Concurrent Collections

Concurrent Collections
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并发集合

DOI：
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发表时间：
2010
期刊：
Scientific Programming
影响因子：
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通讯作者：
Sagnak Tasirlar
Sagnak Tasirlar
中科院分区：
计算机科学4区
文献类型：
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作者：
Zoran Budimlic;M. Burke;Vincent Cavé;K. Knobe;Geoff N. Lowney;Ryan Newton;J. Palsberg;David M. Peixotto;Vivek Sarkar;F. Schlimbach;Sagnak Tasirlar

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我们介绍了并发收集（CnC）编程模型。CnC支持任务和数据并行性的灵活组合，同时保持确定性。CnC是隐式并行的，用户提供高级操作沿着语义排序约束，这些约束一起形成CnC图。 我们正式描述的执行语义的CnC和证明该模型保证确定性计算。我们评估的性能CnC实现几个应用程序，并表明，CnC提供的性能和可扩展性相当于或优于较低级别的并行编程模型所提供的。
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.