使用多线程增强高阶哈恩多项式的性能增强
Basheera M Mahmmod1, Wameedh Nazar Flayyih1, Zainab Hassan Fakhri1
1Department of Computer Engineering, University of Baghdad, Baghdad, Iraq.
PloS one
|October 25, 2023
概括
本研究引入了一种快速的多线程方法来计算高阶离散汉多项式 (DHaPs),这对于图像处理至关重要. 该方法显著减少了计算时间,特别是对于大多项式大小,提高了计算机视觉应用程序的效率.
科学领域:
- 计算机视觉 计算机视觉
- 数字分析 数字分析
- 计算数学 计算数学 计算数学
背景情况:
- 正角多项式,包括离散的哈恩多项式 (DHaPs),在图像处理和计算机视觉中对于压缩和特征提取等任务至关重要.
- 对DHaP的高阶计算可能会导致数值不稳定,这对实际应用构成挑战.
研究的目的:
- 提出一种快速的,多线程的方法来计算高阶离散的哈恩多项式.
- 解决与高阶DHaP相关的数值不稳定性问题.
- 使用并行处理优化DHaP的计算性能.
主要方法:
- 利用多线程来并行计算哈恩多项式系数的计算.
- 实施一种分布方法,以实现跨线程的均衡处理负载.
- 用各种DHaPs参数,矩阵大小和线数测试拟议的方法.
主要成果:
- 与非线程计算相比,在处理时间上显著改进,与多项式大小成比例增加.
- 对于8000x8000的多项式大小和顺序,实现了5.8的最大加速度因子.
- 确定了最大性能的最佳线程范围,并指出过多的线程会导致回报减少或性能降低.
结论:
- 拟议的多线程方法为计算高阶离散哈恩多项式提供了有效的解决方案.
- 平行处理有效地减轻了计算瓶,并提高了图像处理和计算机视觉任务的性能.
- 需要仔细考虑线程数量,以最大限度地提高性能效益,因为可扩展性在某个特定点以外是不线性的.
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