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Out-of-core divisible load processing

机译：核外可分割负载处理

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摘要

In this paper, we analyze processing divisible loads in systems with a memory hierarchy. Divisible loads are computations that can be divided into parts of arbitrary sizes and these parts can be independently processed in a distributed system. The problem is to partition the load so that the total processing time, including communications and computations, is the shortest possible. Earlier works in the divisible load theory assumed distributed systems with a flat memory model. The dependence of the processing time on the size of the assigned load was assumed to be linear. A new mathematical model relaxing the above two assumptions is proposed in this article. We study distributed systems-which have both the hierarchical memory model and a piecewise linear dependence of the processing time on the size of the assigned load. Performance of such systems is modeled and evaluated. Finally, we compare the efficiency of distributed processing divisible loads in multiinstallment and out-of-core modes. Multiinstallment processing consists in sending multiple small chunks of the load to processors instead of a single chunk which needs external memory. It turns out that multiinstallment is an advantageous strategy for reasonably selected load chunks sizes.
机译：在本文中，我们分析具有内存层次结构的系统中的可分割负载处理。可分负荷是可以分为任意大小的部分的计算，并且这些部分可以在分布式系统中独立处理。问题在于分配负载，以使包括通信和计算在内的总处理时间最短。在可分负荷理论中，较早的工作假设分布式系统具有平面内存模型。假定处理时间与分配的负载大小的关系是线性的。本文提出了一个放松上述两个假设的新数学模型。我们研究分布式系统，该系统既具有分层存储模型，又具有处理时间与分配负载大小的分段线性相关性。对此类系统的性能进行建模和评估。最后，我们比较了多安装和核心外模式下分布式处理可分割负载的效率。多次安装处理包括将负载的多个小块发送到处理器，而不是需要外部存储器的单个块。事实证明，对于合理选择的负载块大小，多次安装是一种有利的策略。

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