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The Design and Implementation of LilyTask in Shared Memory

机译:共享内存中LilyTask的设计与实现

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摘要

Constructing high performance computing system and providing easy-to-use programming model for users are two main parts of parallel computing, but the latter has been in a sorry state for a long time. LilyTask programming model is based on tasks which can be easily mapped to the decomposition of computation. Without explict synchronization and mutual exclusion, users will concentrate on the inherent parallelism in a problem instead of lock/unlock programming techniques. Most existing implementations of the task pool, a flexible data structure for task parallel. Jack basic representation of relations among tasks. LilyTask introduces task group and task relation to help users easily map subproblems to tasks. The kernel of LilyTask system, a distributed task pool, automatically exploits potential parallelism among tasks at runtime. With runtime task assignment and task stealing, LilyTask system achieves dynamic load balancing. Our performance evaluation shows that LilyTask system with task pool outperforms sequential programs and BSPlib in solving both regular and irregular problems.
机译:构建高性能计算系统并为用户提供易于使用的编程模型是并行计算的两个主要部分,但是并行计算长期处于令人遗憾的状态。 LilyTask编程模型基于可以轻松映射到计算分解的任务。如果没有明确的同步和互斥,用户将专注于问题中固有的并行性,而不是锁定/解锁编程技术。任务池的大多数现有实现,一种用于任务并行的灵活数据结构。杰克基本表示任务之间的关系。 LilyTask引入了任务组和任务关系,以帮助用户轻松地将子问题映射到任务。 LilyTask系统的内核(一个分布式任务池)在运行时自动利用任务之间的潜在并行性。通过运行时任务分配和任务窃取,LilyTask系统实现了动态负载平衡。我们的性能评估表明,在解决常规和非常规问题时,具有任务池的LilyTask系统优于顺序程序和BSPlib。

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