Accelerating Sorting on GPUs: A Scalable CUDA Quicksort Revision

Mehmed Mujić, Irvin Ćatić, Samra Behić, Amila Hadžibajramović, N. Nosovic, Tarik Hrnjić
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引用次数: 1

Abstract

In this article, an upgraded version of CUDA-Quicksort - an iterative implementation of the quicksort algorithm suitable for highly parallel multicore graphics processors, is described and evaluated. Three key changes which lead to improved performance are proposed. The main goal was to provide an implementation with increased scalability with the size of data sets and number of cores with modern GPU architectures, which was successfully achieved. The proposed changes also lead to significant reduction in execution time. The execution times were measured on an NVIDIA graphics card, taking into account the possible distributions of the input data.
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gpu加速排序:一个可扩展的CUDA快速排序修订
在本文中,描述和评估了CUDA-Quicksort的升级版本-适用于高度并行多核图形处理器的快速排序算法的迭代实现。提出了导致性能提高的三个关键变化。我们的主要目标是通过现代GPU架构提供具有更高可扩展性的数据集大小和核心数量的实现,这已经成功实现了。建议的更改还可以显著减少执行时间。考虑到输入数据的可能分布,在NVIDIA显卡上测量了执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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