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A Block Streaming Model for Irregular Applications

机译:不规则应用的块流媒体模型

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摘要

Due to worsening machine balance, a lightweight irregular application can utilize only a small fraction of the peak computational capacity on modern processors. Performance of such an application is also unpredictable due to the scattered data accesses. Even though some architectural features are commonly found in most of the modern processors (such as a cache system, hardware prefetchers etc.), their design parameters differ widely from one processor to another. Therefore, a performance improving programming technique still needs extensive tuning to gain maximum benefit on a target processor. In this scenario, achieving portable performance becomes difficult. This work proposes a block streaming machine model and hypothesizes that an algorithm based on the model has predictable execution time. To enable adaptation of this model for irregular applications, we also provide algorithmic transformations that can be used to replace the scattered accesses with streaming accesses in a cost predictable way. Further, we experimentally demonstrate usefulness of the model and the transformations for static lightweight irregular computations such as those performed by a numerical partial differential equation solver.
机译:由于机器平衡恶化,轻量级的不规则应用可以仅利用现代处理器上的峰值计算能力。由于分散的数据访问,这种应用的性能也是不可预测的。尽管在大多数现代处理器(例如高速缓存系统,硬件预取器等)中常见的一些架构特征,但它们的设计参数将从一个处理器差别不同于另一个处理器。因此,性能提高编程技术仍然需要广泛的调谐,以获得在目标处理器上的最大利益。在这种情况下,实现便携式性能变得困难。这项工作提出了一个块流式流机型,并假设基于模型的算法具有可预测的执行时间。为了使这种模型适应不规则应用,我们还提供算法转换,可用于以成本可预测的方式用流程访问替换分散的访问。此外,我们通过实验证明了模型的有用性以及静态轻质不规则计算的变换,例如由数值偏微分方程求解器执行的那些。

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