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Concurrent Collections
Scientific Programming Pub Date : 2010 , DOI: 10.3233/spr-2011-0305
Zoran Budimlić, Michael Burke, Vincent Cavé, Kathleen Knobe, Geoff Lowney, Ryan Newton, Jens Palsberg, David Peixotto, Vivek Sarkar, Frank Schlimbach, Sağnak Taşırlar

We introduce the Concurrent Collections (CnC) programming model. CnC supports flexible combinations of task and data parallelism while retaining determinism. CnC is implicitly parallel, with the user providing high-level operations along with semantic ordering constraints that together form a CnC graph. We formally describe the execution semantics of CnC and prove that the model guarantees deterministic computation. We evaluate the performance of CnC implementations on several applications and show that CnC offers performance and scalability equivalent to or better than that offered by lower-level parallel programming models.

中文翻译:

并发集合

我们介绍了并发集合(CnC)编程模型。CnC支持任务和数据并行性的灵活组合,同时保留确定性。CnC是隐式并行的,用户可以提供高级操作以及语义排序约束,这些约束一起构成了CnC图。我们正式描述了CnC的执行语义,并证明该模型保证了确定性计算。我们评估了CnC在多个应用程序上的实现性能,并表明CnC提供的性能和可伸缩性与低级并行编程模型所提供的性能和可伸缩性相同或更好。
更新日期:2020-09-25
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