存数据结构上表达并行计算一直是并行编程中的一个棘手问题。一方面，流行的基于任务的编程模型没有为隔离和局部性提供一流的抽象。另一方面，基于 Actor 的编程自然地捕获局部性，但不适合大型共享数据结构的计算。目前的项目通过 Chorus 部分弥补了这两种并行方式之间的差距，Chorus 是一种新的编程模型，用于在非结构化、不断变化的共享内存数据结构上进行并行计算。 Chorus 的关键抽象是对象组装：堆中配备控制线程的本地隔离区域。程序集可以命令式地修改自身、与其他程序集合并以及拆分为更小的程序集？通过程序集上的这些操作，Chorus 可以捕获并行性的不可预测的动态变化。这使得 Chorus 成为许多不规则数据并行应用程序（例如网格划分、集群）的理想编程模型，这些应用程序在典型执行中表现出细粒度的数据并行性，但在最坏的情况下没有并行性，并且其并行化仍然是一个开放且困难的挑战该项目的预测结果包括对 Chorus 语义基础的新见解以及将 Chorus 与现有抽象集成以实现异步任务创建、定向同步和局部性的新语言结构。在系统构建方面，该项目将Chorus与Habanero Java并行编程语言集成，并为所得语言实现编译器和运行时。这种语言的性能和可编程性将使用主要由新兴的不规则工作负载组成的基准进行彻底评估。