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: 0964520
• 负责人: Vivek Sarkar
• 金额: $ 51.35万
• 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: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0964520&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示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不提供隔离和局部性的第一类抽象。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上的计算。目前的项目部分桥梁之间的差距这两种风格的并行通过合唱团，一个新的编程模型，并行计算的非结构化，不断变化的共享内存数据结构。Chorus的关键抽象是一个对象组装：堆中的一个局部的、隔离的区域，配备了一个控制线程。程序集是否可以强制修改自身、与其他程序集合并以及拆分为更小的程序集？通过对程序集的这些操作，Chorus捕获了不可预测的、动态的并行性变化。这使得Chorus成为许多不规则数据并行应用程序的理想编程模型（例如，网格化、集群化），其在典型执行中表现出细粒度的数据并行性，但在最坏情况下没有并行性，并且其并行化仍然是开放且困难的挑战。该项目的预期成果包括对Chorus语义基础的新见解，以及将Chorus与异步任务创建、定向同步和局部性的现有抽象相集成的新语言结构。在系统构建端，该项目将把Chorus与Habanero Java并行编程语言集成，并为结果语言实现编译器和运行时。该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。