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Evaluation of an MPI-Based Implementation of the Tascell Task-Parallel Language on Massively Parallel Systems

机译:大规模并行系统上基于MPI的Tascell任务并行语言实现的评估

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Tascell is a task parallel language that supports distributed memory environments. The conventional implementation of Tascell realizes inter-node communication with TCP/IP communication via Tascell servers. This implementation is suitable for dynamic addition of computation nodes and wide-area distributed environments. On the other hand, in supercomputer environments, TCP/IP may not be available for inter-node communication and there may be no appropriate places for deploying Tascell servers. In this study, we have developed a server-less implementation of Tascell that realizes inter-node communication with MPI communication in order to evaluate its performance on massively parallel systems. It performs well on four Xeon Phi coprocessors (with 456 workers) and the K computer, for instance, our 19-queens solver achieves a 4615-fold speedup relative to a serial implementation with 7168 workers on the K computer. Our server-less implementation realizes deadlock freedom, although it only requires the two-sided communication paradigm and the MPI_THREAD_FUNNELED support level. On Xeon Phi coprocessors, we compare our implementation with other implementations that employ TCP/IP or the MPI_THREAD_MULTIPLE support level.
机译:Tascell是一种任务并行语言,支持分布式内存环境。 Tascell的常规实现通过Tascell服务器与TCP / IP通信实现节点间通信。此实现适用于动态添加计算节点和广域分布式环境。另一方面,在超级计算机环境中,TCP / IP可能无法用于节点间通信,并且可能没有适当的位置来部署Tascell服务器。在这项研究中,我们开发了Tascell的无服务器实现,该实现通过MPI通信实现节点间通信,以便评估其在大规模并行系统上的性能。例如,它在四个Xeon Phi协处理器(有456名工作人员)和K计算机上表现良好,例如,相对于K计算机上有7168个工作人员的串行实施,我们的19皇后解算器实现了4615倍的加速。我们的无服务器实现实现了死锁自由,尽管它只需要双向通信范例和MPI_THREAD_FUNNELED支持级别。在至强融核协处理器上,我们将我们的实现与采用TCP / IP或MPI_THREAD_MULTIPLE支持级别的其他实现进行比较。

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