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FINE-GRAINED MULTITHREADING SUPPORT FOR HYBRID THREADED MPI PROGRAMMING

机译:混合线程MPI编程的精细多线程支持

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摘要

As high-end computing systems continue to grow in scale, recent advances in multi- and many-core architectures have pushed such growth toward more dense architectures, that is, more processing elements per physical node, rather than more physical nodes themselves. Although a large number of scientific applications have relied so far on an MPI-everywhere model for programming high-end parallel systems; this model may not be sufficient for future machines, given their physical constraints such as decreasing amounts of memory per processing element and shared caches. As a result, application and computer scientists are exploring alternative programming models that involve using MPI between address spaces and some other threaded model, such as OpenMP, Pthreads, or Intel TBB, within an address space. Such hybrid models require efficient support from an MPI implementation for MPI messages sent from multiple threads simultaneously. In this paper, we explore the issues involved in designing such an implementation. We present four approaches to building a fully thread-safe MPI implementation, with decreasing levels of critical-section granularity (from coarse-grain locks to fine-grain locks to lock-free operations) and correspondingly increasing levels of complexity. We present performance results that demonstrate the performance implications of the different approaches.
机译:随着高端计算系统规模的不断扩大,多核和多核体系结构的最新进展已将这种增长推向更密集的体系结构,即每个物理节点更多的处理元素,而不是更多物理节点本身。尽管到目前为止,大量的科学应用都依赖于MPI无处不在模型来对高端并行系统进行编程;考虑到它们的物理限制(例如减少每个处理元素的内存量和共享缓存),该模型可能不足以适应将来的机器。结果,应用程序和计算机科学家正在探索替代编程模型,这些模型涉及在地址空间和地址空间内的其他某些线程化模型(例如OpenMP,Pthreads或Intel TBB)之间使用MPI。此类混合模型需要MPI实施为来自多个线程的MPI消息同时提供有效的支持。在本文中,我们探讨了设计此类实现所涉及的问题。我们提出了四种构建完全线程安全的MPI实现的方法,这些方法降低了临界区的粒度(从粗粒度锁到细粒度锁再到无锁操作),并且相应地增加了复杂度。我们提供的性能结果证明了不同方法对性能的影响。

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