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Implementing the Open Community Runtime for Shared-Memory and Distributed-Memory Systems

机译:为共享内存和分布式内存系统实现开放社区运行时

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The extreme scale, complexity and performance variability of future high performance computing systems pose many new challenges to parallel programming models and runtime systems. The Open Community Runtime (OCR) is a recent effort for a task-based runtime system for extreme scale parallel systems. We have implemented the OCR specification in a shared-memory environment on top of TBB, providing an alternative to the implementation created by the OCR consortium. We have created an experimental extension that supports parallel accelerators programmed with OpenCL. We also have an implementation that targets distributed-memory systems. Despite being in an early stage of development, our implementations can achieve reasonable performance with some applications. We describe the main aspects of our OCR implementations and report on early experimental results on shared-memory and distributed-memory systems.
机译:未来高性能计算系统的极端规模,复杂性和性能可变性给并行编程模型和运行时系统带来了许多新挑战。开放社区运行时(OCR)是针对基于任务的运行时系统的最新成果,用于超大规模并行系统。我们已经在TBB之上的共享内存环境中实现了OCR规范,为OCR联盟创建的实现提供了替代方法。我们创建了一个实验性扩展,该扩展支持使用OpenCL编程的并行加速器。我们还有一个针对分布式内存系统的实现。尽管处于开发的早期阶段,我们的实现仍可以通过某些应用程序实现合理的性能。我们描述了OCR实现的主要方面,并报告了共享内存和分布式内存系统的早期实验结果。

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